Our lab is supported by a highly skilled and dedicated team of professionals with extensive experience in the fields of Electrical Engineering and Computer Science:
Phone: 08 646 12 34
Office: 700, Bldg. 33
I am a faculty member in the School of Electrical and Computer Engineering. I earned my Ph.D. in Electrical Engineering from MIT and joined the faculty in 2007. Throughout my academic career, I have been dedicated to advancing both research and education, mentoring graduate students, and contributing to numerous collaborative projects. I am passionate about creating a dynamic learning environment and fostering innovation through interdisciplinary collaboration. My work focuses on developing efficient algorithms for real-time data analysis, designing next-generation communication systems, enhancing AI models for embedded devices. In 2007, I established My Research Lab, which continues to support cutting-edge projects and student development.
Lab Engineer
Phone: 08 646 15 14
Office: 404, 33
Administrative Assistant
Phone: 08 646 15 12
Office: 409, Bldg. 33
Phone: 08 646 17 35
Office: 422, Bldg. 33
Machine Learning and Artificial Intelligence; Communication Systems and Networks; VLSI and Digital Hardware Design
Phone: 08 646 58 90
Office: 418, Bldg. 33
Deep Learning based Graph Generation Techniques and other learning-on-graph subjects
Ph.D.
Co-Advisor: Prof. Oren Idan
Computer Vision; Deep Learning
Ph.D.
Information Theoretical Compression Methods for Foundation Models; Video Foundation Models; Computer Vision
Ph.D.
Co-Advisor: Prof. Kobi Cohen
Computer Vision; Deep Learning; AI
Ph.D.
Graph Neural Networks; Signal Processing; Computer Vision and Image Processing
Ph.D.
Co-Advisors: Prof. Bruno Ribeiro (Purdue), Dr. Moshe Eliasof (Cambridge/BGU)
Using ODEs in Representation Learning for Foundation Models; Graph Neural Networks; Inverse Problems
M.Sc.
Graph Foundation Models; Embedded Systems and Internet of Things (IoT); VLSI and Digital Hardware Design
Co-Advisor: Prof. Oren Idan
Resource-Efficient Learning; Geometric Deep Learning; Power Systems and Renewable Energy
Graph Neural Networks (GNNs); Geometric Deep Learning; VLSI and Digital Hardware Design
Resource-Efficient Learning; Adversarial Robustness; Graph Neural Networks (GNNs); Geometric Deep Learning
Resource-Efficient Learning; Adversarial Robustness; ; VLSI and Digital Hardware Design
Resource-Efficient Learning; Adversarial Robustness
Resource-Efficient Learning; Adversarial Robustness; Geometric Deep Learning
Electrical Engineering Department, MIT, USA
Resource-Efficient Learning; Adversarial Robustness; Graph Neural Networks (GNNs); Geometric Deep Learning
Co-Advisor: Dan Shar; Foundation Models for Uni- and Multi-Modal DataCurrently: TechnionCo-adviser: Dr. Mira Toledano; Resource-Efficient Learning and Adversarial RobustnessCurrently: MIT, USA
