Hi, I'm Dr. Aliaa Alnaggar

I'm an Assistant Professor in the Industrial and Systems Engineering Department at Rochester Institute of Technology (RIT). I hold a Ph.D. and MASc in Management Sciences from the University of Waterloo, where I was co-supervised by Prof. Fatma Gzara and Prof. James Bookbinder. Prior to my current role, I was an Assistant Professor in Industrial Engineering at Toronto Metropolitan University (TMU) and a Postdoctoral Fellow in Operations Management at the Rotman School of Management, University of Toronto.

My research focuses on leveraging operations research and analytics techniques to optimize service design and operations in uncertain environments, with particular emphasis on last-mile delivery, the sharing economy, and healthcare systems. Additionally, my work explores developing innovative methodologies for modeling and solving complex optimization problems under uncertainty, that are applicable to a wide-range of practical problems. My methodological expertise includes distributionally robust optimization, stochastic programming, Markov decision processes, and machine learning integration into optimization frameworks.

My work has been funded by several competitive grants, including the Natural Sciences and Engineering Research Council of Canada (NSERC) discovery grant, Veterans Affairs Canada and Mathematics of Information Technology and Complex Systems (MITACS)

Welcome to my website!

Office: 81 Lomb Memorial Drive, Rochester, NY, 14623
Email: amaeie [at] rit [dot] edu
RIT Department Webpage Google Scholar LinkedIn
Dr. Aliaa Alnaggar

OPPORTUNITIES

🎓 PhD Opportunity (PDF)

ACADEMIC EXPERIENCE

Rochester Institute of Technology (RIT) Aug 2026 – Present
Assistant Professor, Industrial and Systems Engineering Department | Rochester, NY, USA
Toronto Metropolitan University (TMU) Jan 2023 – Aug 2026
Assistant Professor, Department of Mechanical and Industrial Engineering | Toronto, ON, Canada
Affiliated with the Data Science and Analytics Program
University of Waterloo Nov 2023 – Present
Adjunct Assistant Professor, Department of Management Science and Engineering | Waterloo, ON, Canada
University of Toronto (Rotman School of Management) Sept 2021 – Dec 2022
Postdoctoral Fellow in Operations Management | Toronto, ON, Canada
Recipient of NSERC Postdoctoral Fellowship | Advisors: Dr. Andre Cire and Dr. Adam Diamant

EDUCATION

University of Waterloo Aug 2021
Ph.D. in Management Sciences, Faculty of Engineering | Waterloo, ON, Canada
Dissertation: Optimization under Uncertainty for E-retail Distribution: From Suppliers to the Last-Mile
Advisors: Dr. Fatma Gzara and Dr. James Bookbinder
University of Waterloo Aug 2017
MASc in Management Sciences, Faculty of Engineering | Waterloo, ON, Canada
Dissertation: Distribution Planning with Consolidation – a Two-Stage Stochastic Programming Approach
Kuwait University Aug 2010
B.S. in Industrial Engineering | Kuwait City, Kuwait

RESEARCH INTERESTS

Methodologies: Optimization, Stochastic programming, Dynamic Programming, Markov Decision Processes, Robust Optimization, Distributionally Robust Optimization, Reinforcement Learning, Machine Learning

Applications: Crowdsourced Delivery, Transportation, Sharing-Economy, Healthcare Operations Management, Supply Chain Management, Sustainability

