Bill (IE 1964) & Penny George
The George Fellowship Program is designed to recognize exceptional students who have interests, activities, and research related to health systems and to prepare students for leadership roles in the field of health. Recipients of the fellowships are named George Fellows and are dedicated to the mission of advancing, leading, and transforming healthcare systems and improving the health and well-being of individuals and societies.
Eligibility & Application Process
- Deadline: The application deadline is July 15, 2025
- Eligibility: The nominee must be a graduate student in ISyE for the academic year following the date of nomination, preferably with interests and/or past activities broadly related to health systems.
- Required documents:
- Student Resume or CV: current resume highlighting activities and accomplishments that are relevant to the George Fellowship
- Faculty Nomination Letter: A nomination letter from an ISyE faculty member describing the accomplishments and goals of the student in the area health. The letter must certify that the student satisfies the eligibility conditions.
2025 - 2026 George Fellows
Mackenzie Czerner
Mackenzie Czerner is master's student pursuing a Health Systems degree through the Stewart School of Industrial and Systems Engineering. She recently graduated with highest honors from her undergraduate program, also at Georgia Tech, earning a BSBA concentrated in Information Technology Manangement with minors in Biology and Computer Science. She has previous healthcare experience through internships at a life sciences consulting firm and a biotech company, as well as through her undergraduate projects, including a semester-long strategy consulting practicum with Piedmont Atlanta. During her graduate program, she will be working for the Center for Humanitarian and Health Systems (CHHS) at Georgia Tech. Driven by a desire to leverage her skills to help others and a strong interest in biological sciences, she is drawn to a career focused on improving patient outcomes and advancing health equity, with a particular interests in preventative care, neurology, and women's health. She is eager to contribute to innovation in the healthcare sector and intends to pursue a career in healthcare consulting or hospital administration.
Paul Horton
Paul is a 4th year Ph.D. student in Machine Learning, advised by Dr. Yajun Mei and Dr. David Goldsman. His current research focuses on resource-constrained decision making in healthcare, specifically with clinical trial designs, diagnostic device evaluation, and uncertainty quantification. Paul has been recognized with the Graduate Teaching Fellowship, has served as a Graduate Student Instructor and Head Teaching Assistant, and received the Best Poster Award at the 2024 Georgia State Conference for Biostatistics and Bioinformatics. He also won the 2021 University of South Carolina Big Data in Health Science Competition. Before beginning his Ph.D., Paul worked in engineering, sales, and operations in industries including manufacturing and healthcare. He holds a B.S. in Chemical Engineering from Auburn University and his MBA from the University of South Carolina.
Che-Yi Liao
As a PhD candidate specializing in applied AI, machine learning, and operations research, Che-Yi develops data-driven solutions to improve patient care and optimize public health systems. Che-Yi translates complex research into practical tools that address real-world challenges, such as resource constraints and unpredictable events. His expertise includes using predictive modeling and anomaly detection to inform personalized medicine and identify critical issues in clinical workflows. He is also skilled in building and deploying complete AI/ML pipelines, from initial data analysis to fully operational tools, including recent work with Large Language Models for health-related applications. Che-Yi wish to apply this technical expertise to create reliable, impactful solutions that enhance patient outcomes and support intelligent decision-making in healthcare.
Yang Yang
Yang Yang is a Ph.D. student in Machine Learning in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. She earned a B.S. in Industrial Engineering from Georgia Tech and is advised by Profs. Kaman Paynabar and Edwin Romeijn. Her research focuses on advancing healthcare systems and policies through statistical and machine learning methods, with an emphasis on fair, interpretable, and well-calibrated modeling.
2024 - 2025 George Fellows
Rui Qi Chen
Rui Qi Chen is a Ph.D. student in Machine Learning at the H. Milton Stewart School of Industrial and Systems Engineering. He earned his Bachelor of Science in Chemical Engineering from Carnegie Mellon University. Rui Qi is currently working with Dr. Jing Li, focusing on applying machine learning to bio- and health-related fields such as cell therapy manufacturing, dental imaging, and health sensor data analysis. His research focuses on advancing machine learning methodologies, particularly in learning from limited supervision and improving model generalizability.
Sun Ju Lee
Sun Ju is a Ph.D. candidate in Operations Research at the H. Milton Stewart School of Industrial and Systems Engineering, advised by Dr. Gian-Gabriel Garcia. Her research interests lie broadly in problems motivated by health modeling and health policy applications. She is especially interested in equitable solutions to medical decision-making problems and interpretable machine learning algorithms in healthcare. She received her B.E. and B.A. in Engineering Sciences with a concentration in Mechanical Engineering from Dartmouth College.
Junghwan Lee
Junghwan (Jay) is a third-year PhD student in ISyE majoring Machine Learning. He earned his B.S. in Systems Management Engineering from Sungkyunkwan University in South Korea and an M.A. in Statistics from Columbia University. Under the guidance of Professor Yao Xie and Professor Shihao Yang, Jay's research concentrates on deep sequence models for reliable predictions, with applications in biology and healthcare.
