Weiran Huang

Weiran Huang's Profile 

Weiran Huang (黄维然)
Associate Professor
Qing Yuan Research Institute
Shanghai Jiao Tong University

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About Me

I am an associate professor at Qing Yuan Research Institute of Shanghai Jiao Tong University, working on data-efficient machine learning algorithms and their applications. I earned my PhD in computer science from Institute for Interdisciplinary Information Sciences of Tsinghua University, where I had the honor of being supervised by Turing Award Laureate Prof. Andrew Yao and IEEE Fellow Prof. Wei Chen. Prior to that, I received my bachelor's degree in Electronic Engineering from Tsinghua University. Additionally, I was a visiting scholar hosted by Prof. Yaron Singer at Harvard SEAS.

My research interests are broadly in

  • Machine Learning Theory: This area investigates the foundational principles of machine learning, such as network capacity, optimization methods, and generalization ability. The focus is on deriving insights that can inform and improve algorithm design.

  • Self-Supervised Learning: This field aims to pre-train a powerful feature extractor through a self-supervised task using a large amount of unlabeled data, such that the learned data representations can be efficiently adapted to downstream tasks.

  • Few-Shot Learning: This branch deals with the challenge of making precise predictions in new tasks with a limited number of supervised examples. It emphasizes knowledge transfer to novel tasks with minimal data.

  • Multimodal Learning: This area is concerned with the integration and alignment of various data modalities. The primary challenges are aligning different modalities, fusing them for prediction tasks, and conducting joint training to enable knowledge transfer between modalities and their representations.

  • Continual Learning: This topic explores methods for updating models to stay current, especially focusing on large multimodal models, with a minimal training cost. The goal is to develop strategies that allow models to learn continuously and adapt efficiently to new information.

Students / Interns / Postdocs (招生)

I am actively seeking self-motivated graduate students, as well as interns and postdocs, who are interested in joining our lab.

If you're interested, please email me your CV. Before reaching out, please carefully read our latest guidelines (招生须知).

Latest News

Education & Work Experience

  • 2012–2018: PhD in Computer Science, Tsinghua University (Advisor: Andrew Yao)

  • 2009–2012: BSc in Electronic Engineering, Tsinghua University

  • 2008–2009: Fundamental Science Class (数理基科班), Tsinghua University

  • 2022/12–Present: Associate Professor at Shanghai Jiao Tong University

  • 2018/07–2022/11: Research Scientist at Huawei Noah's Ark Lab (Director: Jun Yao)

  • 2018/03–2018/06: Research Intern at Microsoft Research Asia (Mentor: Wei Chen)

  • 2017/11–2018/02: Visiting Scholar at Harvard University (Advisor: Yaron Singer)

  • 2015/08–2017/10: Research Intern at Microsoft Research Asia (Mentor: Wei Chen)

Awards & Honors

Services

  • Reviewer: ICML (2022-2024), NeurIPS (2019-2023), ICLR (2022-2024).

Sponsors

We are deeply grateful to the following sponsors for their generous support of our research, listed in no particular order.

Microsoft Research AsiaBaidu