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Computer Engineering

The research focus of the Computer Engineering group at Yale University is on reliable and secure architectures and computing platforms. Research projects are led by faculty members in Electrical Engineering , in collaboration with Computer Science  and other Yale departments.

Current strengths of the group include: Computer Architecture, Hardware Security, FPGA, Integrated Circuits, VLSI, Sensors and Sensor Networks.

These strengths form a unique set of expertise that allows the Yale Computer Engineering group to tackle a variety of timely and acclaimed research projects.

• Many-core processor architectures
• System-on-Chip or Smartphone architectures
• Secure hardware-software architectures
• Sensor networks for monitoring and security
• Data center architecture and security 

The "Computer Systems Lab" is an interdisciplinary laboratory with faculty from both Electrical Engineering and Computer Science that have a shared research interest in computer systems.

Research Summaries for EE Computer Engineering Area by Faculty:

Rajit Manohar :  The theory, automation, design and implementation of asynchronous (clockless/self-timed) circuits, architectures, and systems.

Jakub Szefer :  Secure hardware-software architectures for servers and mobile devices; Many-core processor architectures with security features, Hardware trust evidence; Design for security and energy efficiency; Security architecture verification; Cloud computing security; Data center security.

Wenjun Hu : Design, prototyping, and empirical measurements and analysis of networked systems - data communication, network architectures, wireless and mobile networking, information theory applied to network and system design, smartphone based visual communications, multimedia communication, and MIMO systems.

Priyadarshini Panda : Neuromorphic Computing: spanning energy-efficient design methodologies for deep learning networks, novel supervised/unsupervised learning algorithms for spiking neural networks and developing neural architectures for new computing scenarios (such as lifelong learning, generative models, stochastic networks, adversarial attacks etc.).

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Hiring CS Graduates: What We Learned from Employers

Computer science ( CS ) majors are in high demand and account for a large part of national computer and information technology job market applicants. Employment in this sector is projected to grow 12% between 2018 and 2028, which is faster than the average of all other occupations. Published data are available on traditional non-computer science-specific hiring processes. However, the hiring process for CS majors may be different. It is critical to have up-to-date information on questions such as “what positions are in high demand for CS majors?,” “what is a typical hiring process?,” and “what do employers say they look for when hiring CS graduates?” This article discusses the analysis of a survey of 218 recruiters hiring CS graduates in the United States. We used Atlas.ti to analyze qualitative survey data and report the results on what positions are in the highest demand, the hiring process, and the resume review process. Our study revealed that a software developer was the most common job the recruiters were looking to fill. We found that the hiring process steps for CS graduates are generally aligned with traditional hiring steps, with an additional emphasis on technical and coding tests. Recruiters reported that their hiring choices were based on reviewing resume’s experience, GPA, and projects sections. The results provide insights into the hiring process, decision making, resume analysis, and some discrepancies between current undergraduate CS program outcomes and employers’ expectations.

A Systematic Literature Review of Empiricism and Norms of Reporting in Computing Education Research Literature

Context. Computing Education Research (CER) is critical to help the computing education community and policy makers support the increasing population of students who need to learn computing skills for future careers. For a community to systematically advance knowledge about a topic, the members must be able to understand published work thoroughly enough to perform replications, conduct meta-analyses, and build theories. There is a need to understand whether published research allows the CER community to systematically advance knowledge and build theories. Objectives. The goal of this study is to characterize the reporting of empiricism in Computing Education Research literature by identifying whether publications include content necessary for researchers to perform replications, meta-analyses, and theory building. We answer three research questions related to this goal: (RQ1) What percentage of papers in CER venues have some form of empirical evaluation? (RQ2) Of the papers that have empirical evaluation, what are the characteristics of the empirical evaluation? (RQ3) Of the papers that have empirical evaluation, do they follow norms (both for inclusion and for labeling of information needed for replication, meta-analysis, and, eventually, theory-building) for reporting empirical work? Methods. We conducted a systematic literature review of the 2014 and 2015 proceedings or issues of five CER venues: Technical Symposium on Computer Science Education (SIGCSE TS), International Symposium on Computing Education Research (ICER), Conference on Innovation and Technology in Computer Science Education (ITiCSE), ACM Transactions on Computing Education (TOCE), and Computer Science Education (CSE). We developed and applied the CER Empiricism Assessment Rubric to the 427 papers accepted and published at these venues over 2014 and 2015. Two people evaluated each paper using the Base Rubric for characterizing the paper. An individual person applied the other rubrics to characterize the norms of reporting, as appropriate for the paper type. Any discrepancies or questions were discussed between multiple reviewers to resolve. Results. We found that over 80% of papers accepted across all five venues had some form of empirical evaluation. Quantitative evaluation methods were the most frequently reported. Papers most frequently reported results on interventions around pedagogical techniques, curriculum, community, or tools. There was a split in papers that had some type of comparison between an intervention and some other dataset or baseline. Most papers reported related work, following the expectations for doing so in the SIGCSE and CER community. However, many papers were lacking properly reported research objectives, goals, research questions, or hypotheses; description of participants; study design; data collection; and threats to validity. These results align with prior surveys of the CER literature. Conclusions. CER authors are contributing empirical results to the literature; however, not all norms for reporting are met. We encourage authors to provide clear, labeled details about their work so readers can use the study methodologies and results for replications and meta-analyses. As our community grows, our reporting of CER should mature to help establish computing education theory to support the next generation of computing learners.

Light Diacritic Restoration to Disambiguate Homographs in Modern Arabic Texts

Diacritic restoration (also known as diacritization or vowelization) is the process of inserting the correct diacritical markings into a text. Modern Arabic is typically written without diacritics, e.g., newspapers. This lack of diacritical markings often causes ambiguity, and though natives are adept at resolving, there are times they may fail. Diacritic restoration is a classical problem in computer science. Still, as most of the works tackle the full (heavy) diacritization of text, we, however, are interested in diacritizing the text using a fewer number of diacritics. Studies have shown that a fully diacritized text is visually displeasing and slows down the reading. This article proposes a system to diacritize homographs using the least number of diacritics, thus the name “light.” There is a large class of words that fall under the homograph category, and we will be dealing with the class of words that share the spelling but not the meaning. With fewer diacritics, we do not expect any effect on reading speed, while eye strain is reduced. The system contains morphological analyzer and context similarities. The morphological analyzer is used to generate all word candidates for diacritics. Then, through a statistical approach and context similarities, we resolve the homographs. Experimentally, the system shows very promising results, and our best accuracy is 85.6%.

