Ameet Talwalkar
Associate Professor
Develops machine learning methods and tools for AI for science, human-AI interaction and AI agents.
Ameet Talwalkar's lab at CMU works on human-AI collaboration & trust. 25 papers since 2023, 21 at top venues, mostly TMLR and ICLR. 6 PhD students and 2 master's students. 21 alumni. Applications close .
At a glance
- papers, 2023–2026
- 7/ year
- at T1 venues
- 84%
- PhD students
- 6
- MS students
- 2
- alumni listed
- 21
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 10 papers2025 · T1 9
- 6 papers2024 · T1 6
- 9 papers2023 · T1 6
T1 venuesOtherVenues: TMLR, ICLR, AAAI, CHI, ICML
Research focuspaper titles that use each topic's words
- Human-AI collaboration & trust4 papers
- human-ai interaction0 papers
- human-ai0 papers
- tools0 papers
- develops machine0 papers
Paper list
From the lab homepage.
202510 papers
- TMLR (T1)Agreement-based Cascading for Efficient Inference (opens in a new tab)
- FSE (T1)CodingGenie: A Proactive LLM-Powered Programming Assistant (opens in a new tab)
- ICML (T1)Copilot Arena: A Platform for Code LLM Evaluation in the Wild (opens in a new tab)
- TMLR (T1)L2G: Repurposing Language Models for Genomics Tasks (opens in a new tab)
- AAAI (T1)Learning Personalized Decision Support Policies (opens in a new tab)
- CHI (T1)Need Help? Designing Proactive AI Assistants for Programming (opens in a new tab)
- ICLR (T1)Specialized Foundation Models Struggle to Beat Supervised Baselines (opens in a new tab)
- TMLR (T1)The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers (opens in a new tab)
- ICLR (T1)Understanding Optimization in Deep Learning with Central Flows (opens in a new tab)
- AAAI/ACM AIESWhy Do Decision Makers (Not) Use AI? A Cross-Domain Analysis of Factors Impacting AI Adoption (opens in a new tab)
20246 papers
- Nature Methods (T1)Applying interpretable machine learning in computational biology (opens in a new tab)
- TACL (T1)Do LLMs exhibit human-like response biases? A case study in survey design (opens in a new tab)
- ICLR (T1)Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances (opens in a new tab)
- TMLR (T1)Multitask Learning Can Improve Worst-Group Outcomes (opens in a new tab)
- AAAI (T1)On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods (opens in a new tab)
- TMLR (T1)UPS: Towards Foundation Models for PDE Solving via Cross-Modal Adaptation (opens in a new tab)
20239 papers
- ICLR (T1)AANG: Automating Auxiliary Learning (opens in a new tab)
- TMLR (T1)Assisting Human Decisions in Document Matching (opens in a new tab)
- ICML (T1)Cross-Modal Fine-Tuning: Align then Refine (opens in a new tab)
- EAAMOFeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines (opens in a new tab)
- MLSys (T1)On Noisy Evaluation in Federated Hyperparameter Tuning (opens in a new tab)
- PatternsPerspectives on Incorporating Expert Feedback into Model Updates (opens in a new tab)
- TMLR (T1)Towards a More Rigorous Science of Blindspot Discovery in Image Models (opens in a new tab)
- HCOMPWhere Does My Model Underperform? A Human Evaluation of Slice Discovery Algorithms (opens in a new tab)
- CHI (T1)Zeno: An Interactive Framework for Behavioral Evaluation of Machine Learning (opens in a new tab)
Where alumni went21 listed
Apply to CMUFall 2027
CMU SCS Computer Science PhD
- Round
- Single round
- Opens
- GRE
- See program page
- English
- TOEFL / IELTS / Duolingo (F-1/J-1 non-native speakers)
- Fee
- USD 100 (USD 80 by early deadline)
Confirmed on the program page.
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