PEER-REVIEWED JOURNAL PUBLICATIONS

  1. A. Alnaggar and S. Bhatt* (2025) "Fleet Size Planning in Crowdsourced Delivery: Balancing Service Level and Driver Utilization." Omega, 103445.
    Finalist in the Gilbert Laporte Student Paper Competition at the CORS 2025 Conference.
  2. J. Nicholson, F. Gzara and A. Alnaggar (2025) "Unmanned Aerial Vehicle Traffic Network Design with Risk Mitigation." Transportation Research Part E: Logistics and Transportation Review, 204, 104380.
  3. A. Alnaggar, F. Gzara, and J. H. Bookbinder (2025) "Heatmap Design for Probabilistic Driver Repositioning Crowdsourced Delivery." Transportation Science, 59(1), 81-103.
  4. S. Helyar and A. Alnaggar (2025) "Air Quality Monitoring and Mitigation through Time-Series Forecasting and Stochastic Optimization." Journal of Environmental Management, 389, 125540.
  5. A. Alnaggar and F. Farrukh* (2025) "Distributionally Robust Hospital Capacity Expansion Planning under Stochastic and Correlated Patient Demand." Computers & Operations Research, 174, 106887.
  6. S. Rafayal and A. Alnaggar (2024) "Optimal Scheduling of Battery Energy Storage System Operations under Load Uncertainty." Applied Mathematical Modelling, 138, 115756.
  7. A. Alnaggar, F. Gzara, J. H. Bookbinder (2024) "Compensation Guarantees in Crowdsourced Delivery: Impact on Platform and Driver Welfare." Omega, 122, 102965.
  8. M. Cobbinah* and A. Alnaggar (2024) "An Attention Encoder-Decoder Model with the Teacher Forcing Technique for Predicting Consumer Price Index." Journal of Data, Information, and Management, 6 (1), 65-83.
  9. S. Rafayal, A. Alnaggar and M. Cevik (2024) "Optimizing electricity peak shaving through stochastic programming and probabilistic time series forecasting." Journal of Building Engineering, 88, 109163.
  10. A. Alnaggar, F. Gzara, J. H. Bookbinder (2021) "Crowdsourced Delivery: A Review of Platforms and Academic Literature." Omega, 102-139.
  11. A. Alnaggar, F. Gzara, J. H. Bookbinder (2020) "Distribution Planning with Random Demand and Recourse in a Transshipment Network." EURO Journal on Transportation and Logistics, 9 (1).

PREPRINTS

  1. A. Dehghan, A. Alnaggar, M. Cevik, M. Bodur (2026) "Neural Approximate Dynamic Programming for the Blood Sample Delivery Problem." Submitted to INFORMS Journal on Data Science.
  2. A. Alnaggar, G. Baloch, C. Kouki (2026) "Multi Echelon Perishable Inventory Management under Demand Uncertainty." Submitted to European Journal of Operational Research.
  3. T. Ramanan, A. Alnaggar, M. Cevik (2026) "Technician Routing and Coordinated Scheduling in the Sharing Economy Considering Workload Equity and Experience Levels." Submitted to Transportation Research Part E.
  4. S. Rafayal, M. Cevik, A. Alnaggar (2026) "Automated Peak Shaving Methods for Building Energy Management." Submitted to Expert Systems with Applications Journal.
  5. A. Alnaggar, M. Cevik (2026) "Stochastic and Distributionally Robust Models for the Supplier Selection and Order Allocation Problem." Book chapter accepted for publication in New Methods in Supply Chain Management: Data-Driven Techniques.

PAPERS IN PROGRESS

  1. A. Alnaggar and M. Bodur. "Reformulation Linearization Technique-based Solution Approaches for Solving Two-Stage Distributionally Robust Optimization Problems."
  2. A. Alnaggar, M. Bodur and E. A. Yildirim. "Reformulation Linearization Technique for Disjoint Bilinear Programs and Characterization of Exact Relaxations."
  3. A. Alnaggar, A. Cire and A. Diamant. "Two-stage Distributionally Robust Optimization for Network Rebalancing."
  4. A. Alnaggar, M. Cevik. "Optimizing Mass Casualty Evacuations Under Uncertainty Considering Spatiotemporal Dynamics of Casualties and Resources."
  5. A. Alnaggar and M. Cevik. "A Predict-then-Optimize Approach for Ambulance Dispatch Centre Expansion Planning Considering Response Time Uncertainty and Incident Priority."
  6. A. Dehghan, A. Alnaggar, M. Cevik, M. Bodur. "Partially Adaptive Multistage Stochastic Programming for Hospital Surge Capacity Planning."
  7. A. Alnaggar, G. Baloch and G. Taherkhani. "Stochastic Last-mile Delivery with Heterogeneous Crowdsourced Capacity."