A genre-based analysis of questions and comments in Q&A sessions after conference paper presentations in computer science

Gender diversity in computer science at a large public r1 research university: reporting on a self-study.

With the number of jobs in computer occupations on the rise, there is a greater need for computer science (CS) graduates than ever. At the same time, most CS departments across the country are only seeing 25–30% of women students in their classes, meaning that we are failing to draw interest from a large portion of the population. In this work, we explore the gender gap in CS at Rutgers University–New Brunswick, a large public R1 research university, using three data sets that span thousands of students across six academic years. Specifically, we combine these data sets to study the gender gaps in four core CS courses and explore the correlation of several factors with retention and the impact of these factors on changes to the gender gap as students proceed through the CS courses toward completing the CS major. For example, we find that a significant percentage of women students taking the introductory CS1 course for majors do not intend to major in CS, which may be a contributing factor to a large increase in the gender gap immediately after CS1. This finding implies that part of the retention task is attracting these women students to further explore the major. Results from our study include both novel findings and findings that are consistent with known challenges for increasing gender diversity in CS. In both cases, we provide extensive quantitative data in support of the findings.

Designing for Student-Directedness: How K–12 Teachers Utilize Peers to Support Projects

Student-directed projects—projects in which students have individual control over what they create and how to create it—are a promising practice for supporting the development of conceptual understanding and personal interest in K–12 computer science classrooms. In this article, we explore a central (and perhaps counterintuitive) design principle identified by a group of K–12 computer science teachers who support student-directed projects in their classrooms: in order for students to develop their own ideas and determine how to pursue them, students must have opportunities to engage with other students’ work. In this qualitative study, we investigated the instructional practices of 25 K–12 teachers using a series of in-depth, semi-structured interviews to develop understandings of how they used peer work to support student-directed projects in their classrooms. Teachers described supporting their students in navigating three stages of project development: generating ideas, pursuing ideas, and presenting ideas. For each of these three stages, teachers considered multiple factors to encourage engagement with peer work in their classrooms, including the quality and completeness of shared work and the modes of interaction with the work. We discuss how this pedagogical approach offers students new relationships to their own learning, to their peers, and to their teachers and communicates important messages to students about their own competence and agency, potentially contributing to aims within computer science for broadening participation.

Creativity in CS1: A Literature Review

Computer science is a fast-growing field in today’s digitized age, and working in this industry often requires creativity and innovative thought. An issue within computer science education, however, is that large introductory programming courses often involve little opportunity for creative thinking within coursework. The undergraduate introductory programming course (CS1) is notorious for its poor student performance and retention rates across multiple institutions. Integrating opportunities for creative thinking may help combat this issue by adding a personal touch to course content, which could allow beginner CS students to better relate to the abstract world of programming. Research on the role of creativity in computer science education (CSE) is an interesting area with a lot of room for exploration due to the complexity of the phenomenon of creativity as well as the CSE research field being fairly new compared to some other education fields where this topic has been more closely explored. To contribute to this area of research, this article provides a literature review exploring the concept of creativity as relevant to computer science education and CS1 in particular. Based on the review of the literature, we conclude creativity is an essential component to computer science, and the type of creativity that computer science requires is in fact, a teachable skill through the use of various tools and strategies. These strategies include the integration of open-ended assignments, large collaborative projects, learning by teaching, multimedia projects, small creative computational exercises, game development projects, digitally produced art, robotics, digital story-telling, music manipulation, and project-based learning. Research on each of these strategies and their effects on student experiences within CS1 is discussed in this review. Last, six main components of creativity-enhancing activities are identified based on the studies about incorporating creativity into CS1. These components are as follows: Collaboration, Relevance, Autonomy, Ownership, Hands-On Learning, and Visual Feedback. The purpose of this article is to contribute to computer science educators’ understanding of how creativity is best understood in the context of computer science education and explore practical applications of creativity theory in CS1 classrooms. This is an important collection of information for restructuring aspects of future introductory programming courses in creative, innovative ways that benefit student learning.

CATS: Customizable Abstractive Topic-based Summarization

Neural sequence-to-sequence models are the state-of-the-art approach used in abstractive summarization of textual documents, useful for producing condensed versions of source text narratives without being restricted to using only words from the original text. Despite the advances in abstractive summarization, custom generation of summaries (e.g., towards a user’s preference) remains unexplored. In this article, we present CATS, an abstractive neural summarization model that summarizes content in a sequence-to-sequence fashion while also introducing a new mechanism to control the underlying latent topic distribution of the produced summaries. We empirically illustrate the efficacy of our model in producing customized summaries and present findings that facilitate the design of such systems. We use the well-known CNN/DailyMail dataset to evaluate our model. Furthermore, we present a transfer-learning method and demonstrate the effectiveness of our approach in a low resource setting, i.e., abstractive summarization of meetings minutes, where combining the main available meetings’ transcripts datasets, AMI and International Computer Science Institute(ICSI) , results in merely a few hundred training documents.

Exploring students’ and lecturers’ views on collaboration and cooperation in computer science courses - a qualitative analysis

Factors affecting student educational choices regarding oer material in computer science, export citation format, share document.

PhD in Computer Engineering

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• Electrical & Computer Engineering

Degree Details

As a computer engineering PhD student, you will pursue theoretical and empirical studies alongside our world-renowned faculty. Students can enter the program directly after completing a bachelors degree, and earn a masters degree along the way. Students can also enter the program after completing a masters degree.

Degree Type

Tremendous research opportunities.

Electrical & Computer Engineering (ECE) faculty members boast international reputations and provide students with  opportunities for research , for example, in such areas as:  Computer Networking and Distributed Systems, Computer Engineering, Software Engineering and Applications, Communication, Sensor Networks, and Cybersecurity.  You can learn more about research in these areas by visiting  Mobile/Cloud Computing and Cybersecurity  and  BioECE and Digital Health .

The ECE PhD Student Experience

As a computer engineering PhD student, you will pursue theoretical and empirical studies in a topic area determined by your interests and those of your faculty research advisor. As a student in Boston, you will be in the midst of a vibrant high-tech research community where external collaborations with industry, government, and other universities are common. However, your experience will likely not be limited to Boston; PhD students are supported by the Department to present their work at many key conferences around the world.

Program Requirements

Post Bachelors:  A total of 64 graduate-level credits, 32 of which must meet the MS-EE requirements. A successfully defended PhD prospectus may be used to satisfy the MS thesis/project requirement.

Post Masters:  A total of 32 graduate-level credits.

