Biography

I am a Ph.D. Student in Computer Science at University of Massachusetts Boston, working under the supervision of Professor Shichao Pei. I came from an interdisciplinary background with a broad interests in physics, bio-informatics, computer science, and deep learning. Previously, I worked as a backend engineer at DeepTracer lab, where I contributed to developing machine learning approaches for automated Cryo-EM protein structure modeling under the guidance of Professor Dong Si.

Interests

  • Multimodal Knowledge Transfer,
  • Knowledge & Dataset Distillation,
  • Deep Learning for Bioinformatics.

Skills

  • Python, Java, C++, PyTorch, TensorFlow,
  • Competitive Programming (TOP 0.23%).

Education

  • Ph.D. in Computer Science • Jan 2024 - Present

    University of Massachusetts Boston

  • M.S. in Data Science • Sep 2021 - May 2023

    New York University

  • B.S. in Applied Physics • Sep 2018 - June 2021

    B.S. in ACMS: Data Sci & Stat • Sep 2018 - June 2021

    University of Washington - Seattle

Experience

 
 
 
 
 

Senior Backend Algorithm Engineer

DeepTracer

Jun 2020 – Jun 2023 Seattle, WA
Developed deep learning (DL) tool for automatic protein complex structure prediction from high-dimensional microscopy images. Researched computer vision algorithm for processing 3D biomedical image data.
 
 
 
 
 

Research Asistant

Dais Group

Sep 2020 – Nov 2020 Seattle, WA
Collaborated with T-Mobile telecom specialists and provided a solution for 5G telecom security. Investigate ML techniques for cybersecurity. Drafted review paper for key applications in cybersecurity.

Publications

Data-Free Federated Knowledge Exchange
Haowen Guan*, Xuan Zhao, Chengjie Zheng, Allen Yang, Shichao Pei
DOI PDF Code
IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2025 (Submitted)
Discovering Galaxy Features via Dataset Distillation
Haowen Guan*, Xuan Zhao, Zishi Wang, Zhiyang Li, Julia Kempe
DOI PDF Code
NeurIPS Workshop on Machine Learning and the Physical Sciences, 2023
DeepTracer-Denoising: Deep Learning for 3D Electron Density Map Denoising
Haowen Guan, Dong Si*
DOI PDF Video Website
The IEEE International Conference on Bioinformatics and Biomedicine, IEEE-BIBM, 2022
Smart de novo macromolecular structure modeling from Cryo-EM Maps
Dong Si, Jason Chen, Andrew Nakamura, Luca Chang, Haowen Guan
DOI
Journal of Molecular Biology, JMB, 2023
Artificial Intelligence Advances For De Novo Molecular Structure Modeling in Cryo-Electron Microscopy
Dong Si, Andrew Nakamura, Runbang Tan, Haowen Guan, Jie Hou, Ammaar Firozi, Renzhi Cao, Kyle Hippe, Minglei Zhao
DOI
Wiley Interdisciplinary Reviews, WIREs, 2021

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