INDUSTRY TECHNICAL REPORTS

  1. D. Neghab, A. Alnaggar and M. Cevik (2025). "Battlefield Evacuation Optimization during a Mass Casualty Incidents." Final grant report to Veterans Affairs Canada.
  2. S. Bhatt, A. Alnaggar (2025). "Exploring the Canadian Market Landscape for Machine Learning Solutions in the Legaltech Industry." Report to Sino Legaltech Inc., Mitacs Business Strategy Internship Program.
  3. A. Alnaggar, J.H. Bookbinder (2019). "Improving Vehicle Utilization in Truckload Transportation with Driver Regulatory Constraints." Report to Challenger Motor Freight, NSERC Engage Project.
  4. F. Pourhossein, A. Alnaggar, J.H. Bookbinder (2017). "Evaluating the Use of Cross-docks for Optimized Deliveries to Loblaws Stores." Report to Loblaws, NSERC Engage Project.
  5. A. Alnaggar, F. Pourhossein, J.H. Bookbinder (2016). "A Risk Evaluation Model for Network Design Modifications: An Inverse Optimization Technique." Report to Canadian Tire, NSERC Engage Project.

CONFERENCE PRESENTATIONS, EXTENDED ABSTRACTS, AND PROCEEDINGS

  1. Learning-Based Dynamic Dispatch for Time-Critical Blood Sample Collection. Invited talk, INFORMS Annual Meeting, Nov. 2026, San Francisco, CA, USA.
  2. Multi-Echelon Perishable Inventory Management under Demand Uncertainty. Invited talk, INFORMS Annual Meeting, Nov. 2026, San Francisco, CA, USA.
  3. Forecasting Intraday USD/CAD Exchange Rate with News-Derived Monetary-Policy Signals. Accepted Conference Paper, 36th IEEE International Conference on Collaborative Advances in Software and Computing (CASCON 2026), Nov. 2026, Toronto, Ontario, Canada.
  4. Convexification Methods for Solving Two-Stage Distributionally Robust Optimization with Applications to Crowdsourced Delivery. Invited talk, INFORMS Annual Meeting, Oct. 2025, Atlanta, GA, USA.
  5. Leveraging Decoupling in Robust Network Rebalancing. Invited talk, INFORMS Annual Meeting, Oct. 2025, Atlanta, GA, USA.
  6. Multi-Echelon Perishable Inventory Management under Demand Uncertainty. Invited talk, CORS Conference, Jun. 2025, Edmonton, AB, Canada.
  7. Technician Routing and Coordinated Scheduling in the Sharing Economy Considering Workload Equity and Experience Levels. Invited talk, CORS Conference, Jun. 2025, Edmonton, AB, Canada.
  8. Two-Stage Distributionally Robust Optimization for Service Region Design in Crowdsourced Delivery. Invited talk, INFORMS Computing Society Conference, Mar. 2025, Toronto, ON, Canada.
  9. Fleet Size Planning in Crowdsourced Delivery: Balancing Service Level and Driver Utilization. Invited talk, INFORMS Computing Society Conference, Mar. 2025, Toronto, ON, Canada.
  10. Fleet Size Planning in Crowdsourced Delivery: Balancing Service Level and Driver Utilization. Invited talk, Smart Freight Symposium, Nov. 2024, Hamilton, ON, Canada.
  11. Two-Stage Distributionally Robust Optimization for Service Region Design in Crowdsourced Delivery. Invited talk, INFORMS Annual Meeting, Oct. 2024, Seattle, WA, USA.
  12. Two-Stage Distributionally Robust Optimization for Service Region Design in Crowdsourced Delivery. Invited talk, International Symposium on Mathematical Programming, Jul. 2024, Montreal, Canada.
  13. Worker Pool Size Planning in Crowdsourced Delivery: Balancing Service Level and Driver Compensation Standards. Canadian Operational Research Society (CORS) Annual Meeting, Jun. 2024, London, Canada.
  14. Two-stage Distributionally Robust Optimization for Network Balancing Problems. Invited talk, Canadian Operational Research Society (CORS) Annual Meeting, Jun. 2024, London, Canada.
  15. Heatmap design for probabilistic driver repositioning in crowdsourced delivery. INFORMS Transportation Science and Logistics, Jul. 2023, Chicago, IL.
  16. Two-stage Distributionally Robust Optimization for Scarce Resource Allocation. Invited talk, INFORMS Healthcare, Jul. 2023, Toronto, ON.
  17. Dynamic Matching with Driver Compensation Guarantees in Crowdsourced Delivery. INFORMS Manufacturing & Service Operations Management, Jun. 2023, Montreal, Canada.
  18. Two-Stage Distributionally Robust Optimization for Service Region Design in Crowdsourced Delivery. Invited talk, Sustainable and Emerging Supply Chain and Logistics Seminar Defence Research and Development Canada, June 2023, Toronto, Canada.
  19. Two-Stage Distributionally Robust Optimization for Service Region Design in Crowdsourced Delivery. Canadian Operational Research Society (CORS) Annual Meeting, May 2023, Montreal, Canada.
  20. Two-stage Distributionally Robust Optimization for Network Balancing Problems. Invited talk, INFORMS Annual Meeting, Oct. 2022, Indianapolis, IND.
  21. Two-stage Distributionally Robust Optimization for Network Balancing Problems. Invited talk, Canadian Operational Research Society (CORS) Annual Meeting, Jun. 2022, Vancouver, Canada.
  22. Dynamic Matching with Driver Compensation Guarantees in Crowdsourced Delivery. INFORMS Annual Meeting, Oct. 2021, Anaheim, CA.
  23. Dynamic Matching with Driver Welfare Considerations in Crowdsourced Delivery. Canadian Operational Research Society (CORS) Annual Meeting, Jun. 2021, Virtual Conference.
  24. Balancing Supply and Demand in a Crowdsourced Delivery System. INFORMS Annual Meeting, Nov. 2020, Virtual Conference.
  25. Crowdsourced Delivery: State-of-the-art with Applications to Omnichannel Supply Chains. Invited talk, INFORMS Annual Meeting, Oct. 2019, Seattle, WA.
  26. Distribution Planning with Random Demand and Recourse in a Transshipment Network. Canadian Operational Research Society (CORS) Annual Meeting, May 2019, Saskatoon, SK, Canada.
  27. Distribution Planning with Consolidation - A Two-Stage Stochastic Programming Approach. Proceedings of 7th Odysseus workshop on Freight Transportation and Logistics, 2018, Cagliari, Italy, pp. 75-78.