For all PhD students: PhD Qualifying Process and Achieving Candidacy, Prospectus and Final Defenses & Teaching/Residency/Math Requirements.

Note : In structured courses, only grades of B- or higher are accepted for fulfilling PhD credit requirements. In non-structured (P/F) courses, the P grade is acceptable for fulfilling PhD requirements. PhD students who receive grades of C+ or lower in 3 courses will be withdrawn from the program.

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• Teaching/Residency/Math Requirements

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• Northwestern Engineering

Research in the Department of Electrical and Computer Engineering spans a wide range of disciplines that are essential to the growing field of information technology. Our faculty members and students have developed new ideas to achieve results in all aspects of electrical engineering, computer engineering, and computer science.

Because our department is home to research in electrical engineering and computer engineering, as well as different subareas in each of those fields, natural synergies occur between and among faculty members and students.

Areas of research in the Department of Electrical and Computer Engineering spans a diverse set of intellectual disciplines.

Research experience is an integral part of advanced undergraduate education, especially for students planning to enter graduate school.

Learn more about undergraduate research in the Department of Electrical and Computer Engineering

Groups and Labs

The Department of Electrical and Computer Engineering is home to more than 20 groups and labs, supporting the research of our faculty members and students.

Learn more about groups and labs in the Department of Electrical and Computer Engineering

Our award-winning faculty members oversee and participate in several research centers at Northwestern.

Learn more about the research centers in the Department of Electrical and Computer Engineering

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Department of Electrical and Computer Engineering McCormick School of Engineering and Applied Science Northwestern University 2145 Sheridan Road, Room L359 Evanston, IL 60208 Phone: 847-491-5410 Fax: 847-491-4455

Computer Science and Engineering

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Research & Innovation at CSE

Research at the Department of Computer Science and Engineering is conducted by faculty members and students in three research centers and eighteen laboratories of various areas.

CRA, Computing Research Association, Bulletin

Research Centers

The Center for Information and Cyber Security (CICS) has helped UNT earn the designation of "Center of Academic Excellence in Information Assurance Education" and "Center for Academic Excellence in Research" from the National Security Agency and Department of Homeland Security for its strong computer and information security program. This designation places UNT among the top institutions in the country in the field of computer security.

Net-Centric & Cloud Software & Systems (NCSS) Industry & University Cooperative Research Center (I/UCRC) focuses on a collaborative approach of research and development in net-centric and cloud computing systems. This allows us to draw on the expertise of industry and academia. Net-Centric and cloud computing operations offer a computing model for the future. In this paradigm, we no longer view applications as having a fixed set of capabilities: we see them as a set of highly reliable services that are dynamically created from acquired services, then verified and validated in the field in real-time. The center explores the development, verification, validation of applications and systems for net-centric and cloud environments such that the applications and services meet service level agreements (SLAs) including response time, reliability and security.

Research Areas and Labs

Algorithms and computational science.

Algorithms, Combinatorics, and Graph Theory (ACG) is a laboratory whose goal is to improve the theoretical/practical efficiency of algorithms. We aim at developing new branches of Graph Theory/Combinatorics that can aid in modeling, and effectively solving (exactly or approximately), a wide range of computationally hard problems. For related conferences see  Workshop on Algorithms, Combinatorics, and Geometry .

Uncertainty quantification lab develops computational methods for the main aspects of uncertainty quantification, including model correction, parametric uncertainty analysis, non-probabilistic uncertainty modeling, sensitivity analysis, and applies the uncertainty quantification techniques to various disciplines such as biology and engineering.

Artificial Intelligence and Data Science

The Biocomputing Research Group focuses on developing Bioinformatics tools and applying revolutionary technologies to critical scientific and engineering applications related to biology and medical science.

The Biomedical AI Lab develops machine learning tools to predict or precisely measure the outcomes of medical interventions, collaborating extensively with hospitals and medical schools. Although artificial intelligence techniques and clinical populations are highly varied, a major theme is tailored wearable device analytics to assess therapies for individuals with impaired mobility, including past research populations with Parkinson’s disease, lower-limb amputations, incomplete spinal cord injury, and cerebral palsy.

The Computer Vision and Intelligent Systems Laboratory (CoVIS) is to advance the understanding of the theories of machine learning for processing complex data and to develop applications in areas such as medicine, geo-information, etc. The research focuses on both algorithm innovation and hardware integration, which includes computer vision, pattern recognition, data mining, and artificial intelligence. The CoVIS lab is facilitated with the state-of-the-art computing resources and various imaging technologies. The lab provides both graduate and undergraduate students a unique, collaborative research cohort to further their career goals.

The Human Intelligence and Language Technologies (HiLT) lab focuses on research on natural language processing (NLP), machine learning (ML), and cognitive science, with an emphasis on Spoken-Dialogue Educational Health & Wellbeing Companion Robots (Companionbots), Educational Technology, Health & Clinical Informatics, and End-User Software Engineering.

The Information Retrieval and Text Mining Lab focuses on developing a variety of general techniques for representing, searching, filtering, organizing, and mining text information, with applications in multiple domains including the Web, homeland security, and biomedical and health informatics. The research draws on methods from information theory, natural language processing, and data mining to tackle problems in information retrieval and discovery, and emphasizes on both fundamental research and system development.

The Multimedia Information Laboratory conducts research on multimedia material (videos and images) processing, multimedia information extraction, and multimedia information modeling and retrieval, which include video and image segmentation, motion and color analysis, image quality analysis, and object recognition by region clustering and classification.

Computer Systems and Networks

The Computer Systems Research Laboratory focuses its work on researching multithreaded and multicore architectures for both embedded and high-performance applications. Research includes work in processing architectures, memory systems, cache memories and software tools to utilize the special capabilities of underlying hardware systems, and in developing both hardware and software solutions to improve performance, reduce energy consumption and prevent security breaches.

The Dependable Computing Systems Laboratory conducts research on failure modeling, failure management, adaptive failure resilience, failure-aware resource management, and power-aware dependable computing. The lab conducts both fundamental and applied research to develop highly dependable and energy-efficient distributed and cloud computing systems.

The Energy-Efficient High Performance Computing Laboratory focuses on designing computer systems that achieve high performance with limited power budgets. Our research spans across multiple areas of micro architecture design, which includes embedded systems, multi-core processors, memory hierarchies, on-chip interconnections and accelerators.

