Curriculum Vitae
Education
- Ph.D. in Machine Learning, Georgia Institute of Technology, 2026-06 (expected), GPA: 4.0/4.0
- Advisor: Dr. Nicoleta Serban
- M.S. in Computer Science, Georgia Institute of Technology, 2021-12, GPA: 4.0/4.0
- Specialization: Computing System
- B.S. in Computer Science, Georgia Institute of Technology, 2019-12, GPA: 3.92/4.0
- Specialization: Information Internetworking and Intelligence
- B.S. in Industrial Engineering, Georgia Institute of Technology, 2019-12
- Specialization: Operations Research
- B.S. in Mathematics, Georgia Institute of Technology, 2019-12
- Specialization: General Mathematics
Professional Experience
Research
- Spring 2020 - Present: Graduate Research Assistant, Institute for People and Technology
- Advisor: Dr. Nicoleta Serban (Statistics)
- Fall 2023 - Spring 2024: Graduate Research Assistant
- Advisor: Dr. Imam Nabil (Neuroscience)
- Spring 2019 - Fall 2019: Undergraduate Research Assistant, Institute for People and Technology
- Advisor: Dr. Nicoleta Serban (Statistics)
- Spring 2018 - Spring 2019: Undergraduate Research Assistant
- Advisor: Dr. Natashia Boland (Operations Research)
- Spring 2018 - Fall 2018: Undergraduate Researcher
- Advisor: Dr. Karen Liu (Computer Graphics)
Industry
- Summer 2023: Software Engineer Intern, Microsoft, Redmond, WA
- Team: M365 Enterprise Search
- Summer 2022: Data and Applied Scientist Intern, Microsoft, Redmond, WA
- Team: Growth and Monetization
- Summer 2021: Software Engineer Intern, Microsoft, Redmond, WA
- Team: Azure Notification Hub
- Summer 2019: Software Engineer Intern, Microsoft, Redmond, WA
- Team: Activity Feed Service
- Summer 2018: Software Engineer Intern, Automatic Data Processing (ADP), Alpharetta, GA
- Team: Recruiting Management
Research Interests
Grounded in practical decision-making challenges within the healthcare and supply chain, my research aims to empower decision makers to efficiently navigate massive data and complex systems for reliable insights by shaping the next-generation big-data decision intelligence platforms in three interconnected areas:
High-performance information infrastructures that ingest, refine, prepare, and monitor massive volumes of data for large-scale modeling and complex analytics
Structure-aware mathematical modeling methodologies that ensure the scalability and computational tractability in solving large-scale problems
Analytical frameworks that fuse machine intelligence with diverse human expertise for trustworthy decision-making
Publications
Published
[1] Xie, Yujia, Gian-Gabriel Garcia, Eunhye Song, and Nicoleta Serban (2025). “Evaluating Access to Pediatric Psychosocial Services: A Discrete Event Simulation Approach.” Journal of Simulation, September, 1-24.
[2] Xie, Yujia, Pravara Harati, Janani Rajbhandari-Thapa, and Nicoleta Serban (2025). “Evaluating Access to Psychosocial Services for the Medicaid-Insured Children in Georgia,” BMC Public Health, 25(1), 244.
[3] Dehghanian, Amin, Yujia Xie, and Nicoleta Serban (2024). “Identifying Socially Optimal Equilibria using Combinatorial Properties of Nash Equilibria in Bimatrix Games,” INFORMS Journal on Computing, 36(5), 1261-1286.
[4] Zheng, Yuchen, Yujia Xie, Ilbin Lee, Amin Dehghanian, and Nicoleta Serban (2022). “Parallel Subgradient Algorithm with Block Dual Decomposition for Large-Scale Optimization,” European Journal of Operational Research, 299(1), 60-74.
