Rensselaer Catalog 2019-2020
Electrical, Computer, and Systems Engineering
Department Head: Dr. John T. Wen
Curriculum Chair: Dr. James J.-Q. Lu
Undergraduate Program Director: Dr. Shayla M. Sawyer
Graduate Program Director: Dr. Alhussein A. Abouzeid
Department Home Page: https://www.ecse.rpi.edu/
Electrical Engineering at Rensselaer started in 1907, right at the dawn of the age of electricity. A century later, the curriculum has evolved with time, but the same philosophy of combining fundamental engineering principles with relevant contemporary applications remain. Electrical, computer, and systems engineers have always been at the forefront of new discoveries. The impact of electrical, computer, and systems engineers on society can be seen in areas as diverse as robots and artificial intelligence, communications and networking, medicine and medical technology, microelectronics and photonics, power systems, entertainment and gaming, and more. Inventions in these areas, such as integrated electronics and optical devices, stimulate innovations in computers, control, and communications. New systems theory and mathematical techniques are then developed for analysis and design.
As perhaps the broadest of scientific disciplines, Electrical, Computer, and Systems Engineering (ECSE) rests on a wide range of scientific fundamentals and therefore offers numerous advantages for undergraduate and graduate study. Among them is the ability to attack the many facets of modern problems of social relevance that cut across disciplinary lines. The flexibility for students to embark on individually tailored programs and for the department to launch new areas of research is a hallmark of ECSE.
The department offers Bachelors, Masters, and Doctoral degrees in Electrical Engineering (EE), and Computer, and Systems Engineering (CSE). ECSE curriculum builds a broad foundation in math, science, humanity and social science, and multiple disciplines in engineering, while allowing flexibility in electives to pursue specialized concentrations. ECSE students are trained in engineering fundamentals and application-specific domains with emphasis on hands-on education, design experience, and teamwork. ECSE faculty conducts cutting edge research across multiple disciplines and physical scales, including semiconductor design and processing, smart sensors and devices, 5G communication, and cyber-physical systems such as smart grid and collaborative robots. ECSE research is powered by federal funding agencies including NSF, NIH, DOE, DARPA, ONR, ARO, AFOSR, state funding agencies including NYSTAR and NYSERDA, private foundations, and industry partners.
Research Innovations and Initiatives
The following area descriptions capture activities in research and education across a set of fairly broad technical areas. Individual research groups reside within these broad curricular areas, overlap to sometimes significant degrees, and are highly dynamic and fluid in size and composition as new research initiatives and opportunities arise. These descriptions are therefore best taken as a snapshot of the Department’s research and curricular profile, and the lists of topics and areas are not necessarily exhaustive. Prospective graduate students are encouraged to visit the Department Home Page for faculty listings and Web pages, and to contact individual faculty with whom they may share technical interests to learn more.
Artificial Intelligence (AI) and Machine Learning (ML) Systems
Research in this area covers a range of technologies and applications and overlaps those in several research areas described below. The next industrial revolution will largely be driven by Intelligent Technologies (ITs). It will mark with the ubiquitous presence and applications of intelligent algorithms and systems, such as autonomous machines and smart devices. ECSE faculty has a long tradition in developing intelligent technologies. The research activities expand into fundamental advances in AI and machine learning, theory of learning, novel AI algorithms and architectures, and software engineering principles for AI systems (including topics in scalability, robustness, fairness, and verification). In addition to fundamental AI, applied research activities extend to, but are not limited to, applications of AI and ML in computer vision, image processing, cybersecurity, cyber-physical systems, Internet of Things (IoT) and edge-computing, autonomous systems, etc.
Communications, Information, and Signal Processing
Advanced study and research in this field deals with the encoding, transmission, retrieval, and interpretation of information in many forms. Students may pursue programs of study focusing on mathematical foundations, improved algorithms, and hardware/software implementation. Communications research focuses on the transmission of information over wireless, optical, and wired channels. Telecommunications engineering creates wired and wireless systems that satisfy desirable societal, bandwidth, and hardware constraints. Research in statistical communications aims at reducing adverse effects on signal transmission in such systems through probabilistic modeling. The channels considered range from subminiature networks inside a computer chip to broadband cable and communications satellites.
