Cheng Chen

I am a fourth-year Ph.D. student at the Elmore Family School of Electrical and Computer Engineering, Purdue University, advised by Prof. Saurabh Bagchi at Dependable Computing Systems Lab (DCSL). Before that, I received my Bachelor's degree in Computer Science at Nanjing University in 2020 and a Master's degree in Computer Engineering at New York University in 2022.

I spent a wonderful Spring semester at University of California, Berkeley as an exchange student in 2019.

My research focuses on intelligent computer vision systems.

3D Computer Vision --- Broad interest in multi-modal 3D scene understanding; current focus on collaborative perception for 3D/4D semantic occupancy prediction/forecasting among connected autonomous agents, integrating foundation models and generative 3D representations such as Gaussian Splatting.

Intelligent Vision Systems --- Research on resource-efficient deep learning for edge perception, emphasizing performance–resource trade-offs, energy and compute efficiency, communication limits, and real-time coordination across distributed platforms.

Email  /  Instagram  /  Github  /  Google Scholar

News

Publications

(* indicates equal contribution)

Vision-Only Gaussian Splatting for Collaborative Semantic Occupancy Prediction
Cheng Chen, Hao Huang, Saurabh Bagchi
AAAI 2026 (Oral Presentation)  
Paper / Project page / Code
AD-VRAN: DRL-based Adaptive Deployment of Virtualized RAN in an Open Telco Edge Cloud
Yuan-Yao Lou, Cheng Chen, Ying-Hui Huang, Mung Chiang, Kwang Taik Kim
JSAC 2026  
E2D2: Energy-Efficient and Deadline-Driven Ensemble Inference at the Communication-Constrained Edge
Cheng Chen, Xiang Li, Li-Heng Su, Saurabh Bagchi, Kwang Taik Kim
In submission 2025  
HopTrack: A Real-time Multi-Object Tracking System for Embedded Device
Xiang Li, Cheng Chen, Yuan-Yao Lou, Mustafa Abdallah, Kwang Taik Kim, Saurabh Bagchi
Arxiv 2024  
Manifold Adversarial Learning for Cross-domain 3D Shape Representation
Hao Huang, Cheng Chen, Yi Fang
ECCV 2022  
Non-Rigid Multiple Point Set Registration Using Latent Gaussian Mixture
Hao Huang, Cheng Chen, Yi Fang
ICIP 2022  
Teaching and Services

  • Teaching Assistant: ECE 20001 Electrical Engineering Fundamentals, PurdueSU 2025
  • Reviewer: AAAI 2026, IEEE VNC 2025, IEEE Networking Letters 2024
  • Teaching Assistant: CS-GY 6953 / ECE-GY 7123 Deep Learning, NYUSP 2022
Selected Awards

  • Phi Kappa Phi Honor Society, Purdue University2025
  • Graduate School of Engineering Scholarship, New York University2020
  • People’s Award, Nanjing University2017 & 2018
  • National Elite Program Scholarship, Nanjing University2018


Thank Dr. Jon Barron for sharing the source code of his personal page.

Last edited: Dec, 2025