Hello! I am a PhD candidate in Computer Science at Arizona State University (ASU), advised by Prof. Huan Liu. My research lies at the intersection of data mining, computational social science, AI, and NLP. I am particularly interested in understanding and mitigating online harms, such as disinformation, echo chambers, and conspiracies, and in leveraging and evaluating AI models for the benefit of science, public health, and well-being. I also work closely and am advised by Prof. Kristina Lerman and Prof. H. Russell Bernard.

Research Interests

• Public Health: Studying the impact of online activities on offline health-related outcomes; Pandemic dynamics; Multimodal and multilingual public health data collection and analysis.
• Data Mining: Developing advanced algorithms to collect, analyze, and model big data, aiming to provide practical insights to real-world applications and decision making.
• Computational Social Science: Leveraging computational methods and statistical models to address social problems; Fact-checking; Disinformation detection; Social polarization; Crisis Classification.
• AI for Good: Advancing applied ML, AI, and Human-AI collaboration to solve real-world problems and promote well-being; AI for science, AI evaluation, Large Language Model application.

Publications

(* indicates equal contributions)

Conference & Journal Papers

• Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens
  Chengshuai Zhao, Zhen Tan, Pingchuan Ma, Dawei Li, Bohan Jiang, Yancheng Wang, Yingzhen Yang, Huan Liu
  ACL Findings 2026; FoRLM@NeurIPS 2025

• CAMO: Causality-Guided Adversarial Multimodal Domain Generalization for Crisis Classification
  Pingchuan Ma, Chengshuai Zhao, Bohan Jiang, Saketh Vishnubhatla, Ujun Jeong, Alimohammad Beigi, Adrienne Raglin, Huan Liu
  The 30th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2026)

• Preference Leakage: A Contamination Problem in LLM-as-a-judge (🏆 Best Paper Award at DIG-BUG@ICML 2025)
  Dawei Li, Renliang Sun, Yue Huang, Ming Zhong, Bohan Jiang, Jiawei Han, Xiangliang Zhang, Wei Wang, Huan Liu
  The 14th International Conference on Learning Representations (ICLR 2026)

• On Causal and Anticausal LLM-Based Data Synthesis
  Bohan Jiang, Pingchuan Ma, Zhuoyu Shi, Fred Morstatter, Adrienne Raglin, Huan Liu
  The 19th International Conference on Web Search and Data Mining (WSDM 2026)

• Can Large Language Models Assess the Social Impact of Conspiracy Theories?
  Bohan Jiang, Dawei Li, Zhen Tan, Xinyi Zhou, Ashwin Rao, Kristina Lerman, H. Russell Bernard, Huan Liu
  International AAAI Conference on Web and Social Media (ICWSM 2026)

• Evaluating Multimodal Large Language Models for Simulating Subjective Human Responses to Short Video Content: A Case Study
  Prabal Shrestha, Bohan Jiang, Haoning Xue, Huan Liu, Xinyi Zhou
  ICWSM 2026 Workshop on Large Language Models for Social Reasoning and Simulation (SocialLLM@ICWSM 2026)

• From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge
  Dawei Li, Bohan Jiang, Liangjie Huang, Alimohammad Beigi, Chengshuai Zhao, Zhen Tan, Amrita Bhattacharjee, Yuxuan Jiang, Canyu Chen, Tianhao Wu, Kai Shu, Lu Cheng, Huan Liu
  Conference on Empirical Methods in Natural Language Processing (EMNLP 2025)

• Who’s Your Judge? On the Detectability of LLM-Generated Judgments
  Dawei Li, Zhen Tan, Chengshuai Zhao, Bohan Jiang, Baixiang Huang, Pingchuan Ma, Abdullah Alnaibari, Kai Shu, Huan Liu
  Lock-LLM@NeurIPS 2025

