Boris Ivanovic

Boris Ivanovic

NVIDIA

Boris Ivanovic is a Senior Research Scientist and Manager in the Autonomous Vehicle Research Group. Prior to joining NVIDIA, he received his Ph.D. in Aeronautics and Astronautics under the supervision of Marco Pavone in 2021 and an M.S. in Computer Science in 2018, both from Stanford University. He received his B.A.Sc. in Engineering Science from the University of Toronto in 2016.

Boris' research interests are rooted in trajectory forecasting and its interactions with the rest of the autonomy stack. This usually includes a mix of improving raw prediction performance, integrating prediction with perception and planning, and holistically evaluating autonomy stack performance. He has also previously conducted research in the fields of computer vision, natural language processing, and data science.

In his spare time, Boris enjoys playing tennis, skiing, hiking, traveling, watching docudramas, and cooking.

For more information, please check out his personal page.

ial-Temporal Scene Decomposition via Self-Supervision
  • Partial-View Object View Synthesis via Filtered Inversion
  • trajdata: A Unified Interface to Multiple Human Trajectory Datasets
  • Language-Guided Traffic Simulation via Scene-Level Diffusion
  • Language Conditioned Traffic Generation
  • DTPP: Differentiable Joint Conditional Prediction and Cost Evaluation for Tree Policy Planning in Autonomous Driving
  • Reinforcement Learning with Human Feedback for Realistic Traffic Simulation
  • BITS: Bi-level Imitation for Traffic Simulation
  • Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning
  • Planning with Occluded Traffic Agents using Bi-Level Variational Occlusion Models
  • Tree-structured Policy Planning with Learned Behavior Models
  • Robust and Controllable Object-Centric Learning through Energy-based Models
  • DiffStack: A Differentiable and Modular Control Stack for Autonomous Vehicles
  • Task-Relevant Failure Detection for Trajectory Predictors in Autonomous Vehicles
  • Propagating State Uncertainty Through Trajectory Forecasting
  • ScePT: Scene-consistent, Policy-based Trajectory Predictions for Planning
  • Whose Track Is It Anyway? Improving Robustness to Tracking Errors with Affinity-Based Prediction
  • MTP: Multi-Hypothesis Tracking and Prediction for Reduced Error Propagation
  • Injecting Planning-Awareness into Prediction and Detection Evaluation
  • Rethinking Trajectory Forecasting Evaluation