Submitted
[5] Xie, Yujia, Mahdi Noorizadegan, Amin Dehghanian, and Nicoleta Serban. “A Machine-Learning Accelerated Parallel Branch-and-Price Framework for Stochastic Last-Mile Delivery with Cluster Layout.” in INFORMS Operations Research, under review
[6] Liu, Wanmeng, Yujia Xie, Sarah Vinson, Jiaxi Yu, and Nicoleta Serban. “Prevalence of Diagnosed Mental Health Conditions among Children with Publica and Commercial Insurance.” in BMC Public Health, major revision
[7] Zhang, Ziyu, Yujia Xie, Simona Ivanov, Steven Cuffe, and Nicoleta Serban. “Comparing Engagement in Clinic-based versus Community-based Mental Health Treatment for Medicaid-Insured Children.” in Administration and Policy in Mental Health and Mental Health Services Research, under review
In Progress
[8] A Parallel Computation Framework for Simulating and Calibrating Large-Scale Psychosocial Appointment Scheduling Systems. With Eunhye Song and Nicoleta Serban. target INFORMS Journal of Computing
[9] Health Equity: Bilevel Network Design for School-based Healthcare. With Mahdi Noorizadegan, Amin Dehghanian, and Nicoleta Serban. target INFORMS Manufacturing & Service Operations Management
[10] An Efficient Solution Method for a Class of Two-Stage Stochastic Integer Programs with Applications in Operations Management. With Joshua Caplan, Mahdi Noorizadegan, and Nicoleta Serban. target INFORMS Operations Research
[11] An Event Sequence Analysis of Pathways Leading to Dental Emergency Utilization. With Joshua Caplan and Nicoleta Serban. target Journal of the American Dental Association
Talks & Presentations
2025: Data-Driven Decision-Making in Healthcare Access Modeling: A Comparative Framework Analysis. INFORMS Annual Conference, Atlanta, GA
2025: ML-Accelerated Parallel Branch-and-Price Framework for Community-Based Service Delivery. With Mahdi Noorizadegan, Amin Dehghanian, and Nicoleta Serban. IISE Annual Conference, Atlanta, GA
2025: ML-Accelerated Branch-and-Price Framework for Large-Scale Last-Mile Delivery. With Mahdi Noorizadegan, Amin Dehghanian, and Nicoleta Serban. AAAI Bridge Program: Combining AI and OR/MS for Better Trustworthy Decision Making, Philadelphia, PA
2024: Modeling the Formation of Extrastriate Primate Visual Field Maps. With Iman Nabil and Michael Arcaro. VSS Annual Meeting, St. Pete Beach, FL
2023: Interdisciplinary Collaborative Efforts to Advance Mental Health System. With Priscilla Zhang and Nicoleta Serban. Health Systems: The Next Generation (HSNG), Atlanta, GA
2023: Reformulation for Large-Scale Traveling Salesman Problem under Clustered Layout. With Nicoleta Serban. INFORMS Annual Conference, Phoenix, AZ
2021: Identifying Disparities in Access to Psychosocial Services for the Medicaid-Insured Children in Georgia. With Pravara Harati and Nicoleta Serban. INFORMS Annual Conference, Anaheim, CA
2019: Metaheuristic Approach in Solving Less-than-Truckload Mix-Integer Problem. With Natashia Boland. National Conference on Undergraduate Research, Kennesaw, GA
On-Going Research Projects
- Longitudinal analysis and service pattern mining for pediatric psychosocial service utilization.
- Decomposition framework for large scale healthcare access simulation.
- Longitudinal and comparative study on pediatric healthcare access for southeast states between 2013 and 2019.
Research Mentorship & Supervision
Master Students
- Spring 2024 - Present: Joshua Caplan, Master of Analytics, Georgia Tech
- Project: parallel branch-and-price framework for large-scale delivery problem
- Project: dental treatment utilization and emergency treatment causal inference
- Project: two-stage stochastic integer programming in operations management
- Fall 2024 - Present: Hui Qiao, Master of Computational Science and Engineering, Georgia Tech
- Project: parallel simulation for psychosocial appointment scheduling
- Spring 2024 - Fall 2025: Yuting Gu, Master of Operations Research, Georgia Tech
- Project: geospatial psychosocial demand and supply partition
- Fall 2023 - Summer 2024: Ziyu Zhang, Master of Operations Research, Georgia Tech
- Project: psychosocial treatment transition and utilization analysis
- Current position: Ph.D. student in operations research, Georgia Tech
- Spring 2024 - Summer 2024: Kaiwen Wang, Master of Statistics, Georgia Tech
- Project: discrete event simulation for psychosocial appointment scheduling
- Current position: data scientist at ServiceNow
