Gal Mendelson
Assistant Professor
Industrial and Systems Engineering / Operations Research
North Carolina State University
gmendel@ncsu.edu
Assistant Professor
Industrial and Systems Engineering / Operations Research
North Carolina State University
gmendel@ncsu.edu
I am an Assistant Professor in the Edward P. Fitts Department of Industrial and Systems Engineering (ISE) at North Carolina State University. I am affiliated with the NC State Operations Research (OR) Graduate Program and also mentor and advise active-duty and veteran students in ISE and OR.
I received my Ph.D. in Electrical Engineering from the Technion – Israel Institute of Technology in July 2020, under the supervision of Prof. Rami Atar and Prof. Isaac Keslassy. From 2021 to 2022, I was a postdoctoral researcher at the Stanford Graduate School of Business, hosted by Prof. Kuang Xu. From 2023 to 2025, I was an Assistant Professor in the Faculty of Data and Decision Sciences at the Technion.
To build a research hub dedicated to the efficient utilization and management of resources in energy-intensive systems. The goal is to do more with less energy while increasing the use of renewable resources and reducing environmental impact.
Energy systems; stochastic modeling and analysis; probabilistic methods in data science and machine learning; and queueing theory.
Our research group meets weekly. Each week, we either learn something together, work collaboratively on a research problem, or both.
We are currently engaged in a learning initiative that I call Demystifying AI, with the goal of understanding how large language models work end-to-end.
Meeting time: Wednesdays, 3:30–5:00 p.m. Eastern Time
Meeting link: Join the meeting
Who can join? Everyone is welcome. Meetings are open to the public and are not recorded. No registration or forms are required, and no personal information is collected.
No meeting on Wednesday October 7th.
Please note: Meetings may occasionally be canceled or moved and this may not be announced.
September 2026: Served as a judge for the INFORMS Junior Faculty Interest Group (JFIG) Paper Competition.
The competition recognizes outstanding research by junior faculty in operations research and the management sciences.
2026: Serving as a Program Committee member for the Machine Learning and Operations Research Workshop at NeurIPS.
The workshop brings together researchers using ideas from machine learning and operations research to improve learning, optimization, and sequential decision-making.
August 2026: Served on the judging committee for the INFORMS Applied Probability Society Best Student Paper Award.
This annual competition recognizes outstanding student research in applied probability. It was an honor to help evaluate the work of the next generation of researchers in the field.
August 2026: Designed and delivered a full-day workshop on “Becoming a Researcher in the Age of AI” for NC State ISE and Operations Research PhD students.
August 2026: Participated in the Stochastic Networks Conference at Chicago Booth School of Business and a workshop in honor of Jim Dai at Cornell University.
August 2026: Participated in the Stanford Ignite 20-year reunion.
Stanford Ignite is an intensive entrepreneurship program offered by the Stanford Graduate School of Business. The reunion brought together participants and faculty to celebrate two decades of turning innovative ideas into impactful ventures.
July 2026: Gave a workshop on decision-making under uncertainty in complex systems at the Life Cycle Sustainment Institute for Defense and Business.
Summer and Spring 2026: Taught ISE 362: Stochastic Models in IE at NC State.
This undergraduate course introduces students to probabilistic models for systems that evolve under uncertainty.
Spring 2026: Taught ISE/OR 760: Applied Stochastic Models at NC State.
This graduate course lays down the foundations for stochastic modeling and analysis at a PhD level, and is the basis for the Stochastic Models PhD qualification exam.
