Strategic Research Areas
Research in Electrical and Computer Engineering covers an extremely broad range of topics. Whether in computer architecture, energy and power systems or in nanotechnology devices, the research conducted in ECE is at the cutting edge of technological and scientific developments.
Cornell ECE research is categorized into five strategic areas.
Computer Engineering
Computer engineering concerns itself with the understanding and design of hardware needed to carry out computation, as well as the hardware-software interface. It is sometimes said that computer engineering is the nexus that connects electrical engineering and computer science. Research and teaching areas with a significant computer engineering component include digital logic and VLSI design, computer architecture and organization, embedded systems and Internet of things, virtualization and operating systems, code generation and optimization, computer networks and data centers, electronic design automation, or robotics.
Related Research Areas
- Algorithms
- Artificial Intelligence
- Complex Systems, Network Science and Computation
- Computer Architecture
- Computer Systems
- Data Mining
- Energy and the Environment
- Rapid Prototyping
- Robotics and Autonomy
- Scientific Computing
- Security
- Sensors and Actuators
- Signal and Image Processing
- Statistics and Machine Learning
Foundations of Information, Networks and Decision Systems
The Foundations of Information, Networks, and Decision Systems (FIND) is a research group in the School of Electrical and Computer Engineering (ECE) at Cornell University. The FIND group is committed to the advancement of research and education in the information, learning, network, and decision sciences. FIND research is at the frontier of a wide range of fields and applications including machine learning and signal processing, optimization and control theory, information theory and coding, power systems and electricity markets, network science, and game theory. Members of the FIND community are bound together by a common drive to develop the mathematical underpinnings and tools needed to address some of the most pressing challenges facing society today in energy and climate change, transportation, social networks, and human health.
Related Research Areas
- Artificial Intelligence
- Biotechnology
- Complex Systems, Network Science and Computation
- Computational Systems Biology
- Control and Dynamical Systems Theory
- Energy Systems
- Energy and the Environment
- Game Theory
- Image Analysis
- Information Theory and Communications
- Optimization Theory
- Power Systems and Electricity Markets
- Remote Sensing
- Scientific Computing
- Security
- Signal and Image Processing
- Statistics and Machine Learning
- Systems and Networking
High Energy Density Plasma Physics, Electromagnetics
Electromagnetics involves a variety of applications of electromagnetic wave propagation and other time-varying phenomena in the presence of electric and magnetic fields. Plasma science involves the interaction of large numbers of charged particles with electric and magnetic fields in a variety of configurations ranging from the surface of the sun to the interior of fluorescent electric light bulbs.
At Cornell, we specialize in High Energy Density Laboratory Plasma (HEDLP) research, in which the product of the density of the ionized matter (plasma) and its temperature (more than a million degrees C) that it exceeds the ability to of any material to confine it even for a tiny fraction of a second. An example of a high energy density plasma is the center of the sun, where the plasma is 15 million degrees kelvin, the density is 1000 times the density of normal matter on earth, and gravity is the confinement method. In our laboratories, we use pulsed power generators to produce very large currents (300,000-1,000,000 amperes) to produce hot plasmas; we use the high magnetic fields produced by the currents to confine the plasmas far away from material walls. This enables us to study the properties of 1- to 25 million degree high density plasmas for up to 0.1 microseconds using many different measurement techniques. Applications of our experimental, theoretical and computer simulation results include possible approaches to fusion reactors and understanding high energy astronomical observations.
Related Research Areas
Solid State, Electronics, Optoelectronics, MEMs
Solid State Devices, Integrated Circuits, Optical Devices and MEMs (microelectromechanical systems) have generated a monumental change in high performance electronics over the past several decades, enabling complex computer chips, optical communication, integrated sensors, transducers and systems that can be miniaturized to the point of being implanted and/or seamlessly connected to the environment.
At Cornell ECE, we work on diverse topics aimed at transforming the way we view the world. Our interdisciplinary research reveals fundamental similarities across problems and prompts new research into some of the most exciting and cutting-edge developments in the field. These areas include all aspects of communications, sensing, power regulation, and computing related to solid state and optical devices, circuits and MEMs.