The Smart Electronic Systems Laboratory (SESL) conducts research in Smart Electronics for the efficient realization of Internet-of-Things (IoT) based components for Smart Cities. The key aspects of the smart electronics are envisioned to be Energy-Smart, Security-Smart, and Response-Smart. Energy-Smart ensures that energy consumption of electronics is minimal for longer battery life. Security-Smart deals with the security/protection of electronics as well as that of the information/media that these systems capture, process, or store. Response-Smart refers to accurate sensing, intelligent processing, and fast actuation/response. Smart Electronics in the framework of IoT can provide 3Is (Instrumentation, Interconnection, and Intelligence) to the Smart Cities. Optimal combinations of hardware and software modules are explored for ESR-smartness of electronic systems.

Wireless Sensor Laboratory (WiSL) was established with the following mission: to increase general wireless communications awareness among computer science and engineering graduates, produce skilled wireless specialists, and conduct research and development activities to advance the state-of-the-art in wireless sensors.

Cybersecurity

The Network Security Laboratory was established to increase general wireline and wireless network security awareness of computer science and engineering graduates, to produce skilled security specialists, and to conduct research and development activities to advance the state-of-the-art in wireline and wireless network security and communication.

Software Engineering

The Laboratory for Recreational Computing (LARC) serves as a center for research, education and development in the field of video game programming.

The Research Innovation in Software Engineering (RISE) laboratory explores advances in software engineering through the areas of compiler design, domain-specific programming languages, human-computer interaction, logic programming, model-driven engineering, and software testing.

Electrical and Computer Engineering Doctor of Philosophy (Ph.D.) Degree

Request Info about graduate study Visit Apply

Ph.D.s in electrical and computer engineering are explorers of the information age who transform the world by leading trailblazing research that expands and create knowledge.

STEM-OPT Visa Eligible

Overview for Electrical and Computer Engineering Ph.D.

• Knowledge and Skills to Form Successful Researchers: A plan of study that consists of course work and research. Do research under the guidance of the world-class researchers that comprise our faculty.
• Forming Independent Researchers to Transform the World: World-class research in: (1) architectures and devices for computing; (2) communications, networking, and security; (3) machine learning and artificial intelligence; and (4) cyber-physical and embedded systems.

This is an exciting time in electrical and computer engineering. Harnessing electricity not only provides humanity with a transformative form of energy, but it also leads to the development of digital technologies, which have forged our Information Age as a time of revolutionary advances developed at an unprecedented pace.

The 21st century has witnessed such advances as the Smart Grid, ubiquitous fast internet access through wireless networks, artificial intelligence and machine learning technologies that rival humans in performance, the Internet-of-Things, cloud computing, fiber-optic networks capable of transmitting trillions of bits per second, new computing paradigms such as quantum or neuromorphic computing, and many more. None of these advances would have happened without the dedication of researchers in electrical and computer engineering.

Offered jointly by the department of electrical and microelectronic engineering and the department of computer engineering , students in RIT’s Ph.D. in electrical and computer engineering learn to become independent researchers by conducting research under the guidance of the world-class researchers that comprise our faculty. This research is often associated with some of the many centers and laboratories across RIT, including the Center for Human-aware AI (CHAI) and the Global Cybersecurity Institute .

The curriculum for the Ph.D. in electrical and computer engineering provides the knowledge and skills to form successful independent researchers by providing disciplinary and interdisciplinary courses, research mentorship, and seminars.

Students are also interested in: Electrical Engineering MS , Computer Engineering MS

Join us for Fall 2024

Many programs accept applications on a rolling, space-available basis.

Learn what you need to apply

Advancement of world-class impactful research is the ethos of the Ph.D. in electrical and computer engineering. The program forms a dynamic and collaborative environment where our students and faculty are developing the next wave of transformational technologies for our society by conducting research in the following areas:

• Architectures and Devices for Computing
• Communications, Networking and Security
• Machine Learning and Artificial Intelligence
• Cyber-physical and Embedded Systems

Are you a doctoral student interested in participating in our research? Learn more about research assistantship opportunities across the Kate Gleason College of Engineering and how you can apply.

Jamison Heard

Dorin Patru

Shanchieh Yang

Featured Work

Forging the Future of AI and Security through Memory-centric Computing

Ph.D. Student: Purab Sutradhar

Pursuing his Ph.D. in Electrical and Computer Engineering, Purab Sutradhar is at the forefront of developing cutting-edge computing solutions for data-centric and AI applications through his research...

Methods for Quantifying Power Characteristics and Chronic Patterns of Use Behavior of Electronic Vaping Products

Ph.D. Student: Qutaiba M. Saleh; Advisor: Dr. Edward Hensel

The complexity and variety of inhaled tobacco products have increased significantly with the introduction of Electronic Nicotine Delivery Systems (ENDS). Product characteristics and human behavior are...

Generative AI enabled Cybersecurity Operations

Shanchieh Jay Yang

The potential use of generative AI, including Large Language Models (LLMs), for cybersecurity operations may be hindered by misconceptions of its capabilities and missed opportunities to properly...

Featured Profiles

Faculty Spotlight: Dongfang Liu

Dongfang Liu

Meet Dr. Dongfang Liu, assistant professor in the department of computer engineering.

Faculty Spotlight: Dorin Patru

Associate professor at RIT since 2002, Dorin Patru teaches digital and computer, circuits and systems courses. He joined the department in fall 2002. He received a B.S. and M.S. in Electrical...

Advancing research for next generation wireless networks

Omar Abdul Latif is a student in the Electrical and Computer Engineering Ph.D. program who joined while he was working as a lecturer at RIT Dubai. He found that pursuing a Ph.D. is an...

Latest News

April 18, 2024

Engineering professor becomes part of SMART Hub to improve wireless spectrum accessibility

The wireless spectrum has become very crowded real estate, and work is underway through a new technology research center to improve spectrum access, co-existence, and security. 

April 5, 2024

Electrical engineering professor connects history with the future for today’s students

Patru’s authenticity and humor are as much a part of his classes as the informal conversations he has with students about mutual interests in space, music, art, and history. These qualities are only a few of the reasons he’s being honored with the Eisenhart Award for Outstanding Teaching.

February 29, 2024

Engineering Professor Co-Authors New Book on Resilience Engineering

Engineering professor, Andres Kwasinski co-authors new book, “Resilience Engineering for Power and Communications Systems: Networked Infrastructure in Extreme Events” published by Cambridge University Press.

Curriculum for 2023-2024 for Electrical and Computer Engineering Ph.D.

Current Students: See Curriculum Requirements

Electrical and Computer Engineering, Ph.D. degree, typical course sequence

*Engineering Foundation Electives:

† Discipline Concentration: Any graduate level course offered by the departments of Electrical and Microelectronic Engineering of Computer Engineering, exclusive of capstones.

