Chinmay Hegde
Associate Professor
Studies machine learning, including robust and reliable deep learning, generative models and AI for scientific and engineering design.
Chinmay Hegde's lab at NYU works on trustworthy & safe ML and generative & foundation models. 59 papers since 2023, 17 at top venues, mostly ICLR and NeurIPS. Applications close .
At a glance
- papers, 2023–2026
- 15/ year
- at T1 venues
- 29%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 10 papers2026 · T1 3 · collecting
- 19 papers2025 · T1 6
- 19 papers2024 · T1 5
- 11 papers2023 · T1 3
T1 venuesOtherVenues: ICLR, NeurIPS, COLT, TMLR, AISTATS
Research focuspaper titles that use each topic's words
- Generative & foundation models19 papers
- Trustworthy & safe ML0 papers
- engineering design0 papers
- reliable0 papers
- tandon0 papers
Paper list
From the lab homepage.
202610 papers
- AAAI WorkshopBenchmarking Tabular Foundation Models for Agricultural Yield Prediction (opens in a new tab)
- Conference on Language ModelingBreak Me If You Can: Self-Jailbreaking of Aligned LLMs via Lexical Insertion Prompting (opens in a new tab)
- International Conference on LLM-Aided DesignCRAFT: Corrective and Robust Multi-Agent Framework for Text-to-Parametric CAD (opens in a new tab)
- CVPR Biometrics WorkshopDiffClean: Diffusion-based Makeup Removal for Accurate Age Estimation (opens in a new tab)
- CVPR WorkshopFPBench: A Comprehensive Benchmark of Multimodal Large Language Models for Fingerprint Analysis (opens in a new tab)
- NeurIPS WorkshopLea: An Agent Backbone for Mathematician-Controlled Formalization in Lean (opens in a new tab)
- NeurIPS (T1)Learning to Reason with Adaptive Rationale Scaffolding (opens in a new tab)
- ACL WorkshopMulti-Turn Jailbreaking of Aligned LLMs via Lexical Anchor Tree Search (opens in a new tab)
- ICLR (T1)OpenThoughts: Data Recipes for Reasoning Models (opens in a new tab)
- COLT (T1)Query Efficient Structured Matrix Learning (opens in a new tab)
202519 papers
- AAAI WorkshopBioTrove: A Large Curated Image Dataset Enabling AI for Biodiversity (opens in a new tab)
- Asilomar Conference on Signals, Systems, and ComputersDiscovering Sparse Recovery Algorithms Using Neural Architecture Search (opens in a new tab)
- Asilomar Conference on Signals, Systems, and ComputersEfficient Methods for Modeling Shift-Varying Operators (opens in a new tab)
- IEEE International Conference on Automatic Face and Gesture RecognitionFaceCloak: Learning to Protect Face Templates (opens in a new tab)
- Journal of Data-Centric Machine Learning ResearchFlowBench: A Large Scale Benchmark for Flow Simulation over Complex Geometries (opens in a new tab)
- IEEE Conference on Big DataFoundation Model Efficient Fine-Tuning in Centralized and Federated Settings (opens in a new tab)
- Nature Communications EngineeringGeometry Matters: Benchmarking Scientific ML Approaches for Flow Prediction around Complex Geometries (opens in a new tab)
- ICLR (T1)Hidden in the Noise: Two-Stage Robust Watermarking for Images (opens in a new tab)
- WACVLeveraging Vision Language Models for Specialized Agricultural Tasks (opens in a new tab)
- ICLR (T1)LiveBench: A Challenging, Contamination-Free LLM Benchmark (opens in a new tab)
- ACM Conference on AI and Agentic SystemsMARVIS: Modality Adaptive Reasoning over VISualizations (opens in a new tab)
- Journal of Data-Centric Machine Learning ResearchMPFBench: A Large Scale Dataset for SciML of Multi-Phase Flows: Droplet and Bubble Dynamics (opens in a new tab)
202419 papers
- COLT (T1)Agnostic Active Learning of Single Index Models with Linear Sample Complexity (opens in a new tab)
- International Conference on Very Large DatabasesArcheType: Open-Source Column Type Annotation Using Large Language Models (opens in a new tab)
- Neural Information Processing Systems Datasets and BenchmarksBioTrove: A Large Multimodal Dataset Enabling AI for Biodiversity (opens in a new tab)
- ICLR (T1)Circumventing Concept Erasure Methods for Text-to-Image Generative Models (opens in a new tab)
- CVPR (T1)DIMAT: Decentralized Iterative Merging-And-Training for Deep Learning Models (opens in a new tab)
- IEEE Workshop on LLM-Aided DesignEvaluating Large Language Models for G-Code Debugging, Manipulation, and Comprehension (opens in a new tab)
- IEEE Conference on Secure and Trustworthy Machine LearningFast Certification of Vision-Language Models Using Incremental Randomized Smoothing (opens in a new tab)
- IEEE European Symposium on Security and PrivacyGotcha: Real-Time Video Deepfake Detection via Challenge-Response (opens in a new tab)
- IEEE Transactions on Biometrics, Behavior, and Identity ScienceIdentity-Preserving Aging of Face Images via Latent Diffusion Models (opens in a new tab)
- International Joint Conference on BiometricsMitigating the Impact of Attribute Editing on Face Recognition (opens in a new tab)
- Engineering with ComputersNeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs (opens in a new tab)
- Computer-Aided DesignNeural PDE Solvers for Irregular Domains (opens in a new tab)
202311 papers
- CVPR WorkshopA Few Adversarial Tokens Can Break Vision Transformers (opens in a new tab)
- AISTATS (T1)Active Learning for Single Neuron Models with Lipschitz Non-Linearities (opens in a new tab)
- TMLR (T1)Distributionally Robust Classification on A Data Budget (opens in a new tab)
- NeurIPS WorkshopExploring Dataset-Scale Indicators of Data Quality (opens in a new tab)
- ICLR (T1)Implicit Regularization for Group Sparsity (opens in a new tab)
- NeurIPS WorkshopImproved Bounds for Agnostic Active Learning of Single Index Models (opens in a new tab)
- AAAI WorkshopLiT Tuned Models for Efficient Species Detection (opens in a new tab)
- International Conference on Algorithmic Learning TheoryOn The Computational Complexity of Self-Attention (opens in a new tab)
- NeurIPS WorkshopOn The Fine-Grained Hardness of Inverting Generative Models (opens in a new tab)
- NeurIPS WorkshopScaling TabPFN: Sketching and Feature Selection for Tabular Prior-Data Fitted Networks (opens in a new tab)
- Neural Information Processing Systems Track on Datasets and BenchmarksWhen Do Neural Nets Outperform Boosted Trees on Tabular Data? (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to NYUFall 2027
Computer Science PhD (Courant / Tandon)
- Round
- Single round (December)
- Opens
- —
- GRE
- See program page
- English
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- Fee
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Not yet confirmed for this intake.
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