Information processing addresses the theory and engineering design associated with interpreting and manipulating received data, primarily in discrete form. Information theory and rate-distortion theory provide the foundation for a quantitative understanding of the nature and meaning of information. These theories treat the fundamental limits and algorithms for saving memory and bandwidth and protecting against transmission errors, such as in network coding.
Signal processing considers the application of digital processing techniques to problems encountered in many areas, including biomedical instrumentation, remote sensing, subsurface sensing and imaging systems, control systems, and audio processing. Special laboratories are available for speech processing, video and image processing, networking, communications, and document image analysis.
There is significant overlap and interaction with research activities in computer networking, image processing, geographic information sciences, and computer vision.
Computer Vision, Image Processing, Digital Media, and Computational Geometry
Research in this area covers a range of technologies and applications. Rensselaer has a number of specialized laboratories in which this work is undertaken. These include the Intelligent Systems Laboratory, the Distributed and Multidimensional Computer Vision Laboratory, the Computational Geometry Laboratory, the Rensselaer Augmented and Virtual Environment, the Center for Lighting Enabled Systems and Applications, and the Cognitive and Immersive Systems Laboratory.
Research areas include computer vision, image and video processing, artificial intelligence, computer graphics, machine learning, image reconstruction, pattern recognition, computational geometry, geographic information science and computational cartography, probabilistic reasoning and decision making under uncertainty, optical scanning systems, and Internet image analysis services.
Primary application areas include automatic target recognition, camera networks, medical image analysis, diffuse optical and optical coherence tomography, synthetic aperture imaging, distributed RF imaging, range data processing, document image analysis, systems biology, computer-assisted surgery, large geometric datasets, image and video processing for human viewers, image analysis aids to neurobiology, and multimodality imaging and analysis. Additional application areas include occupant-aware environments, activity monitoring and situational awareness, human computer interaction, eye and gaze tracking, bioinformatics, human fatigue monitoring, video imagery activity interpretation, robot localization, robotic devices for automated scoring of assays for the biotechnology industry, biotech assay automation, and biological multidimensional microscopy.
Work related to digital media includes such topics as camera networks and video analysis for large immersive environments, computer vision for visual effects production, image and video compression for networks, and methods for indexing video by content. Multimedia work also includes graphics courseware development for the World Wide Web using HTML, Java, PHP, my SQL, and VRML.
Computer Engineering, Hardware, Architecture, and Networks
The development of advanced computer systems and their interconnection to facilitate ubiquitous and pervasive computing capabilities is the primary focus of this group. Research topics related to the design, implementation, layout, and testing of hardware systems include the design and testing of digital and mixed-signal chips in CMOS and BiCMOS and the development of computer-aided design tools for such designs. Specific topics include the development of high-speed computer chips using SiGe BiCMOS technology, the design and testing of mixed-signal chips for communications applications, the influence of three-dimensional (3D) integration/packaging on computer design, and the development of techniques for the design and reliable operation of digital chips fabricated in deep submicron CMOS.
Other ongoing research activities include error correcting coding system design and VLSI implementation for magnetic and holographic storage, and fiber and wireless communication; algorithm/architecture co-design for wireless multi-antenna signal processing; fault tolerance for semiconductor memories and molecular nanoelectronic memory; signal processing algorithm/architecture co-design for defect/variation tolerance in end-of-the-roadmap CMOS and post-silicon nanoelectronics regimes; silicon-based radio-frequency power amplifiers; multi-Gb/s broadband communications circuits; wafer-level 3D integration for millimeter-wave smart antenna transceivers; RF-powered wireless communication circuits for bio-implantable microsystems; devices, circuits, systems, algorithms, and methodologies to enable intelligent yet inexpensive portable platforms for environmental and biomedical diagnostics; detection and quantification of low levels of biological signals reliably, conveniently, safely, and quickly.
