Research Experience & Projects

Selected research, optimization, and analytics work.

Optimization & Uncertainty Modeling Machine Learning Empirical Research

Optimization & Uncertainty Modeling

Robust Optimization for Integrated Healthcare Scheduling

Multi-resource MILP with budgeted uncertainty sets to jointly optimize surgical case planning and nurse-to-patient assignment, quantifying the Price of Robustness against surgical duration variability and nursing acuity spikes.

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MILP Gurobi Python Robust Optimization Healthcare Operations

The Integrated Healthcare Timetabling Problem — A Systematic Review

Structured literature review of 50+ papers across Patient Admission Scheduling, Surgical Case Planning, and Nurse-to-Room Assignment, mapping the field from foundational metaheuristics to modern robust and stochastic models and establishing the methodological frontier for fully integrated planning.

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Literature Review Healthcare Scheduling Metaheuristics Robust Optimization IHTP

MSc Thesis — Multi-objective Robust Optimization for Remanufacturing SystemsWorking Paper

Multi-period, multi-objective robust MILP for hybrid manufacturing and remanufacturing planning under simultaneous uncertainty in return quality, processing times, and demand, solved with NSGA-II and validated on a real industrial case.

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Robust Optimization Multi-objective Remanufacturing NSGA-II MILP

Blockchain-Based Transparent and Sustainable Supply Chain Network Design

Analysis of a blockchain-enabled closed-loop supply chain framework integrating IoT/RFID traceability, smart contract governance, and a multi-objective fuzzy optimization model to simultaneously balance economic, environmental, and social objectives.

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Blockchain Supply Chain Sustainability RFID Smart Contracts Network Design

Tire Closed-Loop Supply Chain Network Design under UncertaintyWorking Paper

Working paper. Multi-objective MILP for designing a sustainable tire supply chain with two rounds of remanufacturing (retreading), minimizing cost and environmental impact under stochastic demand and fuzzy return and production rates.

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MILP Robust Optimization Stochastic Programming Fuzzy Programming Benders Decomposition Remanufacturing

Large-Scale Optimization of Healthcare Logistics via Benders Decomposition

Benders decomposition algorithm implemented in GAMS to solve a blood supply chain network design problem, exploiting the natural strategic–operational decomposition to achieve tractability on instances where monolithic MILP fails.

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Benders Decomposition GAMS Blood Supply Chain Healthcare Logistics MILP

Discrete-Event Simulation for Transportation System Performance Analysis

Arena-based discrete-event simulation of a multi-stage transportation system, generating utilization profiles, queue-length distributions, and throughput sensitivity curves to identify binding bottlenecks and evaluate the system-wide impact of operational interventions.

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Arena Discrete-Event Simulation Queueing Theory Bottleneck Analysis Transportation

Machine Learning

AI Use in Healthcare: Ethical Framework for Diagnostic Applications

Graduate AI-ethics project combining a six-principle ethical design framework for AI-assisted medical diagnosis with a working explainability pipeline (Grad-CAM, Integrated Gradients, LIME, and SHAP on brain-tumor MRI and stroke-CT classifiers, evaluated quantitatively against ground-truth lesion masks) at its core.

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AI Ethics Healthcare AI Explainable AI Contestability Deep Learning

Next-Basket Prediction using Bidirectional Transformers

Progressive enhancement framework for e-commerce next-basket recommendation, replacing a GRU baseline with a bidirectional BERT4Rec Transformer and structured data augmentation to achieve a 4× improvement in Recall@10 on the Retail Rocket dataset.

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Transformers BERT4Rec Deep Learning Recommender Systems E-Commerce

Customer Lifetime Value Assessment via Weighted K-Means Clustering

Combined RFM scoring with a CLV-weighted K-Means algorithm to segment 2,239 grocery store customers, demonstrating that explicit lifetime value weighting produces sharper, more actionable segments than standard RFM classification alone.

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K-Means RFM CLV Clustering CRM

Empirical Research

Patterns of AI Use in Procurement and Firm PerformanceIn Progress

Ongoing PhD research measuring not whether firms adopt AI in procurement, but how they use it (its extent, locus, and depth across the purchasing process) and linking those patterns to cost performance, supply chain resilience, and sustainability.

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Artificial Intelligence Procurement Supply Chain Management Survey Research Industry 5.0

Structural Equation Modeling for Supply Chain Strategy and Environmental Performance

Two-part quantitative research project applying EFA, moderation/mediation analysis, and PLS-SEM to examine how purchasing recognition, long-term supplier commitment, and proactive environmental strategies drive supply chain performance across Turkish manufacturing firms.

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PLS-SEM SEM SmartPLS Supply Chain Environmental Performance Quantitative Methods

Economic Incentives and Household Waste Reduction — A Prospect Theory Experiment

Controlled experiment testing fines versus subsidies on household waste generation over 10 days, confirming loss aversion: the fine (loss frame) produced a 28% reduction versus 8% for an equivalent subsidy, consistent with Prospect Theory predictions.

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Prospect Theory Behavioral Economics Experimental Design Sustainability Waste Management

CRM Systems as Platforms for Democratizing Corporate Science

Philosophy of science paper arguing that Customer Relationship Management systems can be redesigned as epistemic interfaces, linking diverse stakeholder knowledge with corporate R&D agendas through frameworks of well-ordered science, hybrid forums, and epistemic justice.

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Philosophy of Science CRM Epistemic Justice Science Governance Participatory Research