SG NUSDepartment of Computer Science Dec 15
Works on multimodal foundation models, conversational search and recommendation, and trust and safety of AI; co-directs the NExT search centre.
2026 ADVersa: Abductive Driving Accident Video Understanding TPAMI 2026 AlphaSteer: Learning Refusal Steering with Principled Null-Space Constraint ICLR 215 T1319 papersGroup size not listed · 37 alumniUS UCLAComputer Science Dec 15
Develops natural language processing and machine learning methods, including vision-language models, robustness and fairness of language models.
2026 ARES: Adaptive Red-Teaming and End-to-End Repair of Policy-Reward System ACL 2026 ContextNav: Towards Agentic Multimodal In-Context Learning ICLR 104 T1152 papers12 members46 alumniSG NTUCollege of Computing and Data Science
Han Yu Associate Professor Works on trustworthy federated learning, ethical AI, crowdsourcing and trust management.
2026 A Black Box Optimization-based Bidding Strategy for Data Consumers in Auction-based Federated Learning KDD 2026 Adaptive guidance for local training in heterogeneous federated learning. , IEEE (2026) TPAMI 78 T1195 papers13 members15 alumniCN TsinghuaDepartment of Computer Science and Technology Feb 28
Hang Su Associate Professor Works on trustworthy and explainable AI, adversarial robustness, computer vision, and reinforcement learning.
2026 A Survey on Autonomy-Induced Security Risks in Large Model-Based Agents TPAMI 2026 AEMIM: Adversarial Examples Meet Masked Image Modeling IJCV 73 T1103 papersGroup size not listed US UWPaul G. Allen School of Computer Science & Engineering Dec 15
Studies multilingual and socially aware NLP, including fairness and safety of language models.
2026 Among Us: Measuring and Mitigating Malicious Contributions in Model Collaboration Systems ACL 2026 Cold-Start Personalization via Training-Free Priors from Structured World Models ICML 67 T189 papers10 members20 alumniCN ZhejiangSchool of Artificial Intelligence Feb 28
Researches trustworthy AI, privacy-preserving machine learning and recommender systems.
2026 Demystifying the Optimal Fair Classifier in Multi-Class Classification ICML 2026 FedAU^2: Attribute Unlearning for User-Level Federated Recommender Systems with Adaptive and Robust Adversarial Training AAAI 62 T193 papersGroup size not listed US UIUCSiebel School of Computing and Data Science Dec 1
Bo Li Abbasi Associate Professor Studies trustworthy machine learning, including adversarial robustness, privacy and safety of AI systems.
2026 Any-Depth Alignment: Unlocking Innate Safety Alignment of LLMs to Any-Depth ICLR 2026 ARMs: Adaptive Red-Teaming Agent against Multimodal Models with Plug-and-Play Attacks ICLR 61 T1102 papers11 members21 alumniUS StanfordComputer Science Dec 8
Sanmi Koyejo Associate Professor of Computer Science Studies trustworthy machine learning, including evaluation, robustness and fairness of AI models.
2026 AbdCTBench: Learning Clinical Biomarker Representations from Abdominal Surface Geometry ICLR 2026 Distributional Machine Unlearning via Selective Data Removal ICLR 58 T1102 papersGroup size not listed US CMUMachine Learning Department Dec 9
Steven Wu Associate Professor Studies trustworthy machine learning, including privacy, AI safety, interactive learning and reinforcement learning.
2026 All Roads Lead to Likelihood: The Value of Reinforcement Learning in Fine-Tuning ICLR 2026 Back to Blackwell: Closing the Loop on Intransitivity in Multi-Objective Preference Fine-Tuning NeurIPS 52 T171 papers8 members16 alumniUS UIUCSiebel School of Computing and Data Science Dec 1
Han Zhao Assistant Professor Studies trustworthy machine learning, including fairness, domain adaptation and alignment of large language models.