‡ Focus Area Elective: Any graduate level course offered by the Kate Gleason College of Engineering, exclusive of capstones.

The curriculum for the Ph.D. in electrical and computer engineering provides the knowledge and skills to form successful independent researchers by providing disciplinary and interdisciplinary courses, research mentorship, and seminars. Courses are organized into three categories: core, discipline concentration elective, and focus area elective courses. In addition, the plan of study includes three major research-based milestones: the doctoral qualifying exam, the doctoral candidacy exam, and the doctoral dissertation defense.

Core Courses Core courses are usually completed during the first two semesters of the program since they serve as foundational preparation for other elective courses. Core courses develop core competency skills for research, introducing the research landscape in electrical and computer engineering, and helping to prepare students for the qualifying exam.

Discipline Concentration Elective Courses The discipline concentration elective courses provide rigorous education in a student’s specific field of research in electrical and computer engineering. Students choose courses in consultation with the dissertation and research advisor. Graduate courses offered by the department of electrical and microelectronic engineering (courses code EEEE-6/7/8xx) or the department of computer engineering (courses code CMPE-6/7/8xx).

Focus Area Elective Courses Focus area elective courses provide the curriculum flexibility for students to engage in trans-disciplinary learning. In consultation with the dissertation and research advisor, students choose graduate courses offered by any department in the Kate Gleason College of Engineering. In addition, and subject to the approval of the Ph.D. program director, students may choose graduate courses offered by any of RIT’s colleges.

Qualifying Exam Students complete a qualifying exam at the end of their first year of study. The exam evaluates the student's aptitude, potential, and competency in conducting Ph.D.-level research.

Dissertation Proposal and Candidacy Exam Students must present a dissertation proposal to their dissertation committee no sooner than six months after the qualifying exam and at least twelve months prior to the dissertation defense exam. The proposal provides the opportunity for students to elaborate on their research plans and to obtain feedback on the direction and approach to their research from their dissertation committee.

Dissertation Presentation and Defense Each doctoral candidate prepares an original, technically rigorous, and well-written dissertation that describes the candidate’s research body of work and novel contributions to the discipline of electrical and computer engineering that have resulted from the doctoral studies. In this culminating milestone, each doctoral candidate presents and defends their dissertation and its accompanying research to their dissertation committee.

Admissions and Financial Aid

This program is available on-campus only.

Full-time study is 9+ semester credit hours. International students requiring a visa to study at the RIT Rochester campus must study full‑time.

Application Details

To be considered for admission to the Electrical and Computer Engineering Ph.D. program, candidates must fulfill the following requirements:

• Complete an online graduate application .
• Submit copies of official transcript(s) (in English) of all previously completed undergraduate and graduate course work, including any transfer credit earned.
• Hold a baccalaureate degree (or US equivalent) from an accredited university or college.
• A recommended minimum cumulative GPA of 3.0 (or equivalent).
• Submit a current resume or curriculum vitae.
• Submit a statement of purpose for research which will allow the Admissions Committee to learn the most about you as a prospective researcher.
• Submit two letters of recommendation .
• Entrance exam requirements: GRE optional but recommended. No minimum score requirement.
• Writing samples are optional.
• Submit English language test scores (TOEFL, IELTS, PTE Academic), if required. Details are below.

English Language Test Scores

International applicants whose native language is not English must submit one of the following official English language test scores. Some international applicants may be considered for an English test requirement waiver .

International students below the minimum requirement may be considered for conditional admission. Each program requires balanced sub-scores when determining an applicant’s need for additional English language courses.

How to Apply   Start or Manage Your Application

Cost and Financial Aid

An RIT graduate degree is an investment with lifelong returns. Ph.D. students typically receive full tuition and an RIT Graduate Assistantship that will consist of a research assistantship (stipend) or a teaching assistantship (salary).

Access resources for students including student manual and research resources.

• ECE-PhD student manual
• KGCOE graduate student manual
• ECE-PHD Request for Qualifying Exam
• ECE-PHD Advisory Committee Formation form
• ECE-PhD Request for Candidacy Exam
• ECE-PHD Request for Research Review Meeting form
• ECE-PHD Request for Dissertation Defense
• ECE-PHD Request for Independent Study form

Research Resources

• RIT Libraries
• RIT Libraries InfoGuides
• Our librarian
• IEEE Xplore
• ACM Digital Library
• Springer Link
• SPIE Digital Library
• Elsevier Science Direct

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Electrical and Computer Engineering

College of engineering, the future is what we do. heading link copy link.

Research in electrical and computer engineering at the University of Illinois Chicago is focused on transformative technologies, inventions, and discoveries.

Our faculty members are exploring new frontiers in communications, healthcare technology, microrobots, networks and the Internet of Things, novel devices, power and renewable energy, sensor technologies, and other areas that will change the way we work and live. Research in the department is centered on the idea of improving our quality of life—harnessing change from the micro to the macro to make a tangible difference. Student research also is among our top priorities at UIC ECE, as we work to cultivate the next generation of investigators and inventors.

We invite you to explore the pages in this research section to learn more about where inquiry in electrical and computer engineering at UIC is focused today. Our featured research  page summarizes major projects that are underway or recently completed by our faculty, and the research areas and labs pages allows you to find experts and research teams by category.

What is Computer Engineering?

Computer engineering (CE) has become increasingly popular these days as a result of technology development. Many students opt for this field to pursue. The job projects are also an appealing aspect for learners.

This article gives you a comprehensive explanation of the definition and program of a computer engineering major . We also introduce some job opportunities available in this field for your reference.

Let’s read on to discover!

Computer engineering combines the principles from both electrical engineering and computer science. This major focuses on developing hardware and software for various applications, including electronics and communications networks.

Students following this major study how to build, prototype, examine circuits, microchips, processors, and some other components in a computer system.

The students also develop software to operate the applications and computer systems with the assistance of the hardware.

Computer Engineering vs. Computer Science

Computer science and engineering are both challenging and essential courses. Without computer science, you can’t wholly grasp computer engineering.

In short, computer science focuses on theoretical principles. Meanwhile, computer engineering deals with execution.

It is the goal of computer science to offer potential answers to real-world issues. Studying computer science entails a lot of arithmetic, data analysis, and developing code.

Computer engineering is more practical, asking you to perform other things by hand aside from typing. Although computer programming is crucial, you must also be competent in electronics and physics.

