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Department of Electrical and Computer Engineering

Department of Electrical and Computer Engineering

Tufts University

Department of Electrical and Computer Engineering at Tufts University has 42 faculty on GradNova.

Faculty

J
Computer Architecture
Computer-Aided Design and Computing at the Intersection of Hardware and Software
Interdisciplinary Courses Combining These Topics With Biology
VLSI
+5
B
Advancements in Semiconductor Devices and Circuit Design
Anomaly Detection Techniques and Applications
Face Recognition and Analysis
GAN-Based Semiconductor Devices and Materials
+1
K
Antenna Design
Channel Coding
Fdtd
Medical Devices
+9
D
Biomaterials
Biomedical Microdevices
Ingestibles
Micro and Nano Fabrication
+12
E
Gold and Silver Nanoparticles Synthesis and Applications
Metamaterials and Metasurfaces Applications
Plasmonic and Surface Plasmon Research
Solar Cell Performance Optimization
+1
B
Low-Light Passive Imaging
Photon-Counting Imaging
Wavefront Sensing
L
Actuation and Control Methods
Autonomous Medical Robotics
Embodied Artificial Intelligence
Image-Guided Interventions
+9
M
5G/6G Systems and Techniques
Applied Optimization
Machine Learning
Wireless Communications and Networks
+5
K
Karen Panetta

Distinguished Professor and Dean of Graduate Education

Department of Electrical and Computer Engineering

Tufts University

Computer Vision
Signal Processing
Simulation Modeling
Heart Rate Variability and Autonomic Control
+4
J
Computational Mathematics
Computer Vision
Data Mining
Graph Theory
+9
E
Airport Security
Automatic Target Detection and Classification
Environmental Monitoring and Remediation
Human Performance Assessment
+11
Y
AI for Healthcare and Biomedical Applications
Electronic Design Automation
Hardware Security
Trusted AI
+1
V
Analog Signal Processing
Design of Silicon-Based Mixed-Mode VLSI Systems (analog, Digital, Rf, Optical)
Optoelectronic System-On-Chip Modeling and Integration for Applications in Optical Wireless Communication and Biomedical Imaging
Optical Wireless Communication Technologies
+4
M
Computer Architecture
Computer Systems
Computer Systems for Machine Learning
Embedded Systems
+10
M
Emerging Technologies
Hardware for Machine Learning
Noise Modeling and Reliability
Non-Volatile Memories
+6
S
Information Theory
Machine Learning
Optimal Transport
Statistical Signal Processing
+5
S
Computer-Aided Design for Integrated Circuits
Machine Learning for Systems Biology
Metabolic Engineering
Computational Drug Discovery Methods
+4
A
Data Mining
Performance Analysis
Software Systems Engineering
System, Network, and Data Management
+5
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