The computer networking research group works on the development of protocols and architectures for both wired and wireless networks and their modeling for performance evaluation. Emerging technologies for wireless and optical last mile access, wireless sensors networks, network management, traffic management, congestion control, traffic engineering, and quality-of-service (QoS) architectures form the basic areas of current research. The networking group also participates in interdisciplinary research in control theory, economics, scalable simulation technologies, video compression, cyber-physical systems, Internet of Things (IoT) and edge-computing, autonomous systems, etc.
Control, Robotics, and Automation
With focuses on the methodologies and applications in control, robotics, and automation the ECSE faculty in this area conduct cutting-edge research with emphasis on high impact applications. The methodological tools used in this research area include complex large-scale systems, network science, formal methods, machine learning, vision and perception, and cognitive engineering. The domain of applications includes human-robot systems, advanced manufacturing, cyber-physical systems, autonomous systems, power systems, thermal management, biological systems, human health, micro-robotics, and materials processing.
Current research projects in this area address both control theory and a variety of applications. Faculty interests include advanced control algorithms development in the areas of nonlinear control, formal methods in control, multivariable control, robust control, distributed control, and optimal control. These algorithms are applied to robotics, automation systems, autonomous systems, power generation and transmission systems, power electronics, networked systems, micro and nano-systems, and biomedical and biological systems.
Research in robotics and automation is inherently interdisciplinary. ECSE faculty in this area coordinates closely with the Mechanical, Aerospace, and Nuclear Engineering; Computer Science; and Cognitive Science departments for joint research and curriculum development. Current projects include planning and control for advanced manufacturing systems, multi-robot actuator and sensor networks for coordinated monitoring and manipulation, and precision motion and force control with vision guidance in micro and nano assembly manufacturing and distributed robotics for environmental observation and monitoring. Extensive experimental and computational facilities, as well as undergraduate and graduate research opportunities, are available in the New York State Center for Automation and Technology Systems.
Power Electronics and Power Engineering Systems
Research in power electronics and power engineering systems is becoming critically important to meet the world’s increasing energy needs and demands within the environmental, economic, and national security constraints today. Department faculty are conducting active research programs and projects in power system analysis and optimization, power electronics for application in renewable energy, energy efficiency and transportation electrification, energy harvesting for sensors, photovoltaic devices and systems, semiconductor power devices.
In the power system area, ongoing research includes dispatch and control of voltage-sourced converter based flexible AC transmission systems, in conjunction with the operations of actual hardware installations in power transmission companies. A new area of research is the application of high-sampling rate synchronized phasor data to improve the operation of large power grids. The research covers phasor data streaming and database management, off-line disturbance event analysis, real-time applications in visualization and state estimation, as well as data recovery and cybersecurity. Another new research area is stability and control of high-voltage dc (HVDC) converters and systems for long-distance transmission of renewable energy, including offshore wind. New research directions also include multi-terminal HVDC as well as stability and control of future power systems dominated by renewable sources.
Optimization theory and advanced computational tools are used in the design of electric power systems to obtain high efficiency and reliability at minimum cost, particularly for systems that involve distributed generation. This has been extended to include the development of control and energy management system (EMS) for renewable energy, energy storage and microgrids, as well as intelligent protective relaying for dealing with the problem of islanding and utilizes the Department’s real-time and hardware-in-the-loop (HIL) simulation tools.
Power electronics and electromagnetics provide the foundation for the utilization and integration of renewable energy resources, and enables energy-efficient technologies such as solid-state lighting, variable-speed motor drives for advanced manufacturing and appliances, as well as electrified transportation systems. Current interests and research activities include smart power semiconductor (Si, GaAs, SiC, GaN and diamond) devices and ICs; power converter design for IT, lighting and other electronics applications; autonomous and mobile power systems; as well as energy harvesting systems enabled by power electronics. A new research focus is power electronics for renewable energy and energy storage, including the development of new converters and system architectures for large-scale PV and wind energy, modeling of wind turbines and PV inverters for power system stability studies, and the application of wide bandgap power semiconductors in these systems.
