Long-Kai Huang

Google Scholar  /  Email: longkai [AT] comp.hkbu.edu.hk

I am an Assistant Professor with Department of Computer Science at Hong Kong Baptist University.

Previously, I was a Senior Research at Tencent AI Lab. I received my Ph.D. in Computer Science and Engineering from Nanyang Technological University (NTU) Singapore, supervised by Prof. Sinno Jialin Pan, and B.Eng. in Automation from Sun Yat-Sen University, where I did my undergraduate thesis under the supervision of Prof. Wei-Shi Zheng.

My research centers on the theory and applications of machine learning, with emphasis on continual learning, meta-learning, and efficient pre-training and post-training of LLMs. I am also interested in AI for science, especially drug discovery, protein design, and single-cell omics.

[Updates at Feb 2026] One open Ph.D. position for Fall 2026 . If you are interested in working with me on related research topics, please email me your CV and undergraduate transcript. I am also looking for RAs to work on machine learning and AI for scientific discovery.

News
•

[Feb 2026]

One paper accepted by Nature Communication.
•

[Dec 2025]

One paper accepted by nBME. One paper accepted by Nature Communication.
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[Sep 2025]

One papers is accepted to NeurIPS 2025
•

[May 2025]

Two papers are accepted at ICML 2025!
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[Jan 2025]

Three papers are accepted to ICLR 2025, including one oral presentation!
•

[Sep 2024]

Two papers are accepted to NeurIPS 2024, including one spotlight presentation.
•

[May 2024]

Honored to receive the ICLR 2024 Outstanding Paper Award Honorable Mention!

Publications |

Publications by Topic

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Google Scholar

* indicates equal contributions; † indicates corresponding authors.

Conference Papers
29.

Model Editing for Vision Transformers


Xinyi Huang, Kangfei Zhao, Long-Kai Huang†
In Advances in Neural Information Processing Systems (NeurIPS) , 2025
28.

Steering Protein Language Models


Long-Kai Huang, Rongyi Zhu, Bing He, Jianhua Yao
In International Conference on Machine Learning (ICML) , 2025
27.

IBCircuit: Towards Holistic Circuit Discovery with Information Bottleneck


Tian Bian, Yifan Niu, Chaohao Yuan, Chengzhi Piao, Bingzhe Wu, Long-Kai Huang, Yu Rong, Tingyang Xu, Hong Cheng, Jia Li
In International Conference on Machine Learning (ICML) , 2025
26.

SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning


Yichen Wu*, Hongming Piao*, Long-Kai Huang†, Renzhen Wang, Wanhua Li, Hanspeter Pfister, Deyu Meng, Kede Ma†, Ying Wei†
In International Conference on Learning Representations (ICLR) , 2025
25.

Parameter and Memory Efficient Pretraining via Low-rank Riemannian Optimization


Zhanfeng Mo, Long-Kai Huang, Sinno Jialin Pan
In International Conference on Learning Representations (ICLR) , 2025
24.

Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation


Yikun Zhang, Geyan Ye, Chaohao Yuan, Bo Han, Long-Kai Huang, Jianhua Yao, Wei Liu, Yu Rong
In International Conference on Learning Representations (ICLR) , 2025
23.

Spurious Feature Eraser: Stabilizing Test-Time Adaptation for Vision-Language Foundation Model


Huan Ma, Yan Zhu, Changqing Zhang, Peilin Zhao, Baoyuan Wu, Long-Kai Huang, Qinghua Hu, Bingzhe Wu
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) , 2025
22.

Annotation-guided protein design with multi-level domain alignment


Chaohao Yuan, Songyou Li, Geyan Ye, Yikun Zhang, Long-Kai Huang, Wenbing Huang, Wei Liu, Jianhua Yao, Yu Rong
In Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data (KDD) , 2025
21.

Learning Where to Edit Vision Transformers


Yunqiao Yang, Long-Kai Huang†, Shengzhuang Chen, Kede Ma, Ying Wei†
In Advances in Neural Information Processing Systems (NeurIPS) , 2024
20.

Towards Understanding Evolving Patterns in Sequential Data


Qiuhao Zeng, Long-Kai Huang, Xi Chen, Charles Ling, Boyu Wang
In Advances in Neural Information Processing Systems (NeurIPS) , 2024
19.

Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations Via Pareto Optimization


Yichen Wu*, Hong Wang*, Peilin Zhao, Yefeng Zheng, Ying Wei†, Long-Kai Huang†
In International Conference on Machine Learning (ICML) , 2024
18.

Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction


Yichen Wu, Long-Kai Huang†, Renzhen Wang, Deyu Meng, Ying Wei†
In International Conference on Learning Representations (ICLR) , 2024
17.

Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time


Qiuhao Zeng, Changjian Shui, Long-Kai Huang, Peng Liu, Xi Chen, Charles Ling, Boyu Wang
In International Conference on Learning Representations (ICLR) , 2024
16.

Retaining Beneficial Information from Detrimental Data for Neural Network Repair


Long-Kai Huang, Peilin Zhao, Junzhou Huang, Sinno Jialin Pan
In Neural Information Processing Systems (NeurIPS) , 2023
15.

Secure Out-of-Distribution Task Generalization with Energy-Based Models


Shengzhuang Chen, Long-Kai Huang, Jonathan Richard Schwarz, Yilun Du, Ying Wei
In Neural Information Processing Systems (NeurIPS) , 2023
14.

Concept-wise Fine-tuning Matters in Preventing Negative Transfer


Yunqiao Yang, Long-Kai Huang, Ying Wei
In International Conference on Computer Vision (ICCV) , 2023
13.

DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery–a Focus on Affinity Prediction Problems with Noise Annotation


Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Lanqing Li, Long-Kai Huang, Tingyang Xu, Yu Rong, Jie Ren, Ding Xue, Houtim Lai, Wei Liu, Junzhou Huang, Shuigeng Zhou, Ping Luo, Peilin Zhao, Yatao Bian
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) , 2023
12.

Improving Task-Specific Generalization in Few-Shot Learning via Adaptive Vicinal Risk Minimization


Long-Kai Huang, Ying Wei
In Neural Information Processing Systems (NeurIPS) , 2022
11.

Adversarial Task Up-sampling for Meta-learning


Yichen Wu, Long-Kai Huang†, Ying Wei†
In Neural Information Processing Systems (NeurIPS) , 2022
10.

Frustratingly Easy Transferability Estimation


Long-Kai Huang , Junzhou Huang, Yu Rong, Qiang Yang, Ying Wei
In International Conference on Machine Learning (ICML) , 2022
9.

Fine-Tuning Graph Neural Networks via Graph Topology Induced Optimal Transport


Jiying Zhang, Xi Xiao, Long-Kai Huang, Yu Rong, Yatao Bian
In International Joint Conference on Artificial Intelligence (IJCAI) , 2022
8.

Functionally Regionalized Knowledge Transfer for Low-Resource Drug Discovery


Huaxiu Yao, Ying Wei, Long-Kai Huang, Ding Xue, Junzhou Huang, Zhenhui Jessie Li
In Neural Information Processing Systems (NeurIPS) , 2021
7.

Improving Generalization in Meta-learning via Task Augmentation


Huaxiu Yao*, Long-Kai Huang*, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui Li
In International Conference on Machine Learning (ICML) , 2021
6.

Communication-Efficient Distributed PCA by Riemannian Optimization


Long-Kai Huang*, Sinno Jialin Pan
In International Conference on Machine Learning (ICML) , 2020
5.

Accelerate Learning of Deep Hashing With Gradient Attention


Long-Kai Huang, Jianda Chen, Sinno Jialin Pan
In International Conference on Computer Vision (ICCV) , 2019
4.

Recurrent Knowledge Graph Embedding for Effective Recommendation


Zhu Sun, Jie Yang, Jie Zhang, Alessandro Bozzon, Long-Kai Huang, Chi Xu
In ACM Conference on Recommender Systems () (RecSys) , 2018
3.

Class-Wise Supervised Hashing with Label Embedding and Active Bits


Long-Kai Huang, Sinno Jialin Pan
In International Joint Conference on Artificial Intelligence (IJCAI) , 2016
2.

Online Hashing


Long-Kai Huang, Qiang Yang, Wei-Shi Zheng
In International Joint Conference on Artificial Intelligence (IJCAI) , 2013
1.

Smart Hashing Update for Fast Response


Qiang Yang, Long-Kai Huang, Wei-Shi Zheng
In International Joint Conference on Artificial Intelligence (IJCAI) , 2013

Journal Papers
8.

Functional Protein Design and Enhancement with Ontology Reinforcement Iteration


Bing He*, Chenchen Qin*, Yu Zhao*, Long-Kai Huang*, Zihan Wu, Fang Wang, Fandi Wu, Fan Yang, Jianhua Yao
In Nature Communication (NC) , 2026
7.

De Novo Design of Epitope-specific Antibodies via a Structure-driven Computational Workflow


Fandi Wu, Yu Zhao, JiaXiang Wu, Biaobin Jiang, Bing He, Long-Kai Huang, and other 17 authors.
In Nature Communication (NC) , 2025
6.

A Pre-trained Large Generative Model for Translating Single-cell Transcriptomes to Proteomes


Linjing Liu, Wei Li, Fang Wang, Yiming Li, Long-Kai Huang, Ka-Chun Wong, Fan Yang, Jianhua Yao.
In Nature Biomedical Engineering (nBME) , 2025
5.

Reply to: Deeper evaluation of a single-cell foundation model


Fang Yang, Fan Wang, Long-Kai Huang, Linjing Liu, Junzhou Huang, Jianhua Yao.
In Nature Machine Intelligence (NMI) , 2024
4.

Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation


Shuang Zhou, Xiao Huang, Ninghao Liu, Huachi Zhou, Fu-Lai Chung, Long-Kai Huang†
In IEEE Transactions on Knowledge and Data Engineering (TKDE) , 2023
3.

Deep Domain Adversarial Neural Network for the Deconvolution of Cell Type Mixtures in Tissue Proteome Profiling


Fang Wang*, Fan Yang*, Long-Kai Huang, Jiangning Song, Jiang Qian, Guohua Wang, Jianhua Yao.
In Nature Machine Intelligence (NMI) , 2023
2.

A Fast Online Spherical Hashing Method Based on Data Sampling for Large Scale Image Retrieval


Zhenyu Weng, Yuesheng Zhu, Yinhe Lan, Long-Kai Huang
In Neurocomputing , 2019
1.

Online Hashing


Long-Kai Huang, Qiang Yang, Wei-Shi Zheng
In IEEE Transactions on Neural Networks and Learning Systems (TNNLS) , 2017

Awards
• ICLR 2024 Outstanding Paper Award Honorable Mention
• ICLR 2024 Outstanding Reviewer

Services
• Area Chair: ICML2026, ICLR2025
• Senior Meta Reviewer: ICME2026, PRCV2025

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