Detecting Service Slowdown Using Observational Data
Preprint under revision, 2026
with Kuang Xu (Stanford GSB)
Fooling Algorithms in Non-Stationary Bandits Using Belief Inertia
Preprint under revision, 2026
with Eyal Tadmor (undergraduate student, Technion)
Approximating Uniform Random Rotations by Two-Block Structured Hadamard Rotations in High Dimensions
Preprint under revision, 2026
with Tomer Zilca (M.Sc. student, Technion)
Trap Sampling: A New Method for Sampling Data Streams
Work in progress, 2026
with Ilai Avni (M.Sc. student, Technion) and Shay Vargaftik (Broadcom)
Marginal Value of Additional Resources in Energy Systems Under Uncertainty
Work in progress, 2026
with Joao Gabriel De Souza Vale (Ph.D. student, NC State OR)
Credit Calibration for Large Loads in Energy Markets
Work in progress, 2026
with Mufan Wang (Ph.D. student, NC State ISE)
Effective Energy–Flexibility Trade-offs in Energy Storage Capacity and Placement Planning
Work in progress, 2026
with Konstantin McKenna (Ph.D. student, NC State OR)
Probability of Mission Success in Space-Based Boost-Phase Ballistic Missile Interception
Work in progress, 2026
with Lysander Rehnstrom (M.S. student, NC State OR) and Brandon McConnell (NC State ISE)
On Binomial Tail Bounds
Work in progress, 2026
with Ankita Sen (Postdoctoral Researcher, Technion)
A Note on TurboQuant and the Earlier DRIVE/EDEN Line of Work
Research note, 2026
with Ran Ben-Basat, Yaniv Ben-Itzhak, Michael Mitzenmacher, Amit Portnoy, and Shay Vargaftik
On the Persistent-Idle Load Distribution Policy Under Batch Arrivals and Random Service Capacity
Preprint, 2021
with Rami Atar, Isaac Keslassy, Ariel Orda, and Shay Vargaftik
Load Balancing Using Sparse Communication
Operations Research, 74(2): 1026–1046, 2026
Gal Mendelson and Kuang Xu
Optimal Call-In Policies Under Travel-Induced Risk: Application to Hybrid Hospitalization
Queueing Systems, 110:6, 2026
Noa Zychlinski, Gal Mendelson, and Andrew Daw
EDEN: Communication-Efficient Federated Learning via Robust Distributed Mean Estimation
Proceedings of the 39th International Conference on Machine Learning (ICML), 2022
Shay Vargaftik, Ran Ben Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, and Michael Mitzenmacher
Load Balancing with JET: Just Enough Tracking for Connection Consistency
Proceedings of the 17th ACM International Conference on Emerging Networking EXperiments and Technologies (CoNEXT), 2021
Gal Mendelson, Shay Vargaftik, Dean H. Lorenz, Katherine Barabash, Isaac Keslassy, and Ariel Orda
DRIVE: One-Bit Distributed Mean Estimation
Advances in Neural Information Processing Systems (NeurIPS), 2021
Shay Vargaftik, Ran Ben Basat, Amit Portnoy, Gal Mendelson, Yaniv Ben-Itzhak, and Michael Mitzenmacher
A Lower Bound on the Stability Region of Redundancy-d with FIFO Service Discipline
Operations Research Letters, 2021
Gal Mendelson
AnchorHash: A Scalable Consistent Hash
IEEE/ACM Transactions on Networking, 2020
Gal Mendelson, Shay Vargaftik, Katherine Barabash, Dean Lorentz, Isaac Keslassy, and Ariel Orda
Persistent-Idle Load-Distribution
Stochastic Systems, 10(2): 152–169, 2020
Rami Atar, Isaac Keslassy, Gal Mendelson, Ariel Orda, and Shay Vargaftik
Sub-Diffusive Load-Balancing in Time-Varying Queueing Systems
Operations Research, 2019
Rami Atar, Isaac Keslassy, and Gal Mendelson
Replicate to the Shortest Queue
Queueing Systems, 2019
Rami Atar, Isaac Keslassy, and Gal Mendelson
dRMT: Disaggregated Programmable Switching
Proceedings of the ACM SIGCOMM Conference, 2017
Sharad Chole, Andy Fingerhut, Sha Ma, Anirudh Sivaraman, Shay Vargaftik, Alon Berger, Gal Mendelson, Mohammad Alizadeh, Shang-Tse Chuang, Isaac Keslassy, Ariel Orda, and Tom Edsall
On the Non-Markovian Multiclass Queue with Risk-Sensitive Cost
Queueing Systems, 2016
Rami Atar and Gal Mendelson
2024: Exceptional Teaching Award (Technion, Discrete Mathematics)
2020: Fulbright Postdoctoral Scholarship
2020: Honorable mention: The George B. Dantzig Dissertation award, INFORMS
2019: Applied Probability Society best student paper award for "Sub-Diffusive Load-Balancing in Time-Varying Queueing Systems", INFORMS
2019: The Joseph Perl prize for excellent research in communication systems
2017-2020: Hasso Plattner Institute Ph.D. Scholarship
2008-9, 2015, 2020: Excellent Teaching Award (Technion)
Committees and Competition Judging
Judging Committee, INFORMS Applied Probability Society Best Student Paper Award (2022, 2023, 2026, 2027)
Judge, INFORMS Junior Faculty Interest Group (JFIG) Paper Competition (2026)
Program Committee, Machine Learning and Operations Research (MLxOR) Workshop at NeurIPS (2026)
Peer Review
Number of distinct manuscripts reviewed indicated in parentheses; revisions of the same manuscript are counted once.