Himadri Pandey
Himadri S. Pandey is a PhD student in Machine Learning at the H. Milton Stewart School of Industrial and Systems Engineering, advised by Dr. Gian-Gabriel Garcia. She received her Bachelor of Science in Computer Science, with a minor in Mathematics and Physics, from the University of Cincinnati. Her research interests include the application of Machine Learning to healthcare optimization problems. She is currently working on the optimal allocation of baseline tests for concussion and designing a model to counteract the clinical onset of rapid deterioration in pediatric patients in collaboration with Children's Healthcare of Atlanta. She is the recipient of (i) George Fellowship, (ii) Georgia HIMSS David Cowan Scholarship, and (iii) ISyE Phil and Delores A. Scott Graduate Student Health and Wellness Award.
Anjolaoluwa Popoola
Anjolaoluwa Popoola is 4th year PhD Student in Machine Learning at the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. She is currently advised by Kamran Paynabar. She received her bachelor’s degree in mathematics with a minor in biology from the Lincoln University of Pennsylvania, and her master’s degree in operations research from Georgia Tech. Broadly, her research interests include developing and utilizing machine learning methodologies and algorithms to solve prevalent challenges in healthcare and social welfare. Her current research focuses on glucose management, nutritional health and homelessness.
Yuming Sun
Yuming Sun is a Ph.D. Candidate in Operations Research at the H. Milton Stewart School of Industrial and Systems Engineering. He received his M.S. in Operations Research from Georgia Tech and B.S. in Industrial Engineering from Shanghai Jiao Tong University. His research interests cover healthcare delivery, healthcare optimization, vaccine-preventable disease modeling, evaluation of intervention strategies, resource allocation, and economic analysis of public health. In a collaboration with the Centers for Disease Control and Prevention, he is currently modeling the spread of poliovirus in high-risk areas and investigating cost-effective interventions to stop, prevent and eliminate polio outbreaks. He is the receipient of (i) George Fellowship, (ii) Seth Bonder Scholarship, and (iii) Honorable Mention in the Student Poster Competition at the 2024 American Association for the Advancement of Science Annual Meeting.
Xingjian Wang
Xingjian Wang is a second-year PhD student in Industrial Engineering. His research focuses on enhancing healthcare systems through quantitative methods. He is currently working on resource allocation for malaria intervention and control. Before starting his PhD program, he earned a Master’s degree in Industrial Engineering from Georgia Tech and a Bachelor’s degree in Industrial Engineering from Xi'an Jiaotong University in China.
Zihan Zhang
Zihan Zhang is a Ph.D. candidate in Industrial Engineering, under the supervision of Dr. Jianjun Shi and Dr. Kamran Paynabar. Her research specializes in high-dimensional data analytics and machine learning, with applications in manufacturing and healthcare systems. Her specific areas of interest include reliability and lifetime analysis, automated process control, and the operations and management of multi-unit stochastic systems.
Guantao Zhao
Guantao Zhao is currently a PhD student in machine learning under the guidance of Professor Nicoleta Serban. He previously completed double degrees in Mathematics and Computer Science at Rutgers University. Guantao's primary research focuses on enhancing the precision and efficiency of real-world decision-making processes through machine learning, with applications in traditional operations research, health analytics, healthcare scheduling management, and managerial economics.
2023 - 2024 George Fellows
Ali Abdeen
Ali Abdeen is a PhD student in Industrial Engineering SCE track. He holds a B.Sc. in Electrical Engineering from UW-Milwaukee and an MBA from Clemson University. Ali's primary research focus is on healthcare analytics, decision-making, and disease modeling. He is also interested in using mathematical modeling and simulation techniques on real-world healthcare data. This approach aids in clinical decision-making and plays a crucial role in shaping healthcare policies.
Joseph Bakhtiar
Joseph is currently a Machine Learning Ph.D. student. Previously, he completed dual degrees in Mathematics and Aerospace Engineering at Georgia Institute of Technology. He possesses a unique combination of machine learning, mathematics, and aerospace engineering expertise. His diverse academic journey culminated in a Ph.D. focused on groundbreaking research that intertwines financial planning with health-related uncertainties. This research includes leveraging advanced statistical models to optimize retirement strategies based on an individual's health and financial data.
Michael Biehler
Michael Biehler received his B.S. and M.S. degrees in Industrial Engineering from the Karlsruhe Institute of Technology (KIT) in 2017 and 2020, respectively. He is currently pursuing a Ph.D. degree with the H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology advised by Dr. Jianjun Shi. His research focuses on enabling efficient and safe decision-making in complex systems. Specifically, his main research areas are 3D Machine Learning and Cyber-Physical Security.
Abigail Chambless
Abigail is a master’s student pursuing a health systems degree in the Stewart School of Industrial and Systems Engineering, from where she also received her bachelor of science in industrial engineering in 2021. Throughout both her undergraduate and graduate programs, she has worked for the Center for Health and Humanitarian Systems (CHHS), an interdisciplinary research center on campus. She is drawn to making processes and systems more simple, intuitive, and effective, and is excited to apply her technical skills to the fields of healthcare delivery or public health.