- Spring 2024 - Summer 2024: Wanmeng Liu, Master of Industrial and Systems Engineering, Georgia Tech
- Project: comparative study on nation-wide psychosocial treatment utilization
- Current position: data scientist at Blue Health Intelligence
- Spring 2024: Manvitha Kalicheti, Master of Computational Science and Engineering, Georgia Tech
- Project: structured benchmark data generation for large-scale delivery problem
- Current position: data engineer at Tesla
Undergraduate Students
- Spring 2021 - Summer 2024: Megan Sun, Industrial and Systems Engineering, Georgia Tech
- Project: design the sanity check pipeline for Medicaid-data processing
- Project: nation-wide psychosocial demand and supply estimation
- 2024 ISyE Pennington Undergraduate Research Award Recipient
- Spring 2022 - Present: Nandita Narayanan, Computer Science, Georgia Tech
- Project: hierarchical psychosocial demand estimation
- Current position: M.S. student in computer science, Georgia Tech
- Spring 2024 - Present: Simona Ivanov, Computer Science, Georgia Tech
- Project: psychosocial treatment transition and utilization analysis
- Project: parallel Medicaid-data processing pipeline
- Spring 2024 - Present: Sophia Parodi, Industrial and Systems Engineering, Georgia Tech
- Project: parallel Medicaid-data processing pipeline and process scheduling
- Spring 2024 - Present: Vivek Inumella, Computer Science, Georgia Tech
- Project: Medicaid event encoding
- Fall 2022 - Spring 2023: Jiaxi Yu, Industrial and Systems Engineering, Georgia Tech
- Project: comparative studies on nation-wide psychosocial service utilization
- Current position: planner at SLB
Teaching Activities & Highlights
Teaching
- Fall 2025, Fall 2024, Spring 2024, Spring 2023: Graduate Teaching Assistant, ISyE 6402 Time Series Analysis
- Instructor: Dr. Nicoleta Serban (class size: 100-200)
- Highlight 1: pioneered and managed the first official course GitHub organization to efficiently distribute instructional materials
- Highlight 2: overhauled the existing course instructional examples into interactive Jupyter Notebooks in both R and Python to accommodate students from various backgrounds and to improve learning outcomes
- Summer 2025, Fall 2021: Head Graduate Teaching Assistant, ISyE 6414 Regression Analysis
- Instructor: Dr. Nicoleta Serban (class size: 500-600)
- Highlight 1: transitioned the course grading protocol from Canvas into GradeScope to improve grading efficiency and to reduce scoring variations
- Highlight 2: managed the course GitHub establishment and streamlined the knowledge transfer to onboard the new TA team
- Fall 2022: Graduate Teaching Assistant, Master of Analytics 2022 Cohort
- Highlight: designed a 12-course preparatory series to provide new Master of Analytics students from different academic backgrounds with necessary software, programming, and foundation math knowledges for program success
- Fall 2019 - Summer 2020: Head Undergraduate Teaching Assistant, CS 4400 Intro to Database
- Instructor: Dr. Mark Moss (class size: 400 - 500)
- Highlight: launched the first Docker-based auto-grading system for assignment and coding exercises to provide students with rapid feedback on learning outcomes while simultaneously reducing TA workload
- Fall 2016 - Summer 2020: Undergraduate Teaching Assistant, CS 4400 Intro to Database
- Instructor: Ms. Monica Sweat, Dr. Mark Moss (class size: 400 - 500)
Skillset
Programming C++, C, C#, Java, Python, R, JavaScript, SQL, PHP, Typescript
Scripting Bash, PowerShell, Batch (BAT), Shell Script (sh)
Software Gurobi, CPLEX, SCIP
Deployment Git, Docker, CI/CD
Language Chinese (native), Cantonese (native), English (professional)
Awards and Fellowships
- 2021-2023 George Fellows Leadership Program in Health Systems and Analytics (twice)
- H. Milton Stewart School of Industrial & Systems Engineering, Georgia Tech
- 2019-2020 Alpha Pi Mu Academic Excellence Award
- H. Milton Stewart School of Industrial & Systems Engineering, Georgia Tech
- 2018-2019 President’s Undergraduate Research Award
- Georgia Tech
Industry Experience
- Summer 2023: Software Engineer Intern
- Microsoft M365
- Summer 2022: Data and Applied Scientist Intern
- Microsoft M365
- Summer 2021: Software Engineer Intern
- Microsoft Azure
- Summer 2019: Software Engineer Intern
- Microsoft Azure
- Summer 2018: Software Engineer Intern
- Automatic Data Processing (ADP)