Journals
ACM Transactions on Internet of Things (1)
European Journal of Operational Research (1)
Journal of Simulation (1)
Management Science (1)
Mathematics of Operations Research (4)
Operations Research (4)
Queueing Systems (2)
Stochastic Systems (1)
Grant Proposals
Israel Science Foundation (1)
Conference Session Chair
INFORMS Annual Meeting (4)
INFORMS Applied Probability Society Conference (1)
NC State University
Spring and Summer 2026: ISE 362: Stochastic Models, undergraduate, Industrial and Systems Engineering
Spring 2026: ISE/OR 760: Applied Stochastic Models, graduate, Industrial and Systems Engineering and Operations Research
Technion – Israel Institute of Technology
Spring 2022–2023, 2023–2024, and 2024–2025: Service Engineering, Faculty of Data and Decision Sciences
Winter 2023–2024 and 2024–2025; Spring 2024–2025: Discrete Mathematics, Faculty of Data and Decision Sciences
Technion – Israel Institute of Technology
Graduate-Level Courses
2017, 2018: Stochastic Processes and Applications, Industrial Engineering and Management
2016, 2017: Foundations of Stochastic Processes, Electrical Engineering
Undergraduate-Level Courses
2016–2019: Random Signals, Electrical Engineering
2016–2019: Introductory Project in Electrical Engineering, Electrical Engineering
2008–2009, 2015: Probability, Algebra I, Calculus I and II, Ordinary Differential Equations, and Partial Differential Equations, Mathematics
NC State University
Joao Gabriel De Souza Vale, Ph.D. student in Operations Research
Marginal Value of Additional Resources in Energy Systems Under Uncertainty
Mufan Wang, Ph.D. student in Industrial and Systems Engineering
Credit Calibration for Large Loads in Energy Markets
Konstantin McKenna, Ph.D. student in Operations Research
Effective Energy–Flexibility Trade-offs in Energy Storage Capacity and Placement Planning
Lysander Rehnstrom, M.S. student in Operations Research
Probability of Mission Success in Space-Based Boost-Phase Ballistic Missile Interception
Technion – Israel Institute of Technology
Dr. Ankita Sen, Postdoctoral Researcher
Technion – Israel Institute of Technology
Ilai Avni, M.Sc. student
Trap Sampling: A New Method for Sampling Data Streams
Tomer Zilca, M.Sc. student
Approximating Uniform Random Rotations by Two-Block Structured Hadamard Rotations in High Dimensions
Eyal Tadmor, Undergraduate Researcher
Fooling Algorithms in Non-Stationary Bandits Using Belief Inertia
Energy-Efficient Operation of NC State HVAC Systems
ISE Senior Design Project, 2026
The team is developing models of NC State’s HVAC systems and designing operational solutions to improve energy efficiency.
Students: Yousuf Siddiqui, Emilio Ponce, and Cameron Sivilla
Connecting PetConnect: A Digital Transformation of PetConnect’s Workflow
Student Project, 2023
PetConnect is a nonprofit organization dedicated to rescuing and rehoming pets. The students developed a digital platform that centralizes data, streamlines organizational processes, supports data analysis, matches adopters with dogs, and generates personalized shopping lists. The system was designed to improve operational efficiency and reduce the organization’s administrative workload.
Students: Nour Eldne Shannan, Or Haziza, Yuval Dror, Katia Shammas, and Noa Rahamimov
OPT Tov: Increasing Throughput in a Frozen-Product Packaging Line
Student Project, 2023
The students analyzed the packaging process of a frozen-food manufacturer and developed solutions for improving its throughput. Their work included identifying the factory’s operational needs, collecting and analyzing production data, and evaluating the expected effects of their proposed solutions.
Students: Florian Tordjman, David Poignon Cahen, Naomie Melloul, and Nathaniel Adda
2020: Nvidia (Mellanox), Israel, researcher. Scheduling in optical circuit switching networks and routing in expander based topologies
2018: IBM research, Israel, internship. Using alarm data to predict network failures
2017: IBM research, Israel, internship. Hash based data center load balancing