# Jack Wang > Software Engineer and Hiphop/House Dancer Location: San Jose, California, United States Profile: https://flows.cv/jackwang1 I am a Simulation Engineer focusing on sensor and scene simulation for autonomous driving and robotics. My work centers on creating realistic, scalable environments that enable robust perception, planning, and validation. Technically, I specialize in 3D scene reconstruction, generative scene modeling, and simulation pipelines that integrate LiDAR, cameras, and multi-modal data. In parallel, I conduct research on smart agents with reinforcement learning, leveraging simulation as a training ground for adaptive, decision-making policies. This synergy between simulation and learning helps bridge the gap between controlled virtual environments and complex real-world scenarios. ## Work Experience ### Staff Software Engineer @ WeRide.ai Jan 2019 – Present | San Jose, Bay Area At WeRide, I work on autonomous driving simulation, sensor modeling, and 3D scene reconstruction, and currently lead sensor simulation algorithms. My recent work includes: • closed-loop simulation for multi-agent interaction, RL post-training, and large-scale testing • high-fidelity LiDAR/camera simulation across weather, lighting, and dynamic conditions • 3D Gaussian Splatting based driving-scene reconstruction and dynamic asset extraction • feed-forward generative 3D scene systems with text/image/HD map conditioning for rendering and LiDAR simulation • Git-like HD map maintenance and data pipelines for continuous map update and training-data production ### Research Student @ Volvo Construction Equipment Jan 2018 – Jan 2018 | Greater Pittsburgh Area Proposed a loss function by fusing a classification loss with a weighted target-relevance loss for online fine-tuning. By applying this method to the MDNet, we observed a performance improvement with an increase in accuracy from 53.2% to 53.9% and in robustness from 31.5 to 27.6 on the VOT dataset. ### Tracking Software Engineer Intern @ Oculus VR Jan 2018 – Jan 2018 | Menlo Park Positional Tracking Group Merged multi-session maps from the same location. Improved features matching by selecting distinct descriptors based on TF-IDF scores and gravity information. Built a feature selector to pick up stable points for better map building. ### Summer Research Intern @ Harvard University Jan 2016 – Jan 2016 | Greater Boston Area Used a CNN-PCA method to detect needles in MRI with an accuracy improvement from 75.0% to 93.1%. Deployed the model in a real-time surgery system and co-developed the website: http://needlefinder.org. ## Education ### Master's degree in Computer Vision Carnegie Mellon University ### Bachelor of Engineering - BE in Electronic Engineering Tsinghua University ## Contact & Social - LinkedIn: https://linkedin.com/in/jack-wang-053bbb148 --- Source: https://flows.cv/jackwang1 JSON Resume: https://flows.cv/jackwang1/resume.json Last updated: 2026-04-12