I am a 3rd-year Ph.D. student in Computer Science at University of Southern California (USC), advised by Prof. Viktor Prasanna. Before that, I got my B.S. degree from Central South University (CSU), advised by Prof. Ning Gui. My current research interests lie in AI coding with structure reasoning.
Gangda Deng*, Zhaoling Chen*, Zhongming Yu, Haoyang Fan, Yuhong Liu, Yuxin Yang, Dhruv Parikh, Rajgopal Kannan, Le Cong, Mengdi Wang, Qian Zhang, Viktor Prasanna, Xiangru Tang, Xingyao Wang EvoClaw: Evaluating AI Agents on Continuous Software Evolution. Code Website ICML 2026 (Avg Score 4.67/6)
Gangda Deng, Hongkuan Zhou, Rajgopal Kannan, Viktor Prasanna Mixture of Scope Experts at Test: Generalizing Deeper Graph Neural Networks with Shallow Variants. Code Slides NeurIPS 2025 (3 Clear Accepts)
Zhaoling Chen*, Xiangru Tang*, Gangda Deng*, Fang Wu, Jialong Wu, Zhiwei Jiang, Viktor Prasanna, Arman Cohan, Xingyao Wang LocAgent: Graph-Guided LLM Agents for Code Localization. Code Slides ACL 2025 (OA: 3.67, Meta: 4)
Gangda Deng*, Hongkuan Zhou*, Hanqing Zeng, Yinglong Xia, Christopher Leung, Jianbo Li, Rajgopal Kannan, Viktor Prasanna TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning. Code Slides IPDPS 2024 (2 Strong Accepts, 1 Clear Accept)
Yuxin Yang, Gangda Deng, Ömer Faruk Akgül, Nima Chitsazan, Yash Govilkar, Akasha Tigalappanavara, Shi-Xiong Zhang, Sambit Sahu, Viktor Prasanna SParC-RAG: Adaptive Sequential–Parallel Scaling with Context Management for Retrieval-Augmented Generation. Arxiv 2026
Gangda Deng*, Yuxin Yang*, Ömer Faruk Akgül*, Hanqing Zeng, Yinglong Xia, Rajgopal Kannan, Viktor Prasanna Training Diverse Graph Experts for Ensembles: A Systematic Empirical Study. Code Arxiv 2025
Yuhong Liu*, Gangda Deng*, Hongkuan Zhou, Cauligi S. Raghavendra, Rajgopal Kannan, Ananthram Swami, Viktor Prasanna AP Selection in Uplink Cell-Free Massive MIMO: An Unsupervised Heterogeneous GNN Approach. WCNC 2025
Yi-Chien Lin*, Gangda Deng*, Viktor Prasanna
A Unified CPU-GPU Protocol for GNN Training.
Code
CF 2024
Gangda Deng*, Ömer Faruk Akgül*, Hongkuan Zhou, Hanqing Zeng, Yinglong Xia, Jianbo Li, Viktor Prasanna An Efficient Distributed Graph Engine for Deep Learning on Graphs. Code Slides SC Workshop 2023
Chenhuan Yu, Gangda Deng, Ning Gui PairGNNs: enabling graph neural networks with pair-based view Neural Computing and Applications 2023