Heng Huang
Professor
Develops machine learning, large-scale optimization and AI methods for biomedical data science and computational health.
Heng Huang's lab at UMD works on learning theory & optimization, medical image analysis and data management & big data. 141 papers since 2023, 117 at top venues, mostly ICLR and ICML.
At a glance
- papers, 2023–2026
- 37/ year
- at T1 venues
- 83%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 17 papers2026 · T1 16 · collecting
- 40 papers2025 · T1 32
- 50 papers2024 · T1 43
- 34 papers2023 · T1 26
T1 venuesOtherVenues: ICLR, ICML, NeurIPS, CVPR, AAAI
Research focuspaper titles that use each topic's words
- Learning theory & optimization47 papers
- Medical image analysis9 papers
- Data management & big data8 papers
- computational health0 papers
- biomedical data0 papers
Paper list
From the lab homepage.
202617 papers
- ICLR (T1)An Ensemble Framework for Unbiased Language ModelWatermarking
- ICLR (T1)Analyzing and Evaluating Unbiased Language Model Watermark
- ICML (T1)Beyond Buffer Limits: Energy-Based Data Reassembly for Continual Learning
- ICLR (T1)Catalog-Native LLM: Speaking Item-ID dialect with Less Entanglement for Recommendation
- ISBICRESTomics: Analyzing Carotid Plaques in the CREST-2 Trial with a New Additive Classification Model
- ICML (T1)Distributed Stochastic K-Level Optimization Over Networks
- ICML (T1)Hidden in Plain Tokens: Simply Robust, Gradient-Free Watermark for Synthetic Audio
- ICLR (T1)Learning to Reason via Mixture-of-Thought for Logical Reasoning
- CVPR (T1)Multi-Crit: Benchmarking Multimodal Judges on Pluralistic Criteria-Following
- ICLR (T1)New Hybrid Fine-Tuning Paradigm for LLMs: Algorithm Design and Convergence Analysis Framework
- ICML (T1)Parallel-Probe: Towards Efficient Parallel Thinking via 2D Probing
- ICLR (T1)Parallel-R1: Towards Parallel Thinking via Reinforcement Learning
202540 papers
- TPAMI (T1)A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
- Interspeech (T1)A Watermark for Auto-Regressive Speech Generation Models
- ICLR (T1)A Watermark for Order-Agnostic Language Models
- HERMESAgentic AI/CREATE/Clinical MLLMs@MICCAI
- TMLR (T1)AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving
- NeurIPS (T1)Bilevel ZOFO: Efficient LLM Fine-Tuning and Meta-Training
- Neural NetworksBPEN: Brain Posterior Evidential Network for trustworthy brain imaging analysis
- the ACM International Conference on Bioinformatics, Computational Biology, and Health InformaticsCharacterizing Amyloid Pathogenic Spread in Alzheimer's Disease Through A Network Diffusion Model
- NeurIPS (T1)Cost-Aware Contrastive Routing for LLMs
- ICML (T1)De-mark: Watermark Removal in Large Language Models
- CVPR (T1)Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models
- BioinformaticsEnhancing privacy in biosecurity with watermarked protein design
202450 papers
- EMNLP (T1)A Bayesian Approach to Harnessing the Power of LLMs in Authorship Attribution
- TPAMI (T1)A Bayesian Federated Learning Framework With Online Laplace Approximation
- ICML (T1)A Resilient and Accessible Distribution-Preserving Watermark for Large Language Models
- ICLR (T1)A Unified and General Framework for Continual Learning
- Nature Communications (T1)A unified model-based framework for doublet or multiplet detection in single-cell multiomics data
- ICML (T1)Accelerated Policy Gradient for s-rectangular Robust MDPs with Large State Spaces
- ICML (T1)Accelerated Speculative Sampling Based on Tree Monte Carlo
- AAAI (T1)Adversarial Fairness Network
- ICLR (T1)Alpagasus: Training a Better Alpaca Model with Fewer Data
- TNNLS (T1)Asynchronous Parallel Large-Scale Gaussian Process Regression
- CVPR (T1)Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch
- CVPR (T1)BilevelPruning: Unified Dynamic and Static Channel Pruning for Convolutional Neural Networks
202334 papers
- Computers in Biology and MedicineA convolutional neural network with pixel-wise sparse graph reasoning for COVID-19 lesion segmentation in CT images
- ICML (T1)A Law of Robustness beyond Isoperimetry
- Machine LearningA new large-scale learning algorithm for generalized additive models
- TIP (T1)Adaptive Hierarchical Similarity Metric Learning With Noisy Labels
- AAAI (T1)Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks
- ICML (T1)Beyond Lipschitz Smoothness: A Tighter Analysis for Nonconvex Optimization
- MICCAI (T1)Bidirectional Mapping with Contrastive Learning on Multimodal Neuroimaging Data
- NeurIPS (T1)Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems
- CVPR (T1)Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets
- AAAI (T1)Decentralized Riemannian Algorithm for Nonconvex Minimax Problems
- IEEE Transitions on MultimediaDecompose to Adapt: Cross-Domain Object Detection Via Feature Disentanglement
- NeurIPS (T1)Domain Watermark: Effective and Harmless Dataset Copyright Protection is Closed at Hand
Where alumni went
Alumni are not listed on the lab homepage.
Apply to UMDFall 2027
Not announced yet
UMD Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
Similar labsnearest by research summary
- USNYU
Christopher Musco
- Data management & big data
- CNSJTU
Ruidan Su
0 T1 - DETUM
Reinhard Heckel
- Signal processing & information theory
- USNYU
Julia Kempe
- Trustworthy & safe ML
- USCMU
Zachary C. Lipton
- Trustworthy & safe ML
- GBEdinburgh
Christopher Lucas
7 T1
Your notes
Save this lab to keep notes.
Data
Some numbers could not be verified:
- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Not collected
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.