Taihui Li
Ph.D. Student
Department of Computer Science & Engineering
University of Minnesota
Contact: Email, Google Scholar, Github, Linkedin
I am a Ph.D. student in Computer Science & Engineering at University of Minnesota, Twin Cities. I am fortunate to be advised by Prof. Ju Sun and Prof. Vladimir Cherkassky. Simultaneously, I am pursuing a minor degree (doctoral) in Health Informatics. Before starting my Ph.D. study, I obtained my Master's and Bachelor's degree in Computer Science at Jilin University where I was advised by Prof. Liang Hu.
I am interested in machine learning, deep learning, computer vision, data analytics, and general applications of machine learning/deep learning in healthcare and medical settings.
News
2023-12: Our paper collaborated with Sony Corporation of America has been accepted to ICASSP2024.
2023-09: I am thrilled to join PureBiox as a research intern in Computer Vision this Fall.
2023-09: Our paper Joint Demosaicing and Denoising with Double Deep Image Priors collaborated with Sony Corporation of America is available on arXiv.
2023-05: I am thrilled to join Sony as a research intern in Computer Vision this Summer.
2023-02: Two of our papers have been accepted to ICASSP2023.
2022-11: We submit our paper Deep Random Projector: Accelerated Deep Image Prior to CVPR2023.
2022-10: We submit our paper Robust Autoencoders for Collective Corruption Removal to ICASSP2023.
2022-10: We submit our paper Random Projector: Efficient Deep Image Prior to ICASSP2023.
2022-09: I am thrilled to join Uber as a Ph.D. Software Engineer Intern this Fall.
2022-08: Our paper Blind Image Deblurring with Unknown Kernel Size and Substantial Noise is available at arXiv.
2022-05: I am thrilled to join Bytedance/TikTok as a research intern in Computer Vision this Summer.
2022-05: Our paper Performance of a Chest Radiograph AI Diagnostic Tool for COVID-19: A Prospective Observational Study has been accepted to Radiology: Artificial Intelligence.
2021-12: Our paper Early Stopping for Deep Image Prior is available at arXiv.
2021-06: The preprint of our study about transfer learning in medical imaging is available at arXiv.
2021-06: The preprint of our study on COVID-19 is available at medRxiv.
2021-04: Our paper with Medical School has been accepted to Neurosurgery.
2020-09: Press coverage about our COVID-19 healthcare project is available at CSE News, UMN News, and StarTribune.
Work Experience
Research Intern in Computer Vision at PureBiox | Fall 2023
Research Intern in Computer Vision at Sony | Summer 2023
Ph.D. Software Engineer Intern at Uber | Fall 2022
Research Intern in Computer Vision at Bytedance/TikTok | Summer 2022
Honors and Awards
ADC Graduate Fellowship, University of Minnesota
Distinguished Graduate, Jilin University
Graduate Student Fellowship, Jilin University
Excellent Academic Scholarship (Graduate), Jilin University
Distinguished Graduate Student Cadres, Jilin University
Excellent Academic Scholarship (Undergraduate), Jilin University
Professional Services
Journals and Conferences Reviewer
Reviewer for Pattern Recognition
Reviewer for Journal of Supercomputing
Reviewer for Journal of Network and Systems Management
Reviewer for International Journal of Numerical Modelling, Certificate
Reviewer for Neural Information Processing Systems (NeurIPS) | 2021, 2022, 2023
Reviewer for International Conference on Machine Learning (ICML) | 2021, 2022, 2023
Reviewer for International Conference on Learning Representations (ICLR) | 2021, 2022, 2023
Reviewer for Conference on Uncertainty in Artificial Intelligence (UAI) | 2023
Reviewer for International Joint Conference on Neural Networks (IJCNN) | 2023
Reviewer for The First Workshop on DL-Hardware Co-Design for AI Acceleration | 2023
Reviewer for International Conference on Artificial Intelligence and Statistics (AISTATS) | 2023
Reviewer for International Conference on Computer, Information Technology and Intelligent Computing (CITIC) | 2023
Conferences Volunteer
Volunteer for Neural Information Processing Systems (NeurIPS) | 2021
Volunteer for International Conference on Machine Learning (ICML) | 2021, Certificate
Volunteer for International Conference on Learning Representations (ICLR) | 2021, 2022, Certificate2021, Certificate2022
Assistant Chair for SIAM International Conference on Data Mining (SDM23) | 2023