• Can LLMs Improve Multimodal Fact-Checking by Asking Relevant Questions?
  Alimohammad Beigi, Bohan Jiang, Dawei Li, Tharindu Kumarage, Zhen Tan, Pouya Shaeri, Huan Liu
  IEEE International Conference on Big Data (IEEE BigData 2025)

• An Interventional Approach to Real-Time Disaster Assessment via Causal Attribution
  Saketh Vishnubhatla, Alimohammad Beigi, Rui Heng Foo, Umang Goel, Ujun Jeong, Bohan Jiang, Adrienne Raglin, Huan Liu
  ACM International Conference on Information and Knowledge Management (CIKM 2025)

• Assessing On-the-Ground Disaster Impact Using Online Data Sources
  Saketh Vishnubhatla, Ujun Jeong, Bohan Jiang, Paras Sheth, Zhen Tan, Adrienne Raglin, Huan Liu
  SBP-BRiMS 2025

• In-Group Love, Out-Group Hate: A Framework to Measure Affective Polarization via Contentious Online Discussions
  Buddhika Nettasinghe, Ashwin Rao, Bohan Jiang, Allon Percus, Kristina Lerman
  The ACM Web Conference (WWW 2025), Research Track

• Large Language Models for Data Annotation and Synthesis: A Survey
  Zhen Tan*, Dawei Li*, Song Wang*, Alimohammad Beigi, Bohan Jiang, Amrita Bhattacharjee, Mansooreh Karami, Jundong Li, Lu Cheng, Huan Liu
  Conference on Empirical Methods in Natural Language Processing (EMNLP 2024)

• BlueTempNet: A Temporal Multi-network Dataset of Social Interactions in Bluesky Social
  Ujun Jeong, Bohan Jiang, Zhen Tan, H. Russell Bernard, Huan Liu
  IEEE Data Descriptions (2024)

• Catching Chameleons: Detecting Evolving Disinformation Generated using Large Language Models (🏆 Best Student Paper Award)
  Bohan Jiang*, Chengshuai Zhao*, Zhen Tan, Huan Liu
  IEEE International Conference on Cognitive Machine Intelligence (IEEE CogMI 2024)

• Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media
  Bohan Jiang, Lu Cheng, Zhen Tan, Ruocheng Guo, Huan Liu
  IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA 2024)

• Disinformation Detection: An Evolving Challenge in the Age of LLMs
  Bohan Jiang, Zhen Tan, Ayushi Nirmal, Huan Liu
  SIAM International Conference on Data Mining (SDM 2024)

• SocioHub: An Interactive Tool for Cross-Platform Social Media Data Collection
  Ayushi Nirmal, Bohan Jiang, Huan Liu
  SBP-BRiMS 2024

• Advancing Recognition Justice in Telecoupled Critical Mineral Supply Chains: The Promise of Social Media
  Datu Buyung Agusdinata, Hallie Eakin, Nicole Darnall, Bohan Jiang, Hugo Romero
  Energy Research & Social Science, 2023

• CoVaxNet: An Online-Offline Data Repository for COVID-19 Vaccine Research
  Bohan Jiang, Paras Sheth, Baoxin Li, Huan Liu
  ICWSM 2023 Workshop

• Mechanisms and Attributes of Echo Chambers in Social Media
  Bohan Jiang, Mansooreh Karami, Lu Cheng, Tyler Black, Huan Liu
  SBP-BRiMS 2021

• Quantifying Compliance with COVID-19 Mitigation Policies in the US: A Mathematical Modeling Study
  Nao Yamamoto, Bohan Jiang, Haiyan Wang
  Infectious Disease Modelling, 2021

• MM-COVID: A Multilingual and Multimodal Data Repository for Combating COVID-19 Disinformation
  Yichuan Li, Bohan Jiang, Kai Shu, Huan Liu
  IEEE International Conference on Big Data (IEEE BigData 2020)

Patents

• Methods and Systems for Detecting Disinformation Generated by Large Language Models
  Bohan Jiang, Zhen Tan, Ayushi Nirmal, Huan Liu
  US Patent Application No. 19/326,482.