Dingding Zheng
Senior Autonomous Driving Software Engineer, Mercedes-Benz
I am a senior autonomous driving software engineer at Mercedes-Benz. Prior to that, I was a graduate student at the GRASP Laboratory, University of Pennsylvania.
At Penn, I worked on DCIST, a project focused on multi-agent and heterogeneous systems, supervised by Prof. Vijay Kumar and Dr. Siddharth Mayya.
My interests lie in embodied intelligence, micro unmanned aerial vehicles, robot perception, and learning. Much of my work focuses on making algorithms safe, agile, and reliable on real robotic platforms.

Experience
Principal of Shanghai
Autonomous Driving Software Engineer
Teaching Assistant
MEAM 620: Advanced Robotics (Fall 2021)
Service
UPenn Alumni Interviewer
Projects

G1 Motion Studio
GPU-accelerated motion control for the Unitree G1, combining score-matching motion priors, reinforcement learning, and terrain-adaptive control for natural full-body locomotion.





Quadrotor Control
Trajectory generation and control algorithms for a quadrotor flying aggressive maneuvers.

F1TENTH Autonomous Racing
Maximum-speed path and velocity-profile generation using CMA-ES, pure-pursuit control, and obstacle avoidance with ODG-PFM and RRT*.
SMORES-EP Modular Robots
Controller improvements, test-environment development, and topology-similarity analysis for a reconfigurable modular robot platform.

Human–Robot Interaction in Multi-Agent Traffic
Car dynamics and MPC-based human decision models integrated into a multi-agent environment, with robot agents trained using MADDPG and human agents modeled through social forces.

Humanoid Robot SLAM
2D occupancy-grid mapping and localization using laser scans, IMU, and odometry, extended with Kinect imagery to build a textured map.

Visual-Inertial Panorama
A Kalman filter estimates 3D orientation from IMU data, calibrated against Vicon ground truth, to generate real-time panoramas.

Mask R-CNN
Object instance segmentation experiments using the Mask R-CNN framework.

Clipped PPO for Car Racing
Clipped Proximal Policy Optimization applied to OpenAI Gym's CarRacing environment.

Image Super-Resolution with GANs
A generative adversarial network that reconstructs high-resolution images from downsampled inputs.

YOLO Object Detection
A YOLO v1 implementation for detecting objects in street-scene images.

GMM-Based Barrel Detection
A Gaussian mixture model detects barrels in images and estimates their positions in world coordinates.

Object Pose Estimation
A heatmap-based neural network estimates object keypoints and recovers an oilcan's pose from images.

Planar Tracking and Augmented Reality
Homography estimation maps video frames onto logo points for stable planar augmentation.

Difference of Gaussians Feature Detection
A scale-space feature detector approximating the Laplacian of Gaussian with Difference of Gaussians.

Actor–Critic for Acrobot
An actor–critic neural network trained to control the OpenAI Gym Acrobot environment.