Tao LIN

Tenure-Track Assistant Professor, PI of LINs Lab at Westlake University.

Employment

• Tenure-Track Assistant Professor (Nov. 2022 - Present)
  School of Engineering,
  Westlake University, P.R. China.

Education

• Doctor of Science (Sep. 2017 - Jul. 2022)
  School of Computer and Communication Sciences,
  École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
  

• Master of Science (Sep. 2014 - Feb. 2017)
  School of Computer and Communication Sciences,
  École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
  

• Bachelor of Engineering (with honors) (Sep. 2010 - Jun. 2014)
  College of Electrical Engineering,
  Zhejiang University (ZJU), P.R. China.

Grants

• PI: General Program of National Natural Science Foundation of China, 2026 - 2029
• Participant: Industries of the Future Research Center Funding Project, Westlake University, 2024
• PI: National Natural Science Foundation of China for Excellent Young Scientists Fund (Overseas), 2024 - 2026
• Participant (subproject leader): Science and Technology Innovation 2030 - Major Project, 12.2022 - 11.2027.
• Participant: DIGIPREDICT, EU Horizon 2020, 2021 - 2022.
• Participant: ColTraIn: Co-located DNN Training and Inference, 2017 - 2019.

Honors and awards

• ECCV Best Paper Candidate, 2024
• Recognized as one of the Top 2% Scientists Worldwide by Stanford University, 2024-2025
• Doctoral Program Thesis Distinction Award by EPFL, 2022
• Outstanding performance bonus awarded by EPFL, 2021, 2022
• Top reviewer: NeurIPS 2019 (50%), ICML 2020 (33%), AISTATS 2022 (10%)
• Teaching Assistant Award for Machine Learning Course, 2016.
• Zhejiang University Outstanding Graduates, 2014.
• 1st prize of MITSUBISHIELECTRIC Automation Competition, 2013.
• Excellent Merit Student of Zhejiang University, 2011, 2012, 2013.

Teaching

• Lecturer of Machine Learning for undergraduate students at Westlake University, Fall 2025, Spring 2025.
• Lecturer of Research Methodology of Computer Science and Technology for graduate students at Westlake University, Fall 2023-2025.
• Lecturer of Deep Learning for graduate students at Westlake University, Spring 2023-2024.
• TA of Machine Learning at EPFL, Fall 2016, Fall 2018, Fall 2020, Fall 2021.
• TA of Deep Learning at EPFL, Spring 2018, Spring 2019.
• Other TAs at EPFL: Analysis I, Fall 2019; Signals and Systems, Spring 2020; Systems for data science, Spring 2021.

Invited talks/lectures

• [Talk] Advancing Efficient Learning & Inference in Generative Models.
  机器学习与科学应用大会 CSML, August 2025
• [Talk] Collaborative Intelligence in a Dynamic World: A Small Step Towards Autonomous Evolving.
  Huawei Seminar, Sep 2024; Shanghai Chuangzhi College, Nov 2024; Xplorer Symposia, Dec 2024
• [Talk] Autonomous Evolving of Deep Neural Network Agent.
  CCF Xiuhu conference, Sep 2024
• [Talk] Towards Efficient Learning from Massive and Heterogeneous Data.
  DKU, April 2025; International Conference on Mathematical Theory of Deep Learning, August 2024; 机器学习与科学应用大会 CSML, August 2024
• [Talk] Federated Learning and Inference under Non-stationary Heterogeneous Data.
  Trustworthy FL Winter Camp 2023; School of Public Affairs @ Zhejiang University, April 2023; Hangzhou International Conference on Frontiers of Data Science, August 2023; WISE @ Westlake University, September 2023; Swarm Intelligent Unmanned Systems @ 2023 ZJU National Academic Forum for Ph.D. candidates, November 2023;
• [Lecture] Distributed Deep Learning: Introduction & Recent Advances.
  ZJU-CSE SUMMER SCHOOL on Networked Autonomous Systems, 2022.
• [Talk] Algorithms for Distributed Collaborative Learning.
  Westlake University, 2022; Hong Kong University of Science and Technology (Guangzhou), 2022.
• [Talk] Accelerating Large-scale Distributed Deep Learning Training.
  Noah's Ark Lab (Shenzhen), Huawei, 2021; The Chinese University of Hong Kong (Shenzhen), 2021; Zhejiang University, 2021; Westlake University, 2021; Alibaba DAMO Academy (Hangzhou), 2021; Sun Yat-sen University, 2021.
• [Talk] Recent Trends in Distributed Training: Sparsified, Compressed and Local SGD.
  Platform for Advanced Scientific Computing (PASC). ETH Zurich, Switzerland, 2019.

Professional services

• [Area Chair]:
  • ICLR '2026.
  • NeurIPS '2025; WANT@NeurIPS '2023.
  • WANT@ICML '2024.
• [Organizer & Panelist]:
  • Panelist, SynthData Workshop @ ICLR 2025.
• [Conference reviewer]:
  • ICML '2019-'2025;
  • NeurIPS '2019-'2024;
  • ICLR '2021-'2025;
  • AISTATS '2022-'2023; '2025;
  • CVPR '2025;
  • ICCV '2025;
  • AAAI '2020.
• [Journal reviewer]:
  • Transactions on Machine Learning Research (TMLR);
  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI);
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS);
  • ACM Computing Surveys;
  • Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT);
  • IEEE Transactions on Signal Processing (TSP).
• [Workshop reviewer]:
  • OPT '2020-'2024;
  • KDD Workshop on Federated Learning for Distributed Data Mining '2023;
  • MLSys: Federated Learning Systems Workshop '2023;
  • CLVision: Workshop on Continual Learning in Computer Vision (CVPR 2022);
  • Competition Track NeurIPS 2023.
• [Services at EPFL]:
  • [Organizing committee]: EPFL CIS EdgeAI 2022 Summer School.
  • [Admission committee]: EPFL EDIC, Fall 2022.
• [Services at Westlake University]:
  • Student Seminar Committee, since July 2023;
  • Academic Exchange Committee, since July 2023;
  • Doctoral Student Committee, since June 2024;
  • Teaching director, since Sep 2024.

Open source, outreach, and knowledge transfer

• Post-local SGD was integrated into Pytorch as a distributed optimizer.
• Interviewed by EPFL (news appeared on the EPFL front page), regarding our attempts in distributed deep learning to help industries gear up.
• Software I have contributed to which are actively maintained and ready to use:
  • DIStributed COllaborative machine learning platform for humanitarian aid: (DISCO)