The current roadmap for photovoltaic (PV) device and system technology is based on few well established concepts from decades ago. Though theoretical predictions show that one could achieve very high efficiencies in solar to electricity conversion, breakthroughs are required in the device designs and system architectures to enable cheaper materials and manufacturing processes that can deliver the ultra-high efficiency energy converters. Mere industrial scale-up of processes is not enough for reducing the per-watt cost to make PV a sustainable mainstream energy supply source. The scope of our research activities in this area include: design and fabrication of full solar spectrum PV systems with III-V compound semiconductor devices, integrated power switching devices, non-imaging optical solar concentrator systems and nano-rod based passive optical elements, with emerging technology and innovations.
In the power semiconductor devices area, research in both discrete and integrable transistors, as well as power integrated circuits, on silicon and compound semiconductors are actively pursued. Compound semiconductors explored include conventional (GaAs), wide bandgap (SiC and GaN) and ultra-wide or extreme bandgap (diamond and AlN) semiconductors. Novel device structures examined and/or demonstrated are bi-directional Si and SiC IGBTs, and, GaN and diamond MOS Channel-Heterojunction Field-Effect Transistors. In addition, physics–based, analytical and macro-elements-based device models are developed so as to allow performance evaluation and impact on energy efficient, power electronics systems. Further, recent experimental demonstrations of monolithic integration of power devices with photonic devices in GaN are particularly noteworthy.
Electronic and Photonic Devices and Systems
The discovery of new devices and improvement of existing ones led to the modern electronic industry. These new devices are the basic building blocks of any new systems that positively impact daily life. Many department faculty work on developing such new devices using cutting edge technology and then employ them in building state of the art systems. State of the art laboratory facilities exist to carry out advanced study and research in these areas.
A common user facility accessible to all students and faculty is the Microscale and Nanoscale Fabrication Cleanroom (MNCR) housed in the Center for Materials, Devices, and Integrated Systems (cMDIS). This MNCR is equipped with up to 8” wafer tools for end-to-end device fabrication, characterization, metrology, and testing of silicon-based devices and integrated circuits, and an array of equipments for compound semiconductor device processing. In addition, the nanolithography tools, such as nanoimprint, nano ink, and direct e-beam writer, enable micro-nano-electronic and photonic device fabrication at feature size of 10 nm. This MNCR is being used extensively for research in many areas, including the discovery and invention of new electrical, optical, and thermal interconnect solutions, hyper-integration of heterogeneous components for future terascale systems in AI, Internet of Things, and bio-medical devices and systems.
One of the new projects involves investigation of a new regime of transistor operation in the terahertz range using the excitation and rectification of plasma waves in the transistor channel. This work is supported by modeling and parameter extraction based on our circuit simulator, AIM-Spice (with tens of thousands of users worldwide) and by materials and device research on multifunctional semiconductors having pyroelectric properties. A variety of commercial design and simulation software, presently including Cadence, Mentor, TMA, and Hewlett-Packard software suites, are available for modeling integrated circuits, devices, processes, and interconnects that enable the discovery of new devices.
Several specialized laboratories are available that are equipped to meet industrial standards for advanced research techniques. The electronic materials laboratory includes several state-of-the-art bulk crystal growth systems, wafer slicing and chemical-mechanical polishing facilities, liquid phase epitaxy system for multilayer hetero-epitaxial growth, and cold wall epitaxial reactors for the growth of single crystal III-V, II-VI semiconductors. This equipment is used to grow and fabricate infrared devices, thermophotovoltaic devices, and advanced solar cells. The high-voltage power device laboratory, as part of the Center for Power Electronics Systems (CPES), is used in designing and fabricating high-voltage and high-power semiconductor devices. Equipment to characterize these devices in wafer and package form up to 20 kV and 25A is available.
The Center for Lighting Enabled Systems and Applications (LESA), started in 2008 as the NSF funded Smart Lighting Engineering Research Center (ERC), continues to expand its research horizons through the integration of digitized, color tunable lighting, advanced sensing and control platforms, and machine learning tools to enable “Systems that Think™.” LESA exploits the power of digitized, spectrally controllable illumination across a wide range of cyberphysical applications, including dynamic control of lighting spectral content for improved human health and well-being, privacy preserving occupant counting and position sensing/tracking for improving building energy efficiency, light communications for high bandwidth, wireless data connectivity through lighting, and closed loop control of plant growth in controlled environment agriculture (e.g. vertical farming) where lighting spectrum is dynamically adjusted to improve energy efficiency and nutritional value of plants.