Manvitha Kalicheti
Manvitha is a second-year master's student in ISyE, majoring in Computational Science & Engineering. She is actively involved in the Health Analytics Centre where she uses data to address real-world healthcare challenges. Prior to this, she completed her bachelor's in Mechanical Engineering from the Indian Institute of Technology Hyderabad. She is passionate about using analytical tools to solve problems such as disparities in access, provider burnout, and improving outcomes within healthcare.
Daniel Kim
Daniel Kim is a Ph.D. student in Industrial Engineering, where he is advised by Professor Pinar Keskinocak. He received his B.S. degree in Industrial and Systems Engineering in 2018 and M.S. degree in Operations Research in 2022 from Georgia Institute of Technology. His research interests lie primarily in the fields of decision making, healthcare and humanitarian operations management, and health economics and outcomes.
Mina Kim
I am Mina Kim, a first-year Ph.D. student at the Georgia Institute of Technology, majoring in Industrial Engineering within the Industrial and Systems Engineering department. I am truly honored to have the opportunity to work under the guidance of Professor Valerie Thomas in the ISyE department. My research focuses on the application of data science and machine learning tools, with a particular emphasis on explainable AI techniques to enhance the precision of decision-making processes. My primary research area centers on technology portfolio optimization problems within the energy sector.
Zhaowei Li
Zhaowei Li is a dedicated PhD student at the renowned Industrial and Systems Engineering (ISYE) department of Georgia Tech. Working under the esteemed guidance of Dr. Chip White, Zhaowei delves deep into the intersections of machine learning, biotechnology, and industrial systems. A pioneer in the burgeoning field of Digital Twins for CAR-T cell therapy and other bioindustry products, Zhaowei combines advanced techniques from Deep Reinforcement Learning and Meta-Learning to address complex challenges in bioinformatics.
Lingchao Mao
Lingchao Mao is a Ph.D. student in Machine Learning at the H. Milton Stewart School of Industrial and Systems Engineering. She holds bachelor's degrees in Industrial and Systems Engineering and in Statistics from North Carolina State University. Currently, she works with Dr. Jing Li on projects that use machine learning for the diagnosis and prognosis of neurological diseases such as brain cancer (glioblastoma), Alzheimer's Disease, and Post-Traumatic Headache. Her research interests include methodological developments in statistics and machine learning, specifically, how to integrate domain knowledge into machine learning models when working with high-dimensional and multi-modal health datasets.
Amaya McNealey
As a second-year Ph.D. candidate in Industrial Engineering, Amaya McNealey earned her undergraduate degree from North Carolina A&T State University in Industrial and Systems Engineering. Her research pursuits center around rectifying bias and enhancing fairness in medical decision-making and public health using data mining, statistics, and interpretable machine learning. Amaya's current focus lies in developing methods to mitigate bias in predictive maternal health models and analyzing trends in the opioid epidemic. Additionally, she is the founder of "Your Health, Our Hope," a non-profit organization dedicated to amplifying minority advocacy in health-related issues, while also fostering accessibility and mentorship for aspiring healthcare professionals.
Nathan Popper
Nathan Popper is a current Master’s in Analytics student from Dallas, Texas. He discovered a deeper passion for analytics during his recent work experience at Dallas County Health and Human Services. Analyzing COVID-19 data and formulating data-driven infection prevention strategies was the experience that crystallized his decision to pursue a career in data science. He aspires to improve people’s lives using data, and is confident that he will leave Georgia Tech with the skills required to bring this vision to fruition. In his free time he enjoys basketball, exercising, and nature.
Hairong Wang
Hairong Wang is a Ph.D. student in Operations Research at the H. Milton Stewart School of Industrial and Systems Engineering. She obtained B.A. in Mathematics from University of Oxford. She works with Prof. Jing Li on developing efficient, robust, and generalizable models for real-world problems in healthcare. Her work can be summarized into the following two areas: methodology development, where she integrates domain knowledge and data-driven algorithms to overcome the limitations of small sample sizes, and applications aimed at improving clinical decision-making, and supporting disease characterization understanding and discovery.
With special gratitude to Bill and Penny George; George Family Foundation
Bill (B.I.E. ‘64, Honorary Ph.D. ‘08) is the former CEO of Medtronic and a Senior Fellow at Harvard Business School, where he specializes in developing authentic leaders. Penny, Ph.D., is a leader in the national movement to transform medicine and health care through the principles and practices of integrative medicine. Together, they founded the George Family Foundation in 1994 to support programs they are passionate about and that transform lives by changing the systems affecting those lives for the better. Their foundation focuses on three primary areas: Penny’s passion for integrative health and healing; Bill’s passion for authentic leadership, and a shared passion for community. “To identify and address a need — especially one that connects with something we understand and can bring resources to — brings us pure joy,” said Penny. In addition to providing support for the George Fellows and Leadership Program in ISyE, Bill and Penny support Georgia Tech at the Institute level through the naming of George Tower as part of Tech Square Phase 3. They have also established the William W. George International Study Abroad Scholarships and the George Family Foundation Women in Engineering Leadership Initiative in the College of Engineering. Bill and Penny also funded the William W. George Chair Endowment in Health Systems and general program support for health systems, currently held by Dr. Pinar Keskinocak.
