Tieliang Gong

About Me

I am an Associate Professor at the School of Computer Science and Technology at Xi’an Jiaotong University. My students and I are part of the Shaanxi Key Lab of BDKE. Our research is funded by the National Key Research Development Program of China and the National Natural Science Foundation.

I have previously held positions as a postdoctoral researcher at the University of Ottawa and as a visiting scholar at the University of Michigan, Ann Arbor. I obtained my Ph.D in Applied Mathematics from Xi’an Jiaotong University, where I was fortunate to be advised by Prof. Zongben Xu, an esteemed Academician of the Chinese Academy of Sciences.

I am open to exploring any potential collaboration opportunities. Please let me know if you’d like to collaborate, especially if you’re interested in information theoretical learning issues.

Research

My research interests mainly include statistical learning theory and information theory. My goal is to develop the foundational theory that guides the design of computationally efficient machine learning algorithms that do not cause degradation. Recently, my research revolves around some critical challenges in big data analysis within the information theoretical learning framework, including but not limited to conducting generalization analysis for deep learning algorithms, disclosing the intrinsic factors for transfer learning and contrastive learning. Also, I explore potential applications of these theoretical advances in AI4Science.

Recruiting

I am looking for highly motivated and self-driven students, who are interested in

• Robust/Explainable machine learning, especially on coreset selection, subsampling, random sketching etc.
• Generalization of DNNs, aims to open the black-box of deep learning. Theoretical investigation including complexity analysis,stability analysis, NTK, SGD/SGLD analysis etc.
• Transfer learning, including out-of-distribution generalization/Detection within the information- theoretical learning framework.
• AI for Medical, especially on pathology image analysis and related topics on XAI for Medical.

People

• Formal doctoral students:
  Zeyu Gao (Next position – University of Cambridge)
  Kai He (Next position – National University of Singapore)
  Yuxin Dong (Next position – Ohio State University)
  Jialun Wu (Next position – Northwestern Polytechnical University)
  
• Current Ph.D. students:
  Wen Wen
  Xinmeng Zuo
  
• Current Master students:
  Zeyang Zhang
  Haoyang Zhang
  Ying Huang
  Huiting Huang
  Qi Kong
  Yanan Chen
  Zhongbo Zhang
  Longteng Li
  

Recent news and activities

• [Oct. 2024] One paper (about multi-instance learning for WSI classification) has been accepted to IEEE TMI.
• [Sep. 2024] Two papers (about Non-Maximum Suppression and diffusion model) have been accepted to NeurIPS.
• [May. 2024] One paper (about high-order contrastive learning) has been accepted to ICML.
• [Apr. 2024] Two papers (about Stocastic Bi-level optimization and adversarial contrastive learning) have been accepted to IJCAI.
• [Feb. 2024] Our paper about information theoretical analysis on pairwise learning has been accepted to ICLR.
• [Feb.2024] Our paper about multi-instance learning has been accepted to CVPR 2024.
• [Aug. 2023] I will be the Machine Learning Session Chair of IJCAI in MACAO!
• [Mar. 2023] I have been invited to give a talk at The Second Symposium on Mathematical Technology and New Generation Communication Technology!

Publications

Services

Conference Reviewers

• International Conference on Machine Learning (ICML)
• Conference on Neural Information Processing Systems (NeurIPS)
• International Conference on Learning Representation (ICLR)
• Artificial Intelligence and Statstics (AISTATS)
• AAAI Conference on Aritificial Intelligence (AAAI)
• International Joint Conference on Artificial Intelligence (IJCAI)

Journal Reviewers

• Journal of Machine Learning Research (JMLR)
• IEEE Transactions on Information Theory (IEEE TIT)
• IEEE Transactions on Signal Processing (IEEE TSP)
• IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS)
• IEEE Transactions on Cybernetics (IEEE TCYB)
• IEEE Transactions on Medical Imaging (IEEE TMI)
• IEEE Journal of Biomedical and Health Informatics (IEEE JBHI)
• Neural Computation
• Machine Learning
• Pattern Recognition
• Expert Systems with Applications
• Neurocomputing