About Me
Hi! I'm Abhi Kamboj, a Ph.D. candidate in Electrical and Computer Engineering at the University of Illinois Urbana-Champaign, where I'm also an NSF Graduate Research Fellow. My work sits at the intersection of sensing and AI, where I build machine learning systems that help us better understand motion, perception, and interaction across humans and machines.
Over the years, my research has taken me from multi-modal deep learning for human action recognition to robotics and foundation models, and even into large-scale video reasoning at Google. A common theme in my projects is finding ways to make learning systems robust: aligning modalities, transferring knowledge across domains, and making sense of data that doesn't come in neat, synchronized packages.
Alongside research, I've enjoyed teaching and mentoring-from helping undergraduates debug their first FPGA projects, to guiding new researchers through the nuances of multimodal learning. I believe that the most exciting ideas often emerge from collaboration and interdisciplinary thinking.
Beyond academia, I've explored applied AI in industry with experiences at Google, NVIDIA, Netradyne, Western Digital, and Collins Aerospace. Each stop gave me new perspectives on scaling algorithms into systems that matter—whether it's real-time scene text recognition on edge devices, multi-object tracking for autonomous driving, or reasoning about complex video for next-generation AI.
If you'd like to dive deeper into the details, my publications, experiences, and academic journey are below.
University of Illinois at Urbana-Champaign
- Ph.D. Electrical and Computer Engineering (expected May 2026)
- M.S. Electrical and Computer Engineering (May 2024)
- B.S. Computer Engineering (May 2021)
- B.S. Innovation Leadership and Engineering Entrepreneurship (May 2021)
- Leadership Certificate (Portfolio)
Honors & Programs
- Chancellor's Scholar – Campus Honors Program
- James Scholar – Engineering Honors
- IEEE Eta Kappa Nu (HKN)
- Tau Beta Pi (TBP)
Key Courses
- ECE 513 Vector Space Signal Processing
- ECE 563 Information Theory
- ECE 543 Statistical Learning Theory
- ECE 534 Random Process
- ECE 544 Pattern Recognition
- ECE 527 System on Chip Design
- ECE 490 Intro to Optimization
- CS 473 Algorithms
- ECE/CS 598SG Learning Based Robotics
- ECE 549/CS 543 Computer Vision
- ECE 484 Principles of Safe Autonomy
- ECE 534 Random Processes
- CS 473 Algorithms
- ECE 498/598NS Deep Learning in Hardware
- ECE 498 Quantum Information Processing Theory
- ECE 411 Computer Organization and Design
- GE/SE 361 Emotional Intelligence(Portfolio)
École Polytechnique Fédérale de Lausanne
- B.S. Computer Science Exchange Semester, Fall 2019