Chao Shang

I am a Senior Applied Scientist at Amazon AWS AI. My research interests lie primarily in deep graph learning, natural language processing and machine learning using large-scale graph-structured and text datasets, with an emphasis on LLM safety, LLM finetuning, and knowledge graphs. I received my Ph.D. from the Computer Science and Engineering Department, University of Connecticut, advised by Prof. Jinbo Bi. I got my M.S. degree at Beijing University of Posts and Telecommunications (BUPT).

Experience

06/2022 - Present | Senior Applied Scientist | Amazon AWS AI

Develop high-performance large language models and customized solutions @ Amazon Bedrock
Build safeguards for generative AI applications @ Amazon Bedrock Guardrails

09/2020 - 05/2022 | Research Scientist | JD AI Research, JD.COM Silicon Valley Research Center

Mentor: Dr. Jing Huang

01/2020 - 06/2020 | Research Intern | MIT-IBM Watson AI Lab, IBM Research

Mentor: Dr. Jie Chen

05/2019 - 09/2019 | Research Intern | IBM Thomas J. Watson Research Center, IBM Research

Knowledge Induction Team @ IBM Research AI

05/2018 - 09/2018 | Research Intern | JD AI Research, JD.COM Silicon Valley Research Center

SAIL-JD Knowledge Graph Research Program

09/2015 - 08/2020 | Research Assistant | University of Connecticut

Supervisors: Prof. Jinbo Bi and Prof. Fei Wang (Advised by Prof. Wang for a year).

07/2014 - 11/2014 | Research Assistant | University of Southern California

Supervisor: Prof. Viktor K. Prasanna

Publications

Unraveling and Mitigating Safety Alignment Degradation of Vision-Language Models
Qin Liu, Chao Shang, Ling Liu, Nikolaos Pappas, Jie Ma, Neha Anna John, Srikanth Doss, Lluis Marquez, Miguel Ballesteros, Yassine Benajiba. ACL Findings, 2025.

From Instructions to Constraints: Language Model Alignment with Automatic Constraint Verification
Fei Wang, Chao Shang, Sarthak Jain, Shuai Wang, Qiang Ning, Bonan Min, Vittorio Castelli, Yassine Benajiba, Dan Roth. NAACL Findings, 2025.

Diable: Efficient Dialogue State Tracking as Operations on Tables
Pietro Lesci, Yoshinari Fujinuma, Momchil Hardalov, Chao Shang, Lluis Marquez. The 61st Annual Meeting of the Association for Computational Linguistics (ACL), 2023. (Findings) Code

Automatic depression screening using social interaction data on smartphones
Shweta Ware, Chaoqun Yue, Reynaldo Morillo, Chao Shang, Jinbo Bi, Jayesh Kamath, Alexander Russell, Dongjin Song, Athanasios Bamis, Bing Wang. Smart Health, 2022.

Variance of the Gradient Also Matters: Privacy Leakage from Gradients
Yijue Wang, Jieren Deng, Dan Guo, Chenghong Wang, Xianrui Meng, Hang Liu, Chao Shang, Binghui Wang, Qin Cao, Caiwen Ding, Sanguthevar Rajasekaran. International Joint Conference on Neural Networks (IJCNN), 2022.

Improving Time Sensitivity for Question Answering over Temporal Knowledge Graphs
Chao Shang, Guangtao Wang, Peng Qi, Jing Huang. The 60th Annual Meeting of the Association for Computational Linguistics (ACL), 2022.

TAG: Gradient Attack on Transformer-based Language Models
Jieren Deng, Yijue Wang, Ji Li, Chenghong Wang, Chao Shang, Hang Liu, Sanguthevar Rajasekaran and Caiwen Ding. The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021. (Findings)

Open Temporal Relation Extraction for Question Answering
Chao Shang, Peng Qi, Guangtao Wang, Jing Huang, Youzheng Wu, and Bowen Zhou. Automated Knowledge Base Construction (AKBC), 2021.

Discrete Graph Structure Learning for Forecasting Multiple Time Series
Chao Shang, Jie Chen, and Jinbo Bi. The International Conference on Learning Representations (ICLR), 2021. Code

Multi-view spectral graph convolution with consistent edge attention for molecular modeling
Chao Shang, Qinqing Liu, Qianqian Tong, Jiangwen Sun, Minghu Song, and Jinbo Bi. Neurocomputing, 2021. Code

End-to-End Structure-Aware Convolutional Networks on Graphs
Chao Shang. University of Connecticut, 2020.

