I obtained my Ph.D. degree in Operations Research from The Ohio State University under the guidance of Parinaz Naghizadeh. Prior to joining the OSU, I earned my M.Sc. in Statistics from Georgia Tech, and dual B.Sc. degrees in Mathematics and Economics from the University of Washington, Seattle. 

Email: yang.5483@osu.edu,        CV: [Curriculum Vitae] 

Research Interests

My primary research interests include decision-making under uncertainty, machine learning, data analytics, and optimization, with a particular focus on developing statistical data debiasing algorithms to ensure fair algorithmic decision-making.

Current research projects include:

• Data Bias, Fairness, Generalization in Centralized Machine Learning

• Personalization and Fairness in Federated Learning 

Publication (Google Scholar)

Submitted and Working Papers

• Generalization Error Bound for Learning with Censored Feedback

with Ali Payani and Parinaz Naghizadeh. Under Review. 2025.

• Enhancing Group Fairness in Federated Learning through Personalization

with Ali Payani and Parinaz Naghizadeh. Working paper. 2025.

• Enhancing Efficiency and Reducing Costs in Cardiology Rounds: a Simulation Study on Schedule-based Optimization

with Silvio Fernandes, Thipkanok Wongphothiphan, Xu Zhang, Jeffery Hoffman, Jessica Bowman and Yungui Huang. Submitted paper. 2025.

Conference and Workshop Papers

• Yang, Y., Liu, Y., Naghizadeh, P., "Adaptive Data Debiasing Through Bounded Exploration". Conference on Neural Information Processing Systems (NeurIPS), New Orleans, Dec. 2022. (acceptance rate: 25.6%). [link]

• Yang, Y., Liu, Y., Naghizadeh, P., "Adaptive Data Debiasing Through Bounded Exploration". ICML Workshop on Responsible Decision Making in Dynamic Environment (ICML Workshop), Maryland, July 2022. [link] 

Journal Papers

• Yang, Y., Liu, Y., Naghizadeh, P., "Adaptive Bounded Exploration and Intermediate Actions for Data Debiasing". Informs Journal of Computing (IJOC), 2025. [link] 

• Lu, Jye-Chyi, Yifan Yang, Shu-Yi Han, Yu-Chung Tsao, and Yuxuan Xin. "Coordinated inventory policies for meeting demands from both store and online BOPS channels". Computers & Industrial Engineering (CAIE) 145 (2020): 106542. [link] 

Invited Talks 

• "Enhancing Group Fairness in Federated Learning through Personalization". INFORMS 2024 Annual Meeting, Personalized and Fair AI: Advances in Federated Learning and LLMs Contributed Session. Seattle, WA, Oct. 2024. 

• "Generalization Error Bound for Learning with Censored Feedback". INFORMS 2023 Annual Meeting, Advancing Explainable Machine Learning Invited Session. Phoenix, AZ, Oct. 2023. 

• "Adaptive Data Debiasing through Bounded Exploration and Fairness". INFORMS 2022 Annual Meeting, ML/AI for Fairness, Transparency, and Interpretability Invited Session. Indianapolis, IN, Oct. 2022. 

Working Experience (LinkedIn)

• The Ohio State University

Graduate Research Associate                                                          Columbus, OH                    Feb. 2020 - May 2025

Graduate Teaching Associate                                                          Columbus, OH                    Aug. 2024 - Dec. 2024

Vice President of OSU INFORMS Student Chapter                      Columbus, OH                    Sept. 2021 - May 2024

• Nationwide Children's Hospital  

Research Intern                          Columbus, OH                    May. 2024 - Aug. 2024

• Cisco Research  

Software Engineer III PhD Intern  San Jose, CA (Remotely)    Sept. 2022 - Dec. 2022

• Georgia Institute of Technology   

Project Research Specialist Intern supervised by Jye-Chyi Lu       Atlanta, GA     Jan. 2019 - Dec. 2019

• J.P. Morgan Chase Bank                                         

Teller and ATM Custodian                                  Seattle, WA                       June. 2016 - Apr. 2017

• University of Washington, Seattle                                                

Undergraduate Calculus Tutor at MSC           Seattle, WA                        Jan. 2015 - June. 2016

Awards and Honors

• 2024 Student Chapter Annual Award as Summa Cum Laude awarded by the National INFORMS organization 

• 2023 Student Chapter Annual Award as Magna Cum Laude awarded by the National INFORMS organization 

• Travel grant award awarded by the 2023 North American School of Information Theory [link]

• 2022 NeurIPS scholar award by Conference on Neural Information Processing Systems [link]

• Scholarship awarded in 2020 Spring by both The Ohio State University and Integrated System Engineering

• Annual Dean's List high-scholarship awarded in 2015 - 2016 by University of Washington

• The 2nd prize in 13rd National Essay Competition awarded by CCNU China

Service

• Vice President of the INFORMS Student Chapter at The Ohio State University from Sept. 2021 to May 2024. [link]

• Session Chair: Advancing Explainable Machine Learning session chair in the INFORMS 2023 Annual Meeting.

• Group leader for NeurIPS 2022 High School Outreach Program [link]

• Reviewer for Conferences: IEEE International Symposium on Information Theory (ISIT); FAccT 2023; AISTAT 2024, 2025; ICLR 2025; NeurIPS 2025