RESEARCH GRANTS, FUNDING AND AWARDS

Faculty Grants & Awards

Prior Grants & Awards

TEACHING

RIT - ISEE 601: Systems Modeling and Optimization (Instructor)
Term Taught: Fall 2026 | Class Size: 10

Introductory graduate course covering Operations Research techniques for modeling and solving complex decision problems using deterministic and stochastic methodologies, implemented with commercial solvers like Gurobi.

TMU - IND 604: Operations Research II (Instructor)
Terms Taught: Winter 2023, Winter 2024, Winter 2025 | Class Size: 55-60 | Avg Evaluation: 4.7 / 5.0

Core 3rd-year IE course covering integer programming, dynamic programming, queuing theory, and stochastic processes with Python and Gurobi project implementation.

TMU - IND 405: Introduction to Data Science and Analytics (Instructor)
Terms Taught: Fall 2023, Fall 2024, Fall 2025 | Class Size: 50-60 | Avg Evaluation: 4.7 / 5.0

Core 3rd-year IE course on Python programming, statistical analysis, data visualization, and fundamental machine learning (clustering, regression, classification).

TMU - IND 816: Service Operations Management (Instructor)
Terms Taught: Winter 2024, Winter 2025 | Class Size: 35-40 | Avg Evaluation: 4.9 / 5.0

4th-year elective course using business case studies to cover service design, project management, quality, change management, and revenue management.

UW - MSCI 434: Supply Chain Management (Co-instructor)
Term Taught: Spring 2019 | Class Size: 55-60

Core 3rd-year management engineering course focusing on analytic tools to design, implement, and sustain competitive supply chain systems.

Teaching Assistantships (University of Waterloo)

STUDENT SUPERVISION

Postdoctoral Fellows

PhD Students

MASc Thesis Students

MEng Project Students

Student Research Collaborations & RAs

Capstone Projects Supervised (BEng IE at TMU)

SERVICE

Editorial and Conference Activities

University & Department Services

PhD & MASc Committees

PhD Examination Chair

Community & Outreach

TECHNICAL SKILLS & MEMBERSHIPS

Programming & Data Analysis: Python, MATLAB, R, SQL

Optimization Solvers & Tools: GUROBI, CPLEX, GAMS, Hexaly

Professional Memberships: