Hi, I am a Research Scientist at CMU-LTI. Previously, I was a Staff Scientist at NIH and a Medical AI Advisor at GroqHealth (Maxeler@Groq). I completed my Ph.D. in Computer Science at Georgetown University in 2021, advised by Ophir Frieder. My research focuses on healthcare foundation models and AI in medicine. Before moving to the US, I was a member of Taiwan Marine Corps.
For more information, please visit my LinkedIn and Google Scholar.
Contact:
Email: haoreny@cs.cmu.edu
Research Scientist
June 2025 - Present
Staff Scientist
June 2021 - June 2025
Medical AI Advisor
Jan 2020 - December 2024
Medical Research Internship
2016 - 2019 summers
PhD in Computer Science
2015 - 2021
BS in Information Management
2010 - 2014
Health informatics
Interpretable Medical AI
Healthcare Foundation Model
AI in Medicine
Program Committee:
AAAI 2021, 2022, 2023, 2024, 2025
ECIR 2024
AMIA 2022
TreatRAG: A Framework for Personalized Treatment Recommendation
Chao-Chin Liu, Hao-Ren Yao, Der-Chen Chang and Ophir Frieder
ACM Conference on Recommender Systems (RecSys) 2024
Forecasting Prescription Efficacy
Hao-Ren Yao, Oskar Mencer, Han-Sun Chiang MD, Der-Chen Chang, and Ophir Frieder
European Conference on Information Retrieval (ECIR) 2025
Distilling Multi-Scale Knowledge for Event Temporal Relation Extraction
Hao-Ren Yao, Luke Breitfeller, Aakanksha Naik, Chunxiao Zhou and Carolyn Rose
ACM International Conference on Information and Knowledge Management (CIKM) 2024
(Full Research Track with Oral presentation, acceptance rate 23%)
A Fractional-Order Model for Optimizing Combination Therapy in Heterogeneous Lung Cancer: Integrating Immunotherapy and Targeted Therapy to Minimize Side Effects
David Amilo, Chinedu Izuchukwu, Khadijeh Sadri Khatouni, and Hao-Ren Yao
Scientific Reports 2024
(SCI Q1 IF 3.8)
Self-supervised Representation Learning on Electronic Health Records with Graph Kernel Infomax
Hao-Ren Yao, Nairen Cao, Katina Russell, Der-Chen Chang, Ophir Frieder, and Jeremy T. Fineman
ACM Transactions on Computing for Healthcare (HEALTH) 2024
(Invited to oral presentation at IEEE/ACM CHASE 2024)
(SCI Q1 IF 8.0)
Heat kernels on unit spheres and applications to graph kernels
Der-Chen Chang, Ophir Frieder, Chi-Feng Hung, and Hao-Ren Yao
Journal of Nonlinear and Variational Analysis 2023
(SCI Q1 IF 2.175)
A. Anshika, Debdas Ghosh, Radko Mesiar, Hao-Ren Yao, and Ram Surat Chauhan
Information Sciences 2023
(SCI Q1 IF 8.233)
Clinical Aligned Interpretable Graph-Based Modeling for Intelligent System in Predictive Medicine
Hao-Ren Yao
Georgetown University, PhD dissertation 2021
The analysis from nonlinear distance metric to kernel-based prescription prediction system
Der-Chen Chang, Ophir Frieder, Chi-Feng Hung, and Hao-Ren Yao
Journal of Nonlinear and Variational Analysis 2021
(SCI Q1 IF 2.175)
Cross-Global Attention Graph Kernel Network Prediction of Drug Prescription
Hao-Ren Yao, Der-Chen Chang, Ophir Frieder, Wendy Huang, I-Chia Liang and Chi-Feng Hung
ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) 2020
(Full paper with Oral presentation, acceptance rate 31%)
GUIR at SemEval-2020 Task 12: Domain-Tuned Contextualized Models for Offensive Language Detection
Tong Xiang*, Sajad Sotudeh*, Hao-Ren Yao, Sean MacAvaney, Eugene Yang, Nazli Goharian, Ophir Frieder
* equal contribution
SemEval @ COLING 2020
Hate speech detection: Challenges and solutions
Sean MacAvaney, Hao-Ren Yao, Eugene Yang, Katina Russell, Nazli Goharian, Ophir Frieder
PLoS ONE 2019
(SCI Q1 IF 3.24 - highly cited paper)
Multiple Graph Kernel Fusion Prediction of Drug Prescription
Hao-Ren Yao, Der-Chen Chang, Ophir Frieder, Wendy Huang, and Tian-Shyug Lee
ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) 2019
(Full paper with Oral presentation, acceptance rate 27%)
Graph Kernel Prediction of Drug Prescription
Hao-Ren Yao, Der-Chen Chang, Ophir Frieder, Wendy Huang, and Tian-Shyug Lee
IEEE-EMBS International Conference on Biomedical and Health Informatics (IEEE-BHI) 2019
(Full paper with Oral presentation, acceptance rate 11%)
On Bochner's theorem and its application to graph kernels
Der-Chen Chang, Ophir Frieder, and Hao-Ren Yao
Journal of Nonlinear and Convex Analysis 2018
(SCI Q2 IF 1.075)
Topic Participation Algorithm for Social Search Engine Based on Facebook Dataset
Hao-Ren Yao and I-Hsien Ting
MISNC 2014
Method and system for assessing drug efficacy using multiple graph kernel fusion
(Co-Inventor: Ophir Frieder and Der-Chen Chang)
Assignee: Georgetown University
U.S. Patent #11410763, August 9, 2022
Method and System for Assessing Drug Efficacy Using Multiple Graph Kernel Fusion
(Co-Inventor: Ophir Frieder and Der-Chen Chang)
Assignee: Georgetown University
U.S. Patent #11238966, February 1, 2022
Explainable AI-driven prescription prediction technologies
Maxeler Technologies, UK
License announced on January 2020
Cross-Global Attention Graph Kernel Network Prediction of Drug Prescription
(Co-Inventor: Ophir Frieder and Der-Chen Chang)
Assignee: Georgetown University
U.S. Pending provisional application #63/042,676, filed on June 23, 2020
Multiple Graph Kernel Fusion Prediction of Drug Prescription
(Co-Inventor: Ophir Frieder and Der-Chen Chang)
Assignee: Georgetown University
U.S. Pending provisional application #62/930/072, filed on November 4, 2019
NIH Postdoctoral Intramural Research Training Awards (IRTAs), 2021
National Science Foundation (NSF) Student Travel Award, IEEE BHI-BSN, 2019
Presidential Award, National University of Kaohsiung, 2014
Excellent Graduate, National University of Kaohsiung, 2014
Valedictorian, National University of Kaohsiung, 2014
Second Place, South Taiwanese Student Creativity Competition, 2013
Second Place, Graduation Project Competition, National University of Kaohsiung, 2013
Second Place, International ICT Innovative Services Contest, 2013
Speaker, Trends in Social Network Research Taipei Workshop, Academia Sinica, 2013
First Place, Social Network Analysis Competition, National University of Kaohsiung, 2013
College Student Research Training Fellowship, ROC National Science Council, 2013