Computer engineers have to comprehend how circuits link, processors run, and everything else that happens to a digital device.

For more details please check this article .

What is a Computer Engineering Program?

With the background knowledge from computer science, you will advance into more specialized fields.

You’ll discover about biology, computer architecture, hardware and software, game design, computer programming, and data analysis, among other subjects you would not have thought to study about like artificial intelligence.

A capstone project would almost definitely be necessary at the end of the degree program. It requires a detailed survey, writing, and presentation.

You will have the opportunity to work on a specific computer project, leading to the next wonderful thing in the computing industry.

In a CE program, there are also other things to look forward to:

• Robots and automation subjects.
• Hands-on experience in digital operating systems and high-end embedded systems.
• Problem-solving and teamwork skills.
• Upgraded hardware or software in labs and classrooms.
• Internships at tech businesses .
• Research on the projects.
• Competitions with other universities and colleges.

Why Choose To Become a Computer Engineer?

According to the Bureau of Labor Statistics, computer engineering jobs may grow 2% from 2019 to 2029. Computer engineers tend to grow due to their tasks, which are about developing computer networks and circuits.

Becoming a computer engineer has a lot of benefits. Below are some potential scenarios for computer engineers.

The national average wage for computer engineers is almost three times that of the overall national average income. According to our report , typical computer engineers earn about $127,038 per year or $61.07 per hour.

Some computer engineers work for peripheral equipment production. These jobs have the highest salary, at about $140,840 per year.

Another plus of a profession in CE is the high demand throughout the globe. Computer engineers get the opportunity to function nearly anywhere due to our increased needs.

Competitive analysis

Computer engineers often go further than traditional analysis.

The capacity to manipulate and manage vast amounts of data is a competitive advantage. Moreover, planning, forecasting, and budgeting are beneficial means for staying ahead of the competition.

Companies can also distinguish services and products by tracking their competitors’ advertising and profits success thanks to the assistance of computer engineering.

Creativity and innovation

Computer engineer’s missions are to build optimized changes to existing items. To create new solutions, they have to consider technical trends and advancements. This feature might be highly motivating to engineers who like keeping updated and enjoy fixing problems.

What Are Computer Engineering Jobs?

Looking for a job after graduation may be stressful. Fortunately, choosing computer majors offers you lots of choices. The list of potential employers can help you choose more career options.

Software engineer

Software engineers are among the most common jobs for CE students. It requires the construction of software assisting users to do tasks on the different devices they’re using.

In general, software engineers build programs and apps that are functional with any device, making the software systems easy to use.

Hardware engineer

Hardware engineers are in charge of creating, developing, and evaluating different hardware components, including memory devices, circuit boards, and routers.

Hardware engineers need a strong partnership between creativity and technical knowledge. As a result, most companies ask enthusiasts keen to learn about the latest computer hardware advancements.

Systems analyst

All system analysts perform an in-depth study of each operating system to make recommendations for action.

Computer system analysts are necessary for most prominent firms, such as Microsoft or Dell. They have to execute sophisticated algorithms. These components make the firm’s operating systems more efficient, so the workflow can proceed smoothly.

Network architect

Network architects are responsible for designing, implementing, and supporting network and computer systems. These tasks include network architecture,  local area networks, wide area networks, intranets, and extranets.

It’s your responsibility to find out what companies want regarding data management and cooperation.

Web developer

Web development may be the most exciting job for computer engineering students. Web developers are in charge of building the web page by arranging page structures.

The programming language and operating system are the most critical part of web and software development. A web developer has to understand how the servers work before building the page.

Database administrator

A database administrator examines and monitors current software alterations as well as consumer software transactions. The motoring task is crucial since it demands utmost caution.

Because private data must stay secure, a database administrator must control the computer system and its accuracy.

Best Universities for Computer Engineering

There are numerous options for computer engineering intuitions around the world. With the sharp development of technology, many universities and colleges have decided to include this major in their coursework.

Here are some best choices all around the world:

• Stanford University in the USA
• Oxford University in England
• ETH Zurich in Switzerland
• Toronto in Canada
• Cambridge University in England
• Carnegie Mellon University in the USA

How To Get a Computer Engineering Job?

If you want to pursue a computer engineering career, you first need to obtain a bachelor’s degree in a related subject. There are tons of job choices with this level of degree.

On the other hand, you may think about getting a master’s degree after earning a bachelor’s degree.

There are also several online CE classes accessible. A master’s degree might enhance your potential and give you the opportunities to accelerate to senior or leadership positions.

You can also specialize in sectors like software engineering or network security, depending on your interests.

It’s essential to have excellent problem-solving, design, and communication skills in addition to standard schooling. These qualities might offer you a leg up on the competition when it comes to opening a profession as a computer engineer.

Frequently Asked Questions

What is a computer engineer’s starting income.

An entry-level computer engineer earns an average of $79,881 per year. A skilled computer engineer can earn an annual salary of $196,540.

Do computer engineers write code?

Although a computer engineer frequently works as a coder, web developers are the ones who create most of the programs, such as operating computer systems and networks. A computer engineer, on the other hand, is in charge of creating the algorithms for computer-based solutions.

What are the pros and cons of this profession?

Working as a computer engineer allows you to work in groups, use your skills at home, and achieve professional progression.

The disadvantage of this field is that the workplace is often the same. Engineers suffer from the high pressure of work and have to be devoted to work overtime.

We have shared with you some necessary information about computer engineering. Job opportunities in this field are expected to expand continuously in the future. The demand for computer engineers is always high in response to market development.

If you like learning how computers operate, upgrading them, and providing new models, you should pursue CE degrees .

• How to Become a Computer Engineer
• How To Get Computer Engineering Degree
• Guide To The Computer Engineering Major
• Computer Engineering vs. Electrical Engineering
• What Can You Do With a Computer Engineering Degree?
• Computer Engineering vs. Software Engineering
• Computer Engineer Career Overview & Outlook
• How To Prepare for Computer Engineering in High School
• 4 Types of Computer Engineering Courses
• Master’s in Computer Engineering: Is it Worth it?

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May 7, 2024

This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:

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trusted source

A guide for early-career researchers in computational science

by Samuel Jarman, SciencePOD

In recent years, a growing number of students have embraced scientific computation as an integral component of their graduate research. Yet since many of them are new to the field, they often have little to no coding experience, or any prior knowledge of computational tools. For many students starting out in the field, this can seem daunting, and leaves them unsure of where to start.

In a new article published in The European Physical Journal Plus , a team led by Idil Ismail, a current graduate student at the University of Warwick, UK, present an introductory guide to the field for researchers embarking on new careers.

