Techniques: Infectious Disease Modeling, Game Theoretical Model (stylized economic model), Real World Data Science, Statistical Modeling, Machine Learning, Health Economics and Outcomes Research (HEOR)Thesis Advisor: Pinar Keskinocak, Ph.D. Thesis Title: Modeling and Analytics to Inform Resource Allocation and Policy Decisions** RESEARCH STREAMS **Health Analytics: Child and Adolescent Mental Health • Analyzed Centers for Medicare &… Show more Techniques: Infectious Disease Modeling, Game Theoretical Model (stylized economic model), Real World Data Science, Statistical Modeling, Machine Learning, Health Economics and Outcomes Research (HEOR)Thesis Advisor: Pinar Keskinocak, Ph.D. Thesis Title: Modeling and Analytics to Inform Resource Allocation and Policy Decisions** RESEARCH STREAMS **Health Analytics: Child and Adolescent Mental Health • Analyzed Centers for Medicare & Medicaid Services (CMS) insurance claims data, assessing clinicians’ adherence to clinical practice parameters and FDA medication labels for treating Medicaid-insured children with mental health disorders in the 50 U.S. states.• Evaluated sequences of service utilization for children exhibiting suicidal ideation with machine learning techniques to identify underlying factors contributing to subsequent suicide attempts. Mathematical Predictive Modeling for the Spread of Infectious Diseases under Interventions • Forecasted the spread of infectious virus under various vaccine policies by considering deployment time and qualities of various vaccines types in response to the emergence of virus variants, contributing to improved public health outcomes.• Evaluated tradeoffs between efficacy and reach of vaccines with different attributes for effective allocation of scarce resources.Economic Decision Frameworks for Public-Private Partnership (PPPs)• Investigated the impacts of a state government’s financial and environmental policies on post-disaster debris recycling operations executed by public and private sectors with a stylized sequential game-theoretical model. Show less

• Analyzed flight volume and census bureau data to identify and visualize risk levels of Ebola across U.S. zip codes, providing actionable insights for surveillance and intervention.• Performed a cost-effectiveness analysis of mask mandates in public transportation using airborne transmissible disease models.• Conducted a machine learning study in conjunction with statistical analyses to estimate disease under-reporting rates and adjusted prevalence level, improving data insights… Show more • Analyzed flight volume and census bureau data to identify and visualize risk levels of Ebola across U.S. zip codes, providing actionable insights for surveillance and intervention.• Performed a cost-effectiveness analysis of mask mandates in public transportation using airborne transmissible disease models.• Conducted a machine learning study in conjunction with statistical analyses to estimate disease under-reporting rates and adjusted prevalence level, improving data insights required for further modeling studies. Show less

• Developed a discrete-time mixed-integer program optimizing the location of parcel carriers in a distribution center, thereby reducing their temporary staging time.• Designed greedy heuristics with historical last-mile delivery data, resulting in a 10% enhancement of on-time delivery service levels.

• Deployed IoT (Internet of Things) tags on products, enabling real-time tracking in middle-mile logistics.• Developed a machine learning model for inventory forecasting, facilitating proactive management of potential shortages and predicting future demand.

Georgia Institute of Technology - BS Industrial and Systems Engineering Capstone DesignClient : Delta Air Lines - Cargo Department• Designed a tool that finds the most optimal shipment routes that minimizes shipment time in inventory, flight cost, and load variance using greedy heuristics method, dynamic multi-commodity network flow, and python• Analyzed data given from Delta Cargo and formulate the optimization model and a routing algorithm

• Assisted Seong-Hee Kim, PhD (Georgia Institute of Technology)• Designed highway access control system using multi-class M/G/C/C State Dependent Queueing models and Cross-Entropy method• Discovered an optimal allocation of the lane capacity among different vehicle classes which maximizes the long-run average passenger throughput • Formulated multiple Simio Simulation models to provide real-life highway access control system data and validate the computed analytical data… Show more • Assisted Seong-Hee Kim, PhD (Georgia Institute of Technology)• Designed highway access control system using multi-class M/G/C/C State Dependent Queueing models and Cross-Entropy method• Discovered an optimal allocation of the lane capacity among different vehicle classes which maximizes the long-run average passenger throughput • Formulated multiple Simio Simulation models to provide real-life highway access control system data and validate the computed analytical data • Co-authored the proceeding paper, which is accepted to 2017 Winter Simulation Conference (WSC) Show less