Related Research Areas
Bio-Electrical Engineering
Biological and Biomedical Electrical Engineering (B2E2) consists of both applied and fundamental work to understand the complexity of biological systems at different scales, e.g., from a single neuronal or cancer cell, all the way to the brain or malignant tumor. B2E2 aims to develop new hardware and computational tools to identify, characterize, and treat diseases. In the physical domain, electrical engineering approaches to integrated microsystems lead to new biological and medical sensors. These sensors consist of state-of-the-art ultrasonic, RF, optical, MRI, CT, electrical impedance transducers.
The integration of sensors, electronics are used to develop implantable and wearable devices, with decreasing size, weight, and power and increased functionality. B2E2 microsystems can help create interfaces for sensing and actuation to help understand the physiological and pathological mechanisms of diseases, and enable advanced robotic interfaces in medicine. Medical devices can generate vast amounts of data, which require both real-time and post-acquisition processing. B2E2 faculty, sometimes in collaboration with medical researchers, develop advanced computational tools to learn from and exploit data and apply artificial intelligence approaches to impact medical practice by improving: early disease detection, disease diagnosis, response to therapy assessment, and guided surgical procedures.
Related Research Areas
- Algorithms
- Biomedical Imaging and Instrumentation
- Biotechnology
- Complex Systems, Network Science and Technology
- Computer-Aided Diagnosis
- Image Analysis
- Microfluidics and Microsystems
- Nanobio Applications
- Nanotechnology
- Neuroscience
- Remote Sensing
- Scientific Computing
- Sensors and Actuators
- Signal and Image Processing
- Statistics and Machine Learning
Hardware That Protects Against Software Attacks
ECE's Ed Suh and Zhiru Zhang and CS's Andrew C. Myers aim to develop both hardware architecture and design tools to provide comprehensive and provable security assurance for future computing systems against software-level attacks that exploit seven common vulnerability classes.
Image credit Beatrice Jin
Re-architecting Next-Gen Computing Systems
Disaggregated architectures have the potential to increase resource capacity by 10 to 100 times server-centric architectures.
Image credit Beatrice Jin
Re-imagining Computer System Memories
Interdisciplinary team will provide new insights and an entirely new paradigm for the semiconductor industry in the emerging era of big data.
Image credit Beatrice Jin
Engineers to hack 50-year-old computing problem with new center
Cornell engineers are part of a national effort to reinvent computing by developing new solutions to the “von Neumann bottleneck,” a feature-turned-problem that is almost as old as the modern computer itself.
The Laboratory of Plasma Studies: Uncovering mysteries of high energy density plasma physics
In the basement of Grumman Hall, an x-ray pulse produced by a hot, dense plasma – an ionized gas – lasting only fractions of a microsecond both begins and ends an experiment. Hidden within that fraction of time lies a piece of a puzzle—data that graduate students and staff scientists at the Laboratory of Plasma Studies (LPS) will use to better understand the mysterious physics behind inertial confinement fusion.
Sophia Rocco: Hoping to make the world a better place through a potential renewable energy source
When she was looking at graduate schools, physics major Sophia Rocco thought she would be in a materials science program bridging her interests in electricity and magnetism and novel materials for solar cells. Chancing upon the School of Electrical and Computer Engineering at Cornell, she discovered the Laboratory of Plasma Studies (LPS).
Finding the Ultimate Energy Source: Cornell’s Lab of Plasma Studies
Plasma is one of the four fundamental states of matter, but it does not exist freely on the Earth’s surface. It must be artificially generated by heating or subjecting a neutral gas to a strong electromagnetic field. Located in the basement of Grumman Hall are two large pulse-power generators that create plasma by delivering extremely high currents to ordinary matter for short periods. These generators are part of the Lab of Plasma Studies at Cornell University.
Photo credit: Dave Burbank
Vertical gallium oxide transistor high in power, efficiency
The research group led by Grace Xing and Debdeep Jena presented research on a new gallium oxide field-effect transistor at a conference at the Massachusetts Institute of Technology May 29-June 1.
Molnar, Jena and Xing join national consortium to develop future cellular infrastructure
Three Cornell faculty will be part of the newly established $27.5 million ComSenTer, a center for converged terahertz communications and sensing.
Data on the Brain
The NSF has found a willing partner at Cornell University in this quest to create technologies that will allow researchers to image the brain and the nervous system.