The team's work will help new graduate students to navigate the complexities of scientific computation science as they begin their journey in computational science research, and could ultimately help the wider field to become more transparent and inclusive.

Modern computational science is now being used in a wide array of subject areas: including mathematics, physics, chemistry, engineering, and the life sciences . Yet despite their many differences, these different branches of the field share many of the same techniques, which graduate students will need to learn regardless of the area they decide to pursue.

In their article, Ismail's team aim to highlight the universal skills, themes, and methods widely used by computational scientists. In nine carefully structured sections, they cover a broad spectrum of important techniques: including scientific programming, machine learning , and Bash scripting, With its approachable and instructive tone, the article is not intended as an exhaustive guide.

Instead, it acts as a useful starting point: signposting readers to more in-depth sources, and encouraging them to expand their knowledge by seeking out information for themselves. Altogether, the team's work will help early-career computational scientists to build a toolkit of indispensable skills, and will be a valuable resource for any graduate student entering the field.

Provided by SciencePOD

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Computer Science and Engineering Research

The Department of Computer Science and Engineering has many opportunities for undergraduate students to engage in research during the academic year and the summer. Also, all students in the computer science and engineering track of the Engineering Honors Program participate in an intensive undergraduate research experience, culminating in an honors thesis.

Research News

How ‘Computer Science for All’ initiatives affect students’ college and career outcomes

Subscribe to the brown center on education policy newsletter, jing liu , jing liu assistant professor of education policy - university of maryland-college park @drjingliu cameron conrad , and cameron conrad ph.d. candidate - university of maryland david blazar david blazar associate professor - university of maryland @david_blazar.

May 1, 2024

• Thirty states have adopted “CS for All” policies, which require all high schools to offer CS coursework, while eight states have gone a step further in requiring all students to take CS as a high school graduation requirement.
• Exposure to high school CS coursework raises CS BA receipt and improves early-career labor market outcomes.
• Although positive long-run impacts of CS course exposure are stronger for historically underrepresented groups, CS course take-up rates are lower among these students.

As the U.S. economy becomes more digitalized, employment in computer and information technology occupations is projected to grow by 10% in the next decade. In response to this increasing demand for technology skills, many states are working to expand CS learning opportunities across K-12 classrooms. Thirty states have adopted “CS for All” policies, which require all high schools to offer CS coursework, while eight states have gone a step further in requiring all students to take CS as a high school graduation requirement. Despite heightened policy interest in CS access, however, research is surprisingly sparse on how the expansion of CS coursework affects postsecondary and labor market outcomes.

In a recent working paper , we aim to fill this research gap by investigating the impact of the expansion of high school CS course offerings. The State of Maryland, which is the context of our study, has rapidly expanded CS course offerings over the last decade. A 2018 law further requires all Maryland high schools to offer at least one “high-quality” CS course aligned with rigorous K-12 CS standards. These “high-quality” courses include foundational courses such as Computer Science Essentials, AP courses such as AP Computer Science Principles, and more specialized programming courses. They are also closely aligned with Code.org’s definition of “foundational” CS courses.

Using rich longitudinal data from the Maryland Longitudinal Data System (MLDS) Center, our study is among the first that offers causal evidence on how access to these “high-quality” CS courses in high school affects college major choice and early-career earnings. Our research design exploits the fact that high schools adopted CS courses at different points in time. In a nutshell, we compare cohorts of students who were exposed to CS to prior cohorts of students from the same high school that were not exposed to CS. This design allows us to estimate causal impacts of both CS course offering and CS course-taking.

Finding #1: Exposure to high school CS coursework raises CS BA receipt and improves early-career labor market outcomes.

Taking a high school CS course leads to a large, five-percentage-point increase in students’ likelihood of earning a bachelor’s degree in CS. Figure 1 shows the estimated effects of taking a CS course in high school on the likelihood of completing a bachelor’s degree for a selection of subjects. Though only the point estimate on CS majors is statistically significant, the negative coefficients for other STEM fields, social sciences, and humanities suggest students may be switching from these fields into CS.

We also find positive impacts on employment and earnings at age 24: High schools offering high-quality CS courses raise students’ likelihood of being employed by 2.6 percentage points and annual earnings by about eight percent. Importantly, these estimates are based on all students, not just those who pursue CS in their later studies or careers.

These findings on degree receipt are similar in magnitude to prior research on STEM course-taking. For example, one study has found that taking advanced secondary science coursework raises STEM degree receipt for male students by six percentage points. In another study, taking advanced secondary mathematics coursework raises engineering degree receipt by nine percentage points for females. Along with these studies, our study suggests that policies that expand high school STEM offerings can increase degree receipt in related fields.

Finding #2: Effects on CS BA receipt and earnings are similar or larger for students who are historically underrepresented in the CS field.

CS, along with many other STEM fields, have historically been dominated by workers who are white or male, and recent policy efforts have been intended to make CS learning and career options more accessible for all . On receipt of bachelor’s degrees in CS, high school CS course-taking has similar and sometimes even larger effects for females, students from lower socioeconomic status (SES) backgrounds, and Black students relative to peer groups that have been better represented in CS fields historically. For example, taking a CS course raises receipt of CS bachelor’s degrees by seven percentage points for Black students, five percentage points for Hispanic students, and six percentages for white students, which are statistically indistinguishable from each other. The biggest difference comes from subgroup analysis by SES. The effect size is nearly eight percentage points for low SES students, while only two percentage points for their counterparts (though it is not statistically significant).

A striking difference across groups emerges when we look at earnings outcomes. In Figure 2, we plot the impact of CS course-taking in high school on earnings for different student demographic groups. The overall effect is also included for comparison. We find that high schools offering CS coursework increase earnings at age 24 by eight percentage points overall (see Figure 2 below). Even more, when we break these estimates out by different student subgroups, we find these earnings effects are driven by historically underrepresented subgroups, including females, those from low SES backgrounds, and Black students. Together, these findings suggest that exposing students to CS coursework in high school can be an effective approach for increasing the supply of CS degree recipients and professionals in the labor market, with enhanced earnings particularly for historically underrepresented groups.

Finding #3: Although positive long-run impacts of CS course exposure are stronger for historically underrepresented groups, CS course take-up rates are lower among these students.

