Electrical and Computer Engineering Research Labs
Research labs supported by a variety of government and industry sponsors provide faculty, students and post-docs with outstanding opportunities for research, development, and technical innovation.
The CNL Lab, under director Bijan Jabbari, focuses on communication networks and systems, with an emphasis on theory, architecture, modeling, performance analysis, mutli-access, mobility, routing and switching, teletraffic, and protocols
Current areas of research include:
- Routing and path computation in optical networks.
- Optimal resource allocation in wireless networks.
- High-performance computer networks and applications.
The Computer Architecture, Machine Learning, and Security (CAMLsec) Lab, under director Khaled N. Khasawneh, conducts research on machine learning for security, machine learning security & privacy, microarchitecture security, and hardware support for security. Current research topics include:
- Adversarial machine learning
- Privacy-preserving machine learning
- Malware detection
- Side channel attacks
- Transient execution attacks
- IoT security
- High-performance implementations to ultra-low power implementations of public key and secret key algorithms.
- Fault-tolerant implementations.
- Attack-resistant implementation.
- Implementations of attacks.
This lab, under director Peter Pachowicz, focuses on hands-on engineering of ultra-small CubeSats and satellite communications systems by combining research and educational objectives. Lab facilities include:
- CubeSat Development and Testing Lab.
- SatCom Ground Station (VHF/UHF/S-band antenna system).
- Space Communication Station (9.1m dish).
Most hardware and software is designed and built though multiple undergraduate, graduate, and student club projects. Researchers' work covers a broad spectrum of topics such as:
- Development of ultra-small CubeSats.
- Resilient satellite bus architectures.
- Hybrid power systems.
- Rad-hard embedded software.
- Low-noise antennas, signal and data fusion.
- Custom software defined radios.
Researchers in the HArt lab, under director Sai Manoj Pudukotai Dinakarrao, study computer architecture security using machine learning to create, detect, and defend emerging security threats on computing systems, including side-channel attacks and malware threats in stand-alone and connected IoT devices.
They are also investigating:
- In-memory computing for deep learning architectures.
- Accelerator design for machine learning applications.
- Architecting advanced adversarial threats and defenses for convolutional neural networks.
- Graph neural networks.
- Deep neural networks.
- Deep learning application and acceleration.
- Distributed mobile computing.
- Machine learning security.
- Mobile display.
- VR/AR technologies.
The NAPL Lab, under director Brian L. Mark, conducts research on the design, architecture, and performance of communication networks, encompassing wireline, wireless, and heterogeneous networks. Research covers all aspects of network architecture, from the physical layer to the application layer, which includes:
- Development of theoretical results.
- Algorithm design.
- Numerical computation.
- Computer simulation.
- Hardware and/or software development.
The Ocean Acoustic Signal Processing Group, which is a team of graduate students led by Professor Kathleen Wage, works on multi-disciplinary problems that require a synthesis of array processing, acoustics, and oceanography. The group focuses on:
- Random matrix theory.
- Sparse array design.
- Deep-water ambient noise.
- Mode propagation.
The work is funded by the Office of Naval Research.
The PRL, under director Maryam Parsa, focuses on developing next generation of neuro-inspired algorithms, neuromorphic computing, and distributed collaborative learning. Current research topics include:
- Bayesian Brain
- Physics-Informed Neuromorphic Computing
- Multi-objective Bayesian-Evolutionary Optimization
- Novel Bio-Inspired Paradigms
- Computational Neuroscience
- Full-Stack Omnidirectional Cognitive Computing
- Neuromorphic Computing for Distributed Learning
- Algorithm-Hardware Codesign
- Safe Lifelong Learning
- Quantum Machine learning
- Quantum Data Privacy
- Quantum Sensing
- Automated neural network design
- Automated hardware-software co-design
- 5G cybersecurity.
- Cyber-physical system/Internet of Things security.
- Wireless physical layer security.
- Spectrum-sharing system security and privacy.
- Edge-computing security and privacy with applications of machine learning.
- Information theory.
- Optimization techniques.
Affiliated with ECE
The Interdisciplinary Biomedical Imaging Lab conducts translational research using imaging to investigate pathophysiology and function. One overarching focus is the investigation of brain-body interactions through imaging. In particular, we are studying the interactions between the central and peripheral nervous system and the musculoskeletal system in a number of clinical conditions of major public health significance, such as chronic pain, stroke, spinal cord injury, and amputation.
This interdisciplinary group conducts pre-clinical research for developing new technology and translational research on human subjects. The group uses state-of-the-art ultrasound and laser instrumentation for developing new ultrasound, optical, and hybrid imaging techniques.
Our research has potential applications in noninvasive diagnosis, screening, and treatment monitoring for a number of diseases, as well as for understanding underlying mechanisms of disease. Principal investigators: Siddhartha Sikdar and Parag Chitnis. Peterson Family Health Sciences Hall, Room 3300.