2026 ACTG-ARL: Differentially Private Conditional Text Generation with RL-Boosted Control ICML 2026 Can VLMs Reason Robustly? A Neuro-Symbolic Investigation TMLR 50 T161 papers7 members14 alumniCN ZhejiangCollege of Computer Science and Technology Feb 28
Works on large language models and representation learning, including white-box hallucination detection, demonstration validation for in-context learning…
2026 An Invariant Latent Space Perspective on Language Model Inversion AAAI 2026 KMLP: A Scalable Hybrid Architecture for Web-Scale Tabular Data Modeling WWW 47 T164 papersGroup size not listed US UMDComputer Science
Leads the Reliable AI Lab, studying robustness, interpretability and detection of AI-generated content in deep learning models.
2026 GHOST: Hallucination-Inducing Image Generation for Multimodal LLMs ICLR 2026 Revisiting the Past: Data Unlearning with Model State History ICLR 41 T159 papers12 members13 alumniCN SJTUSchool of Computer Science May 31
Works on natural language processing, AI agents and agent safety.
2026 Agent-Dice: Disentangling Knowledge Updates via Geometric Consensus for Agent Continual Learning ACL 2026 An LLM-based Quantitative Framework for Evaluating High-Stealthy Backdoor Risks in OSS Supply Chains AAAI 35 T142 papers14 members7 alumniUS UIUCElectrical and Computer Engineering Dec 1
Studies trustworthy machine learning, including formal verification of neural networks and AI safety and robustness.
2026 BEAT: Visual Backdoor Attacks on VLM-based Embodied Agents via Contrastive Trigger Learning ICLR 2026 DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty ICLR 34 T137 papers14 members4 alumniUS MichiganComputer Science and Engineering Dec 15
Lu Wang Associate Professor, EECS – Computer Science and Engineering Studies natural language processing, including text summarization, trustworthy and safe language models and AI evaluation.
2026 AdaMEM: Test-Time Adaptive Memory for Language Agents ICML 2026 CASPER in the Machine: Insights into Character Variety in LLM-Generated Stories ACL 34 T160 papers7 members17 alumniUS UCSDHalıcıoğlu Data Science Institute Dec 15
Studies robustness, interpretability and safety of deep neural networks, including certified robustness and automated neuron explanation.
2026 Beyond Top Activations: Efficient and Reliable Crowdsourced Evaluation of Automated Interpretability CVPR 2026 CI-CBM: Class-Incremental Concept Bottleneck Model for Interpretable Continual Learning TMLR 32 T143 papers6 members4 alumniCN PekingInstitute for Artificial Intelligence Jan 15
Researches machine learning, neuro-symbolic integration and reinforcement learning with interpretable model representations.
2026 Can Language Models Discover Scaling Laws? ICLR 2026 CREATE: Cross-Layer Resilience Characterization and Optimization for Efficient yet Reliable Embodied AI Systems ASPLOS 32 T146 papersGroup size not listed US NYUComputer Science (Courant) Dec 12
He He Associate Professor of Computer Science and Data Science Studies natural language processing and machine learning, focusing on robustness, reasoning and the trustworthiness of language models.
2026 Estimating Tail Risks in Language Model Output Distributions ICML 2026 Is It Thinking or Cheating? Detecting Implicit Reward Hacking by Measuring Reasoning Effort ICLR 27 T139 papers8 members14 alumniUS UMDComputer Science
Studies question answering, human-computer cooperation in language tasks and topic models, including adversarial quiz-bowl evaluation of AI.
2026 BenchMarker: An Education-Inspired Toolkit for Highlighting Flaws in Multiple-Choice Benchmarks ACL 2026 Check The Scoreboard: An Analysis of Scoring Schemes on Multiple-Choice Evaluation EMNLP 27 T149 papers12 members43 alumniUS UMDComputer Science
Studies large language models for long-context understanding, long-form generation evaluation, factuality and literary translation.
2026 AI use in American newspapers is widespread, uneven, and rarely disclosed ACL 2026 Argument Collapse: LLMs Flatten Long-Form Public Debate EMNLP 25 T147 papers9 members13 alumni