The technology platforms being developed at LESA are highly interdisciplinary, playing an increasingly important role in the development of energy efficient Smart Buildings and Smart Cities programs that interface to research programs in improved healthcare, sustainable architecture, and smart grid management, while developing new sensor platforms needed to balance smart connectivity with individual privacy concerns.
In many cases, novel solutions to system level problems require attention to advances in new electronic devices and materials. LESA’s materials research includes the development of advanced, refractive index engineered optical systems for improved lighting energy efficiency. LESA’s semiconductor device research includes novel approaches to monolithic optoelectronic integration of LEDs and electronics for future display applications, and high-speed optical receiver ICs for emerging light communications (LiFi) that will soon become part of advanced 5G wireless communications platforms.
Facilities for conducting LESA’s research include the 5,000 square foot LESA Central Laboratories, located in RPI’s George Low building, which include an advanced “smart conference room” for exploring new sensing technologies for improving human well-being and creating more energy efficient building systems. There is also a controlled environment plant growth testbed for integrating optical, chemical, and acoustical sensing methods with lighting spectral properties for improving plant growth efficiency. For research on lighting applications in healthcare, LESA collaborates with the University of New Mexico (LESA lighting and sensing facilities installed in an operational hospital room) and Thomas Jefferson University (LESA systems installed in a neurological ICU). LESA also maintains light testing facilities for evaluating the optical behavior of materials, including the performance of new LED lighting systems.
Semiconductor and photonic devices are the building blocks of many systems; many faculty do research in the design, implementation, layout, and testing of hardware systems. Research areas include the design and testing of digital and mixed-signal chips in CMOS and BiCMOS and the development of computer-aided design tools for such designs. Specific topics include the development of high-speed computer chips using SiGe BiCMOS technology, the design and testing of mixed signal chips for communications applications, the influence of wafer-to-wafer bonded 3D integration on computer design, and the development of techniques for the design and reliable operation of digital chips fabricated in deep submicron CMOS.
Recent faculty activities in this area include error correcting coding system design and VLSI implementation for magnetic and holographic storage, and fiber and wireless communication; algorithm/architecture co-design for wireless multi-antenna signal processing; fault tolerance for semiconductor memories and molecular nanoelectronic memory; signal processing algorithm/architecture co-design for defect/variation tolerance in end-of-the-roadmap CMOS and exploration of possible post-silicon technology including SiGe, GaAs/GaInAs, InP, GaN, (both FET and HBT) and nanoelectroics; silicon-based radio-frequency power amplifiers; multi-Gb/s broadband communication circuits; millimeter-wave smart antenna transceivers; RF-powered wireless communication circuits for bio-implantable microsystems; devices, circuits, systems, algorithms, and methodologies to enable inexpensive portable platforms for environmental and biomedical diagnostics.
Abouzeid, A.A.—Ph.D. (University of Washington); packet networks.
Bhat, I.—Ph.D. (Rensselaer Polytechnic Institute); sold state, electronic materials.
Chow, J.H.—P.E., Ph.D. (University of Illinois); large-scale system modeling, multivariable control systems.
Chow, T.P.—Ph.D. (Rensselaer Polytechnic Institute); semiconductor power devices and integrated circuits, device physics and processing technologies, monolithic integration.
Dutta, P.S.—Ph.D. (Indian Institute of Science); compound semiconductor materials and devices, crystal growth and substrate engineering, semiconductor quantum dots and nano-particles, photovoltaics, optoelectronics and microelectronics technologies.
Franklin, W.R.—Ph.D. (Harvard University); computational geometry, graphics and CAD applications, large geometric databases, geographic information systems, terrain visibility and compression, parallel computing on GPUs.
Hella, M.—Ph.D. (Ohio State University); RF and mixed signal VLSI circuits for wireless/optical transceivers; analog/RFIC design for biomedical applications.
Ji, Q.—Ph.D. (University of Washington); computer vision, image processing, pattern recognition, robotics.
