Manish Raghavan
Drew Houston Career Development (2005) Professor; Assistant Professor
Applies computational techniques to social concerns, including algorithmic fairness, online platforms, and behavioral economics.
Manish Raghavan's lab at MIT works on trustworthy & safe ML, reasoning & neuro-symbolic AI and computational social science. 27 papers since 2023, 18 at top venues, mostly NeurIPS and WWW. 4 PhD students. 3 alumni. Applications close .
At a glance
- papers, 2023–2026
- 7/ year
- at T1 venues
- 67%
- PhD students
- 4
- MS students
- 0
- alumni listed
- 3
Papers by yearfrom the lab homepage, 2023–2026
- 9 papers2026 · T1 7 · collecting
- 6 papers2025 · T1 3
- 6 papers2024 · T1 4
- 6 papers2023 · T1 4
T1 venuesOtherVenues: NeurIPS, WWW, ICML, Management Science, EC
Research focuspaper titles that use each topic's words
- Trustworthy & safe ML2 papers
- Reasoning & neuro-symbolic AI0 papers
- Computational social science0 papers
- platforms0 papers
- algorithmic fairness0 papers
Paper list
From the lab homepage.
20269 papers
- Philosophical Perspectives, SeptemberAlgorithmic Monoculture and its Critics (opens in a new tab)
- Management Science (T1)Competition and Diversity in Generative AI (opens in a new tab)
- NeurIPS (T1)Hitting a Moving Target: Test-Time Adaptation for AI Text Detection under Continual Distribution Shift (opens in a new tab)
- NeurIPS (T1)Impacts of Aggregation on Model Diversity and Consumer Utility (opens in a new tab)
- ICLR (T1)Statistical Guarantees in the Search for Less Discriminatory Algorithms (opens in a new tab)
- ICML (T1)Strategic Candidacy in Generative AI Arenas (opens in a new tab)
- NeurIPS (T1)The Subjectivity of Monoculture (opens in a new tab)
- TMLR (T1)Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models (opens in a new tab)
- FORCWhen to Ask a Question: Understanding Communication Strategies in Generative AI Tools (opens in a new tab)
20256 papers
- ICML (T1)Double Machine Learning for Causal Inference under Shared-State Interference (opens in a new tab)
- NeurIPS (T1)Evaluating multiple models using labeled and unlabeled data (opens in a new tab)
- ACM Symposium on CS and LawEvaluating the Impacts of Swapping on the US Decennial Census (opens in a new tab)
- NeurIPS (T1)Homogeneous Algorithms Can Reduce Competition in Personalized Pricing (opens in a new tab)
- Journal of Privacy and Confidentiality, AugustSynthetic Census Data Generation via Multidimensional Multiset Sum (opens in a new tab)
- ACM Symposium on CS and LawWhat Constitutes a Less Discriminatory Algorithm? (opens in a new tab)
20246 papers
- WWW (T1)Content Moderation and the Formation of Online Communities: A Theoretical Framework (opens in a new tab)
- EC (T1)Equilibria, Efficiency, and Inequality in Network Formation for Hiring and Opportunity (opens in a new tab)
- NeurIPS (T1)Human Expertise in Algorithmic Prediction (opens in a new tab)
- Georgetown Law Technology Review, JanuaryLimitations of the “Four-Fifths Rule” and Statistical Parity Tests for Measuring Fairness (opens in a new tab)
- WWW (T1)Reconciling the accuracy-diversity trade-off in recommendations (opens in a new tab)
- Communications of the ACM, JanuaryWhat Should We Do when Our Ideas of Fairness Conflict? (opens in a new tab)
20236 papers
- NeurIPS (T1)Auditing for Human Expertise (opens in a new tab)
- SIAM Journal on Computing (T1)Greedy Algorithm almost Dominates in Smoothed Contextual Bandits (opens in a new tab)
- Nature Human Behaviour, NovemberHuman bias in algorithm design (opens in a new tab)
- WWW (T1)Simplistic Collection and Labeling Practices Limit the Utility of Benchmark Datasets for Twitter Bot Detection (opens in a new tab)
- Management Science (T1)The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization (opens in a new tab)
- Perspectives on Psychological Science, DecemberThe Inversion Problem: Why Algorithms Should Infer Mental State and Not Just Predict Behavior (opens in a new tab)
Where alumni went3 listed
Apply to MITFall 2027
MIT EECS Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
- TOEFL/IELTS
- Fee
- USD 90
Confirmed on the program page.
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