Taxonomy Construction of Unseen Domains via Graph-based Cross-Domain Knowledge Transfer
Chao Shang, Sarthak Dash, Md Faisal Mahbub Chowdhury, Nandana Mihindukulasooriya, and Alfio Gliozzo. The 58th Annual Meeting of the Association for Computational Linguistics (ACL), 2020. Code

Automatic depression prediction using Internet traffic characteristics on smartphones
Chaoqun Yue, Shweta Ware, Reynaldo Morillo, Jin Lu, Chao Shang, Jinbo Bi, Jayesh Kamath, Alexander Russell, Athanasios Bamis, Bing Wang. Smart Health, 2020.

Predicting Outcomes of Chemical Reactions: A Seq2Seq Approach with Multi-view Attention and Edge Embedding
Xia Xiao, Chao Shang, Jinbo Bi and Sanguthevar Rajasekaran. International Joint Conference on Neural Networks (IJCNN), 2020.

End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion
Chao Shang, Yun Tang, Jing Huang, Jinbo Bi, Xiaodong He, and Bowen Zhou. The AAAI Conference on Artificial Intelligence (AAAI), 2019. Code

Large-scale Automatic Depression Screening Using Meta-data from WiFi Infrastructure
Shweta Ware, Chaoqun Yue, Reynaldo Morillo, Jin Lu, Chao Shang, Jinbo Bi, Jayesh Kamath, Alexander Russell, Athanasios Bamis and Bing Wang. ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), 2019. (ACM Journal of IMWUT)

Predicting Depressive Symptoms Using Smartphone Data
Shweta Ware, Chaoqun Yue, Reynaldo Morillo, Jin Lu, Chao Shang, Jayesh Kamath, Athanasios Bamis, Jinbo Bi, Alexander Russell and Bing Wang. IEEE/ACM CHASE, 2019.

Edge Attention-based Multi-Relational Graph Convolutional Networks
Chao Shang, Qinqing Liu, Ko-Shin Chen, Jiangwen Sun, Jin Lu, Jinfeng Yi, and Jinbo Bi. arXiv preprint arXiv:1802.04944, 2018.

Joint Modeling of Heterogeneous Sensing Data for Depression Assessment via Multi-task Learning
Jin Lu, Chao Shang, Chaoqun Yue, Reynaldo Morillo, and Shweta Ware, Jayesh Kamath, Athansios Bamis, Alexander Russell, Bing Wang, and Jinbo Bi. ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), 2018. (ACM Journal of IMWUT)

Fusing Location Data for Depression Prediction
Chaoqun Yue, Shweta Ware, Reynaldo Morillo, Jin Lu, Chao Shang, Jinbo Bi, Jayesh Kamath, Alexander Russell, Athanasios Bamis and Bing Wang. IEEE Transactions on Big Data (IEEE TBDATA), 2018.

VIGAN: Missing View Imputation with Generative Adversarial Networks
Chao Shang, Aaron Palmer, Jiangwen Sun, Ko-Shin Chen, Jin Lu, Jinbo Bi.
IEEE International Conference on Big Data (IEEE BigData), 2017. Code

Event Extraction from Unstructured Text Data
Chao Shang, Anand Panangadan, and Victor K. Prasanna.
International Conference on Database and Expert Systems Applications (DEXA), 2015.

A carrier class IoT service architecture integrating IMS with SWE
Dongliang Xie, Chao Shang, Jinchao Chen, Yongfang Lai, and Chuanxiao Pang.
International Journal of Distributed Sensor Networks (IJDSN), 2014 .

Professional Services

Program Committee / Reviewer

Conferences: ACL, ICLR, NeurIPS, EMNLP, NAACL, AAAI, COLING, IJCAI, COLM, IJCAI, EACL, CIKM, ECML-PKDD, AMIA, ACL Rolling Review.
Journals: IEEE Transactions on Neural Networks and Learning Systems (TNNLS); Transactions on Knowledge and Data Engineering (TKDE); Neurocomputing; Transactions on Audio, Speech, and Language Processing; Artificial Intelligence Review; Journal of Artificial Intelligence Research (JAIR); Journal of Chemical Information and Modeling (JCIM); IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB); Journal of Health Information Science and Systems; ACS Omega; PLOS ONE.

Session Chair

SR1: Graph Neural Networks, CIKM 2019.

Awards

2020 Departmental Research Excellence Award
2019 Predoctoral Prize for Research Excellence
2019 AAAI Student Scholarship.
2018 Predoctoral Honorable Mention Award.
2018 the 4th Annual Graduate Poster Competition, Computer Science & Engineering First Place Award.
2017 IEEE International Conference on Big Data, Student Travel Award.
2014 National Scholarship for Graduate Students.

Teaching Experience

CSE-1010 Introduction to Computing for Engineers (09/2016-05/2017)
CSE-5820 Machine Learning (01/2017-05/2017)