Boris Ivanovic
Manager, Autonomous Vehicle Research at NVIDIA
Palo Alto, California, United States
Summary
🤩
Rockstar🎓
Top SchoolBoris Ivanovic is a manager leading autonomous vehicle research at NVIDIA with a decade of experience at the intersection of deep learning, control, and perception. A Stanford ASL alum with an MS and PhD-level training bridging computer science and aerospace engineering, he has progressed from intern roles at Amazon and Toyota Research Institute to research scientist and manager at NVIDIA. His work emphasizes making learning-based systems robust for real-world autonomy, informed by earlier projects on reinforcement learning with control systems and large-scale data analysis. Based in Palo Alto, he combines hands-on research with team leadership to move cutting-edge models toward production within a hardware-aware environment. Outside the obvious résumé, he has a track record of contributing to both academic and industrial projects—from flying-machine arenas to drone delivery software—that reflect a practical focus on safety and systems integration.
10 years of coding experience
4 years of employment as a software developer
Ontario Secondary School Diploma, Ontario Secondary School Diploma at Bayview Glen SchoolBachelor of Applied Science (B.A.Sc.), Engineering Science - ECE Option, Bachelor of Applied Science (B.A.Sc.), Engineering Science - ECE Option at University of TorontoMaster of Science (MS), Computer Science, Master of Science (MS), Computer Science at Stanford University
Github Skills (48)
random-walk10
robotics10
datasets10
forecasting10
nvidia10
autonomous-vehicles10
heterogeneous10
forecast10
visual-question-answering10
reasoning10
python9
time-series9
self-driving-car9
deep-learning9
autonomous-driving9
Programming languages (6)
Github contributions (5)
NVlabs/trajdata
May 2022 - Jan 2023
A unified interface to many trajectory forecasting datasets.
Contributions:13 releases, 9 reviews, 26 commits in 8 months
forecastingpythondeep-learningmachine-learningtrajectory-forecasting
StanfordASL/Trajectron-plus-plus
Apr 2020 - Jun 2022
Code accompanying the ECCV 2020 paper "Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data" by Tim Salzmann*, Boris Ivanovic*, Punarjay Chakravarty, and Marco Pavone (* denotes equal contribution).
Contributions:5 commits, 7 PRs, 16 pushes in 2 years 2 months
forecastingeccvplanningtimequal
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