Education
PhD in Electrical and Computer Engineering, University of Illinois Urbana-Champaign
Subjects
Multimodal Machine Learning, Temporal Reasoning in Video and Sensor Data, Cross-Modal Alignment, Multi-Agent Reasoning, Embedded AI
Achievements
BS in Computer Engineering (dual in Engineering Entrepreneurship) from UIUC (2021); academic exchange semester at EPFL (2019); NSF Graduate Research Fellow (2023-2026); IEEE Eta Kappa Nu and Tau Beta Pi Engineering Honors; Dean's List, Engineering James Scholar, and Chancellor's Scholar (2017-2021); Best Reviewer Award at the UniReps Workshop at NeurIPS 2024; publications at NeurIPS, IJCAI, CVPR, and RO-MAN
About
Abhi holds a PhD in Electrical and Computer Engineering from the University of Illinois Urbana-Champaign and is a National Science Foundation Graduate Research Fellow, specializing in multimodal machine learning and temporal reasoning in videos and sensor data. His research spans cross-modal alignment, multi-agent reasoning, and robust multimodal machine learning. He is joining Waymo as a Machine Learning Engineer, previously completed research internships at Google, Netradyne, and NVIDIA, and has mentored undergraduate researchers since 2021.
Discipline
Computer Science & AI
Academic Achievements
- Doctor of Philosophy in Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (May 2026), - Bachelor of Science in Computer Engineering, Dual in Engineering Entrepreneurship, University of Illinois at Urbana-Champaign (May 2021) - Academic Exchange Semester at EPFL, School of Computer and Communication Sciences, Switzerland (Dec 2019). - National Science Foundation Graduate Research Fellow (2023–2026). - IEEE Eta Kappa Nu and Tau Beta Pi Engineering Honors. - Dean’s List Standing, Engineering James Scholar, and University Chancellor’s Scholar Honors (2017–2021). - Best Reviewer Award, Unifying Representations Workshop (UniReps) at NeurIPS 2024.
Teaching & Mentoring Experience
- Undergraduate Research Mentor, UIUC (Aug 2021 – present): Mentored multiple undergraduate students in machine learning, typically 1–3 students per year for ~1–2 hours per week each, covering topics such as recurrent networks, diffusion models, GANs, multimodal alignment, and core ML practices (data preprocessing, feature engineering, evaluation, fine-tuning, compression, and hyperparameter tuning). - Teaching Assistant, ECE 220 Computer Systems & Programming, UIUC (Aug 2021 – May 2022): Led weekly office hours and lab sections of ~40 students (approximately 5–8 hours per week), teaching LC-3 assembly, C programming, algorithms, and basic object-oriented design, and contributed exam questions for a class of 400+ students. - Course Assistant, ECE 385 Digital Systems, UIUC (Aug 2020 – May 2021): Assisted students weekly (around 4–6 hours per week) with FPGA-based digital design projects, including processor and RAM design, SystemVerilog, state machines, simulations, and timing analysis. - IEEE Eta Kappa Nu Tutor, UIUC (Aug 2018 – May 2021): Provided one-on-one tutoring and open review sessions (roughly 2–4 hours per week during semesters) for courses in computing, signal processing, probability, electromagnetics, semiconductors, computer systems, and AI, and participated in outreach events teaching basic circuits and programming to K–12 students
Explore more mentors