Kar, K.—Ph.D. (University of Maryland); computer networks, wireless and sensor networks, Internet-of-Things, smart grid.
Karlicek, R.F.—Ph.D. (University of Pittsburgh); compound semiconductor materials and devices, device packaging, lasers and light emitting diodes, solid state lighting.
Lu, J.-Q.—Ph.D. (Technical University of Munich); electronic materials, devices, frabrication, integration and packaging; 3D integrated system technology; 3D-IC and 3D packaging; LED display technology.
McDonald, J.F.—Ph.D. (Yale University); communication theory, coding and switching theory, computer architecture, integrated circuit design, high frequency packaging, digital signal processing.
Radke, R.J.—Ph.D. (Princeton University); image and video processing.
Schubert, E.F.—Ph.D. (University of Stuttgart); compound semiconductor devices and materials, light emitting diodes, heterobipolar transistors, semiconductor device physics, solid state lighting.
Shur, M.S.—D.Sc. (Ioffe Institute); semiconductor materials and devices, integrated circuit simulation, characterization, and design.
Sun, J.—Ph.D. (University of Paderborn); power electronics and its application in renewable energy, IT, transportation, and power systems.
Wen, J.T.—Ph.D. (Rensselaer Polytechnic Institute); modeling and control of dynamical systems with applications to robot manipulation, materials processing, and thermal management.
Yazici, B.—Ph.D. (Purdue University); inverse problems in biomedical imaging, tomography, diffuse optical tomography, biomedical optics, free space optical communications, ultrasonics, statistical pattern recognition theory and application.
Zhang, T.—Ph.D. (University of Minnesota); VLSI signal processing, error-correcting coding.
Julius, A.A.—Ph.D. (University of Twente); mathematical systems theory and control, systems biology, control of biological systems, hybrid systems.
Huang, Z.R.—Ph.D. (Georgia Institute of Technology); optoelectronic devices, integration and packaging, 3D integrated microsystems, lightwave circuits, integrated slow wave structures, photodetectors, electro-optic modulators, and laser diodes.
LeCoz, Y.L.—Ph.D. (Massachusetts Institute of Technology); numerical methods, random-walk algorithms for thermal and electromagnetic analysis of IC interconnects, quantum theory of semiconductor heterojunctions.
Sawyer, S.M.—Ph.D. (Rensselaer Polytechnic Institute); optoelectronics, characterization, design, sensor development.
Schoch, P.M.—Ph.D. (Rensselaer Polytechnic Institute); plasma diagnostics, instrumentation, engineering education.
Tajer, A.—Ph.D. (Columbia University); information theory, wireless communication, statistical signal processing, smart grids.
Vanfretti L. —Ph.D. (Rensselaer Polytechnic Institute); synchrophasor and electrical energy technology and applications; cyber-physical power system modeling, simulation, stability and control.
Wang, M.—Ph.D. (Cornell University); machine learning, high-dimensional data analytics, power systems, signal processing.
Chen, T.—Ph.D. (University of Minnesota); machine learning and resource allocation for Internet-of-Things and cyber-physical systems, network communication and machine learning co-design.
Malak, D.—Ph.D. (University of Texas at Austin); communication theory and networks, stochastic modeling of content caching and computation, network resource utilization and performance optimization.
Professors of Practice
Kanai, J.—Ph.D. (Rensselaer Polytechnic Institute); engineering education, software engineering, systems engineering.
Shah, M.—Ph.D. (Virginia Polytechnic Institute and State University); electric machines design and analysis, machine system interaction, low frequency electromagnetics.
Braunstein, J.—Ph.D. (Rensselaer Polytechnic Institute); microwave heating, antenna theory, and numerical computing.
Gela G.—Ph.D. (University of Toronto); electric power AC and DC transmission and distribution; high voltage equipment and phenomena; electric power system operation, maintenance, and safety; renewables.
Hameed, M. A.—Ph.D. (University of Kansas); fiber optic telecommunications, digital signal processing, analog and digital circuit design.
Khoukhi, A.—Ph.D. (University of Montreal); robotics, control, computational intelligence, and mechatronics.