Given the range of long-run benefits of taking a high school CS course, which student groups are most likely to take advantage of this opportunity? We find that high schools offering CS raises the chance of students taking a CS course by about six percentage points for all students, on average, as not all students end up enrolling in the class when offered. Specifically, CS course take-up increases by about 13 percentage points for Asian students, but only six percentage points for Black students and four percentage points for Hispanic students. The contrast is similarly stark for students at different achievement levels: Based on their prior math achievement, the top 25% of students have an increased CS course-taking rate almost three times higher than that of the bottom 25% of students. We also observe slightly lower CS course take-up rates for females and students from low SES backgrounds compared to their counterparts, but the differences are not statistically significant.

Overall, although underrepresented groups of students benefit from taking a CS course if they enroll, they may be less likely to take on this opportunity compared to their peers. Similar lower participation rates among under-represented groups are also observed in other states and nationally as well. For example, in California , female students are much less likely to take CS despite having similar access relative to male peers. National data also show that male students are more than twice as likely to take CS compared to females. Thus, it is critical to identify and remove the barriers underrepresented students face regarding CS course enrollment.

Rapid expansion of CS courses raises questions about the capacity of schools and teachers to fulfill new requirements.

The number of states requiring all high schools to offer CS coursework has increased from just four states in 2017 to 30 states in 2023. We can also expect more states to follow the existing eight states that have mandated CS courses as a requirement for high school graduation. As Maryland and many other states continue their efforts in expanding CS courses in K-12 schools, this fast growth also raises concerns about whether schools are prepared to implement new CS requirements. In particular, a major bottleneck is the shortages of qualified CS teachers, a challenge also faced by many other countries that try to expand CS education. This is not surprising, given that individuals with CS skills and qualifications often have other highly paid job alternatives.

The limited supply of CS teachers also has implications for the current CS teacher workforce. Our own analysis of Maryland data suggests that most high schools that offer CS courses only have one CS teacher, meaning that they do not have colleagues to do co-planning or to share the challenges they encounter in their CS classrooms. In addition, a large share of Maryland CS teachers teaches out of their certified fields without adequate preparation for the necessary skills needed to teach CS.

These staffing challenges require school systems to concentrate efforts to boost the supply of qualified CS teachers as well as provide support to existing CS teachers to ensure quality CS instruction. States may consider allocating funding to expand traditional and alternative pathways to CS teacher certification. Focusing on professional development that provides training on CS content and pedagogy for existing teachers who will be new to teaching CS may also offer the potential to promote impactful CS instruction.

Taken as a whole, our research offers reasons for optimism about the potential of “CS for All” policies, especially given the positive effects of CS course-taking on CS degree recipients and early-career earnings for underrepresented student groups. However, policymakers must also be mindful of the way course expansion policies are implemented and improve the supply of qualified CS teachers to ensure all students benefit from these opportunities.

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FHU announces new computer engineering program, launching Fall 2024

F reed-Hardeman University will offer a new computer engineering program in the fall of 2024, providing students with the opportunity to enter a first cohort for a Bachelor of Science in engineering with a concentration in computer engineering.

Students of this cohort will be among the first to take advantage of the new ATPI Center for Computer Science and Digital Innovation, coming in the fall of 2025. The Center is named in honor of Albert and Treva Brown and Philip and Irene Kopel, the parents of John and Rosemary Brown, whose donations made the Center a reality.

“As the demand for computer engineers continues to grow, we are pleased to be a part of meeting that demand,” FHU President David R. Shannon shared.

“We are excited about the director, professors, curriculum, and planned facility, which will set up students for a successful career. John and Rosemary Brown believe in Freed-Hardeman University and in this new engineering program and its success. John’s own success as an engineer led him to become one of the leading CEOs in America. The Browns’ support continues to be indispensable. At FHU, we continue to move forward for God's glory.”

The purpose of the computer engineering degree is to encourage and direct students toward opportunities in undergraduate research in fields such as robotics, artificial intelligence, and business analytics.

Additionally, students will be connected with businesses and organizations interested in hiring or providing internships.

The field of computer engineering has grown exponentially in recent years, and jobs are being continually created to fill related needs in the workforce. Such in-demand positions may include computer hardware engineers, data scientists, software developers, game developers, forensic computer analysts and hardware reverse engineers. 

While many other engineering programs are research-driven with classes often being taught by graduate teaching assistants, students in FHU’s program will be taught directly by the full-time computer engineering faculty. Additionally, graduates in computer engineering will be prepared to continue their education and research in qualified master’s and doctoral programs.

“We live in a world of exciting and important challenges, from our rapidly developing technologies to society’s questions of how best to use them,” Dr. Ben Clark, FHU director of computer science and digital innovation, said.

“To meet these opportunities head-on, Freed-Hardeman University will begin training engineers for a full bachelor’s degree starting in the fall of 2024. We are building this program with support from the generous donations of John and Rosemary Brown and others who see our vision for providing an undergraduate engineering education in a Christ-centered context. The next few years will bring many changes, both on our campus and throughout the world. This is our next step in providing students an education that integrates faith, scholarship, and service at every level of their university experience.”

The program is designed around the following objectives for student growth:

Faith: By using their unique talents in the practice of engineering for skillful stewardship of God's creation, encouraging professional interactions that are fair, ethical, and of the utmost integrity

Scholarship: By engaging in the practice of engineering and the continued adventure of learning in a rapidly advancing field

Service: Being involved in community, making their families, congregations, companies and cities better because these students are “fit for use.”

With the addition of the ATPI Center for Computer Science and Digital Innovation in the fall of 2025, students will have access to a new academic location on campus that is designed to focus on project-based learning. This state-of-the-art location will have new classrooms, engineering labs, faculty offices, a fully equipped Makerspace and spaces for student collaboration.

For FHU, the addition of this program is the first step in a plan to train engineers in the field of robotics in a Christ-centered context. Further engineering concentrations are planned for the future. 

“The offering of the first engineering degree is an important milestone in the University’s history and further diversifies our academic portfolio,” said Dr. C.J. Vires, FHU provost and vice president for academics.

“This program aligns with the workforce demands of West Tennessee and the Southeast region. This is a first step, and we will add additional concentrations for several more years. I’m very excited about the quality team of professors we’ve assembled to launch this program and the new forthcoming facility that will provide a showcase and new home for the program’s students and faculty.”  

The mission of Freed-Hardeman University is to help students develop their God-given talents for His glory by empowering them with an education that integrates Christian faith, scholarship, and service. With locations in Henderson and Memphis, FHU offers associate, bachelor’s, master’s, specialist, and doctoral degrees. More information is available at  fhu.edu .

This article originally appeared on Jackson Sun: FHU announces new computer engineering program, launching Fall 2024