Jim Aldon D'Souza

For the past decade, I've worked as an engineer and leader in autonomous driving systems, bridging mobile robotics and machine learning to solve real-world autonomy challenges. My career spans every layer of autonomous vehicle development—from perception and mapping to prediction, planning, and control—with a focus on translating cutting-edge research into scalable solutions.

Leadership at Torc Robotics

As Sr. Engineering Manager at Torc Robotics (a Daimler Trucks subsidiary), I lead three global teams across Germany, the U.S., and Canada with 23 ML scientists & engineers reporting. These teams—which I built from scratch—now anchor Torc's autonomy stack:

End-to-End: Responsible for coming up with a single-model to do everything from perception to planning, and replace the traditional autonomy stack
Motion Forecasting: Develops & deploys models to predict next 6-10 seconds of every vehicle around SDV, based on learned behaviors from data
Learned Planning: Develops & deploys models that learn safe, legal, comfortable trajectories to execute a highly dynamic environment

Experience & Research

Before Torc, I held technical roles at Algolux and TomTom, advancing robot perception, SLAM, and visual odometry. My academic work at DFKI (Germany) focused on autonomous navigation in featureless environments—a problem later echoed in real-world autonomy challenges I've tackled professionally.

I've co-authored two influential papers: a CVPR 2023 study on using sound to enhance automotive vision systems and a spotlight paper at ICLR 2022 (top 5% of submissions) on interaction-aware motion prediction. I hold a Master's in electrical engineering, robotics, and machine learning from Technical University of Denmark, Nanyang Technological University, and DFKI.

Engineering Philosophy

I specialize in identifying gaps between academic research and industry needs, prioritizing pragmatic innovation. At Torc, I've shaped technical roadmaps, hired and mentored teams, and delivered systems now core to self-driving truck operations—all while keeping the focus on solving the engineering puzzles that make autonomy safer and more reliable.