Kraft, R.P.—Ph.D. (Rensselaer Polytechnic Institute); embedded systems and control education, electronic manufacturing inspection, high-speed digital circuits.
Wilt, K. R.—Ph.D. (Rensselaer Polytechnic Institute); acoustic and ultrasonic wave theory, piezoelectric transducer theory and design, embedded systems.
Close, C.M.—Ph.D. (Rensselaer Polytechnic Institute); network analysis and synthesis, control systems.
Connor, K.A.—Ph.D. (Polytechnic Institute of New York); plasma diagnostics, instrumentation, engineering education.
Das, P.K.—Ph.D. (University of Calcutta); microwave acoustics, solid-state devices, integrated circuits.
Desrochers, A.A.—Ph.D. (Purdue University); discrete event dynamic systems, robotics, automated manufacturing systems control.
DiCesare, F.—Ph.D. (Carnegie Mellon University); discrete event systems, Petri net theory and applications manufacturing automation and integration, traffic control.
Frederick, D.K.—Ph.D. (Stanford University); automatic control, process modeling and control, computer simulation.
Gutmann, R.J.—Ph.D. (Rensselaer Polytechnic Institute); solid-state devices, microwave techniques, and interconnection technology.
Jennings, W.C.—Ph.D. (Rensselaer Polytechnic Institute); plasma diagnostics, electronics manufacturing, multimedia educational materials.
Kelley, R.B.—Ph.D. (University of California, Los Angeles); methods to give machines smart behaviors, sensor-based automation/robotic systems, teaching methods.
Nagy, G.—Ph.D. (Cornell University); pattern recognition, document-image analysis, optical character recognition, geometric computation, computer-mediated learning, computer vision.
Nelson, J.K.—C.Eng., Ph.D. (University of London); dielectrics and insulation systems, computer-based diagnostics, electrostatic phenomena.
Pearlman, W.A.—Ph.D. (Stanford University); information theory and source coding; image, video, and audio compression; digital image and signal processing.
Rose, K.—Ph.D. (University of Illinois); semiconductor and superconductor materials and processing, VLSI design and testing.
Salon, S.J.—P.E., Ph.D. (University of Pittsburgh); machine design, system component modeling and simulation.
Sanderson, A.C.—Ph.D. (Carnegie Mellon University); robotics, knowledge-based systems, computer vision.
Savic, M.—Eng.Sc.D. (University of Belgrade); signal processing, biomedical electronics, electronics.
Saxena, A.N.—Ph.D. (Stanford University); solid-state materials, devices, integrated circuits, and advanced technologies.
Woods, J.W.—Ph.D. (Massachusetts Institute of Technology); digital signal processing, image processing, digital image and video compression.
* Departmental faculty listings are accurate as of the date generated for inclusion in this catalog. For the most up-to-date listing of faculty positions, including end-of-year promotions, please refer to the Faculty Roster section of this catalog, which is current as of the May 2019 Board of Trustees meeting.
Outcomes of the Undergraduate Curriculum
Students who successfully complete this program will be able to demonstrate:
- an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
- an ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
- an ability to communicate effectively with a range of audiences.
- an ability to recognize ethical and professional responsibilities in engineering situations and make informed judgments, which must consider the impact of engineering solutions in global, economic, environmental, and societal contexts.
- an ability to function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives.
- an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
- an ability to acquire and apply new knowledge as needed, using appropriate learning strategies.
Objectives of the Undergraduate Curricula
The Electrical and Computer and Systems Engineering programs are each designed to prepare students for continued learning and successful careers in industry, government, academia, and consulting. Within a few years of graduation graduates of the Bachelor of Science programs are expected to:
- pursue professional positions and/or graduate study in their areas of interest.
- contribute to the body of knowledge in their professional disciplines through problem-solving, discovery, leadership, and responsible application of technology.
- continue to develop both professionally and personally through activities such as participation in professional societies, continuing education, and community service.
The Electrical Engineering and Computer and Systems Engineering degree programs are each independently accredited by the Engineering Accreditation Commission of ABET, http://www.abet.org.
