I am currently an Applied Scientist at Amazon, working on search, ranking, pricing, and LLM problems. Before that, I was a post-doc and received my Ph.D. in the Computer Science Department at Purdue University, working on research problems in optimization, machine learning, causal inference, and NLP. I received my B.S in the Computer Science Department at National Tsing Hua University and worked as a Research Assistant at Academia Sinica before moving to Purdue.

** Coming from an underrepresented group, I feel incredibly fortunate and privileged to have been guided by amazing people. While I don’t consider myself to be particularly extraordinary, I believe I can still offer help to those in need. Please don’t hesitate to reach out to me here to see if I may help.

News

• Grateful to be invited to serve as a reviewer at FAccT 2025, Dec 2024.
• Grateful to be invited to serve as at ICML 2025, Dec 2024.
• Honored to be nominated as a full member of Sigma Xi, Nov 2024.
• Happy to announce that our paper on the Pricing Model (flatter minimum) was accepted in Amazon Machine Learning Conference (AMLC) Pricing Workshop, Oct 2024.
• Grateful to be invited to serve as a reviewer at AISTATS [Apologies due to time constraints, 0 biddings], Oct, 2024.
• Grateful to be invited to serve as a reviewer at ICLR, August, 2024.
• Grateful to be invited to serve as a Program Committee at AAAI, July, 2024.
• Honored to serve as a reviewer at Frontiers in Medicine, June, 2024.
• Attended Penn Causal Inference Summer Institute, June, 2024
• Thrilled to be selected as the final winner (selected from 234 teams out of 22 countries) at The IES International Hackathon at Amazon, May, 2024.
• Grateful to be a poster judge at American Causal Inference Conference (ACIC), May, 2024.
• Happy to serve as a reviewer at Amazon Machine Learning Conference (AMLC), May, 2024.
• Happy to serve as a reviewer at Neurips. May, 2024.
• One Paper Submitted to Amazon Machine Learning Conference (AMLC), May, 2024.
• Happy to serve as a reviewer at ICML. Jan, 2024.
• Paper accepted to ACM BCB (Jul ‘23). Published in Cell iScience. Jan, 2024.
• Applied Scientist at Amazon, Dec, 2023.
• Accepted and prestented a poster on GNN model for News framing prediction task at (The New Directions in Analyzing Text as Data (TADA), Nov, 2023.
• Invited to serve as a reviewer of NeurIPS. March, 2023.
• Invited to serve as a reviewer of ICML. Jan, 2023.
• Postdoctoral Research Associate at Purdue University , Jan, 2023.
• Ph.D Graduated, Dec, 2022.
• Paper accepted in PLOS Digital Health, Sep ‘22.
• Invited to serve as a reviewer of NeurIPS. March, 2022.
• Invited to serve as a reviewer of ICML. Feb, 2022.
• Invited to serve as a reviewer of ICPP. May, 2021.
• Presented our work “Identifying and Analyzing Sepsis States: A Retrospective Study on Patients with Sepsis in ICUs” at Regenstrief Center for Healthcare Engineering (RCHE), (flyer). Feb 24, 2021.
• Featured article about our Distributed GPU-Accelerated Optimizer for Multiclass Classification Problems (link). Feb 3, 2021.
• Google Fellowship Nominated by Purdue University. Sept, 2020
• Invited to serve as a reviewer of ICDM. 2020.
• Book Chapter “Parallel Optimization Techniques for Machine Learning”. Springer. 2020
• Received Regenstrief Center for Healthcare Engineering (RCHE) Student Scholarship, Purdue University. 2020 (Tweet)
• Our paper “Newton-ADMM: A Distributed GPU-Accelerated Optimizer for Multiclass Classification Problems” has been accepted in the Proceedings of the ACM/IEEE Supercomputing Conference (SC20) - 18% acceptance rate.
• Received Regenstrief Center for Healthcare Engineering (RCHE) Travel Award, Purdue University. 2020
• Received SIAM International Conference on Data Mining Travel Award (Cancelled due to COVID-19 outbreak), Cincinnati, Ohio, USA. 2020