Dr. Yossi Luzon

Senior Lecturer, School of Industrial Engineering and Management
Afeka - The Tel Aviv Academic College of Engineering
Email: yossefl@afeka.ac.il

Every second counts when someone calls 911. Every appointment slot matters when a patient needs care. Every kilowatt-hour counts as we transition to renewable energy. These aren't just abstract problems: they're puzzles where better mathematical models can genuinely improve lives. That's what drives my research: finding elegant analytical solutions to real-world challenges in emergency response, service systems, and sustainable energy.

How I Got Here

I've been captivated by improving decision-making in complex systems since my undergraduate days. The moment I realized that mathematical models could shape real-world outcomes, I knew this was my path. That journey started at the Technion, where I earned my B.Sc. in Industrial Engineering and M.Sc. in Operations Research.

After earning my Ph.D. from Tel Aviv University, I spent two formative postdoctoral years at the Rotman School of Management, University of Toronto, working with Oded Berman, Opher Baron, and Vedat Verter. Those years shaped my approach to research: it's not just about elegant mathematics but about developing analytical tools people can genuinely use.

Today, I'm a senior lecturer at Afeka College, specializing in Operations Research and Applied Analytics. My work combines optimization, stochastic modeling, and data-driven decision-making to tackle challenges in service systems, emergency response, digital marketing, and sustainable energy. I also serve as Chair of the Senior Faculty Union Committee.

The Work That Keeps Me Excited

Emergency response systems have always captured my imagination. I'm especially proud of our recent publication On Designing a Fire Emergency Vehicle Fleet (Manufacturing & Service Operations Management, 2025). In collaboration with colleagues from the University of Toronto and Queen's University, we developed a queueing-based framework to optimize emergency fleet design, validated using Toronto Fire Services data. Our insights can directly inform decisions that reduce response times and save lives.

Beyond emergency response, my paper Calendar Design for Assignment of Ongoing Appointments (Computers & Industrial Engineering, 2025) presents a stochastic optimization framework enhancing efficiency in hospitals and public service agencies. It's the kind of problem that seems straightforward but reveals fascinating complexity.

These projects have opened new directions: a multi-city study of light traffic conditions in emergency response, a data-driven framework for profit optimization in social media advertising, and analytical work on steady-state distributions for two-phase phase-type queues.

The People Who Make It Possible

Research is never a solo endeavor. I maintain active collaborations with researchers at the Rotman School of Management and Queen's University in Canada. In Israel, I work closely with Prof. Evgeni Khmelnitsky from Tel Aviv University (my Ph.D. supervisor), whose insights consistently push my thinking forward.

One exciting collaboration is with Playtika Ltd., one of the world's leading gaming companies. Supported by a substantial Israel Innovation Authority grant, we're developing data-driven optimization models for digital marketing, user engagement, and resource allocation. It's thrilling to see academic research translate into business solutions, demonstrating how operations research drives innovation in unexpected domains.

A Growing Passion for Sustainable Energy

Integrating renewable energy into national grids may be one of the most important optimization problems of our time. In our paper The potential of renewable electricity in isolated grids: The case of Israel in 2050 (Applied Energy, 2023), co-authored with Dr. Gur Mitelman and colleagues, we assess optimal energy mix and storage capacity to maximize renewable energy use in Israel's grid by 2050. We're developing solutions that could shape our energy future and contribute to global sustainability.

This work extends my core expertise in optimization to one of society's most pressing challenges. The intersection of operations research and environmental sustainability feels like where I can make my most meaningful contribution.

How I Think About Problems

I approach research through modeling simplicity combined with analytical rigor: abstracting complex systems into tractable formulations, validating them empirically, and iterating toward implementable solutions.

I believe the next evolution of artificial intelligence lies in Decision Intelligence, integrating data-driven learning with analytical modeling for smarter, context-aware decision-making. AI should empower human decision-makers without replacing them. Analytical models should remain supportive rather than prescriptive, combining computational precision with human intuition, ethics, and experience.

What Excites Me About the Future

The convergence of machine learning and operations research represents a new paradigm for data-driven optimization. I stay engaged by reviewing for journals such as MSOM, EJOR, POM, and attending conferences, including INFORMS and ORSIS.

Integrating predictive analytics into operational decision-making is transforming industries across logistics, healthcare, and energy. I'm convinced the best discoveries lie ahead, particularly at the intersections of disciplines that haven't traditionally collaborated.

Passing It Forward

As a mentor, I emphasize critical thinking, rigor, and creativity. I encourage students to pursue research that balances analytical depth with real-world relevance, and to seek collaborations beyond disciplinary boundaries where the most exciting discoveries occur.

I'm grateful to the mentors who instilled in me intellectual openness and resilience. These are qualities I cultivate in the next generation. Watching students grow into independent thinkers who tackle complex problems remains one of the most rewarding aspects of my career.