Within the department, students may obtain the Bachelor of Science degree in either of two disciplines: electrical engineering or computer and systems engineering. The department also encourages students to consider graduate study in either of these curricula.
Engineering design is introduced and developed throughout the program, setting the stage for a capstone design experience. The capstone design experience is a communications-intensive course and satisfies the Institute writing requirements as it prepares the student for a professional career.
Starting templates are available for students who select either of the ECSE disciplines. However, various arrangements can be made with the help of an adviser. In all cases, adviser approval of individual plans of study is necessary to ensure satisfaction of departmental and accreditation requirements. The adviser must also approve in writing any exceptions to the courses specified in the descriptions below.
The electrical engineering curriculum requires completion of a minimum of 128 credit hours; the computer and systems engineering curriculum requires 129 credit hours. In either case, the Pass/No Credit option may be used only for humanities and social sciences electives (up to a maximum of 6 credits) or free electives. All other courses used to satisfy the degree requirements must be taken on a graded basis.
Dual Major Programs
Dual majors lead to a single baccalaureate degree embracing two fields. Special programs which can be completed in eight semesters have been developed. Examples include dual majors in Electrical Engineering and Computer and Systems Engineering, Computer and Systems Engineering and Computer Science, Electrical Engineering and Mechanical Engineering, Electrical Engineering and Applied Physics, and others.
See the ECSE homepage for detailed/updated information about these programs. Further information is also available in the ECSE Student Services office.
Special Undergraduate Opportunities
The Grainger Scholar Program
This program is for well-qualified U.S. students whose individual studies emphasize energy sources and systems. The Grainger Scholars Award is given annually in the amount of $7,500 for junior undergraduates who are entering their senior year and $10,000 for current co-terminal students or students entering the department’s Master’s or Ph.D. programs. Eligible students must have a concentration in energy sources and systems, especially electric power.
The department offers graduate programs leading to the Master of Engineering, Master of Science, and Doctor of Philosophy in both of the department curricula. In all cases, particular emphasis is placed on developing a coherent individualized Plan of Study with the help of a faculty adviser. See more details at ECSE department homepage.
Both the M.S. and the M.Eng. require 30 credits beyond the bachelor’s degree. See more details here about the Master’s Program at ECSE homepage.
Advanced study and research for a Ph.D. degree is conducted under the guidance of a thesis adviser representing the department. The student formulates an individual Plan of Study in consultation with the adviser. Major milestones for the Ph.D. program in ECSE include passing a doctoral qualifying exam (DQE), a doctoral candidacy exam (DCE), and successfully defending the dissertation in an open presentation to his or her committee. The doctoral qualifying examination should be taken during the first year of the doctoral program. The doctoral degree requirements include 72 credits for students entering the graduate program with a bachelor’s degree or 48 credits for students entering with a master’s degree. The ratio of 6000-level to 4000-level credits on 72-credit Plan of Study must be 2 or greater with maximum of 15 credits at 4000-level. The doctoral dissertation credits accounted for time spent on research are 12 credits minimum and 36 credits maximum. The Ph.D. dissertation must be scholarly, creative, and original. The department expects the Institute requirements for candidacy and residency to be satisfied.
Outcomes of the ECSE Graduate Curriculum
Students who successfully complete this program will be able to:
- develop and demonstrate substantial breadth and depth of knowledge beyond the bachelor’s degree with a focus on one area of ECSE. [Coursework and DQE.]
- demonstrate an expertise in the student’s thesis area that covers both the background and current research in that area. [DCE and defense.]
- create substantial original knowledge in an advanced area of ECSE. [DCE, defense, and thesis.]
- clearly and thoroughly document both the state of the art and the student’s own research in the form of a dissertation. [Candidacy proposal and thesis.]
Special Graduate Opportunities
In collaboration with the various campus centers and other departments, ECSE sponsors master’s and doctoral program options in manufacturing systems and semiconductor technology. Descriptions of these programs are available upon request.
Courses directly related to all Electrical, Computer, and Systems Engineering curricula are described in the Course Description section of this catalog under the department codes CSCI, ECSE, ENVE, ISYE, ITEC, MATH, MATP, MTLE, and PHYS.