Teaching is central to my work and one of the aspects of academic life I value most. Across MBA and Ph.D. programs and executive education, I focus on helping learners develop the analytical foundations and practical judgment needed to make decisions in a world increasingly shaped by data and artificial intelligence.

Education in the age of AI must go beyond learning how to use new tools. Students and leaders need to understand how to formulate the right problems, evaluate and challenge AI-generated outputs, recognize where human judgment remains essential, and deploy AI responsibly. That responsibility includes questions of fairness, transparency, and accountability, as well as the environmental footprint of the digital and AI systems we build and use.

My teaching also focuses on the operational settings in which these decisions play out. In degree programs and executive education, I cover optimization and process analysis, value-chain management, and ways to understand disruptions and resilience in global supply chains. Across these settings, I aim to help learners use analytical tools thoughtfully and with a clear understanding of their practical consequences.

What I teach

  • Analytics, optimization, and AI. Formulating decision problems, building and interpreting optimization and simulation models, and using AI tools productively while checking their assumptions and outputs.
  • Responsible AI and sustainable digital systems. Fairness, transparency, accountability, human judgment, and the social and environmental consequences of data-driven and AI systems.
  • Operations, value chains, and resilience. Process analysis, global value-chain management, supply disruptions, operational risk, resilience, and sustainability.

MBA and undergraduate courses

  • Optimization and Simulation Modeling (OIT 245, 247, and 248), Stanford GSB. Versions of Stanford’s MBA core course on translating managerial problems into optimization and simulation models. Recent offerings have incorporated chatbots for coding and model-building, together with exercises on auditing generated code, interpreting results, modeling fairness, and data-driven optimization. Cases have drawn on energy operations, course scheduling, commodity sourcing, and other operational settings.
  • Analytics and AI for Responsible Management, INSEAD. I designed this MBA elective around principles and practical design choices for responsible analytics and AI, and taught it twelve times across INSEAD’s Fontainebleau and Singapore campuses between 2019 and 2022.
  • Essentials of Technology for Business, INSEAD. Sessions on ethical issues in AI and on blockchain, taught between 2020 and 2022.
  • Business Analytics (OIDD 612) and Introduction to Management Science (OIDD 321), the Wharton School. Hands-on, flipped-classroom formats in which students worked through analytical models and applications during class.

Doctoral courses

  • Optimization (OIT 676 / CME 307 / MS&E 311), Stanford. Co-developed with Madeleine Udell as a foundation in optimization theory and algorithms for doctoral students in OIT, ICME, and related fields.
  • Foundations of Supply Chain Management (OIT 655), Stanford GSB. Fundamental supply-chain models, with applications to disruptions, supply-chain finance, sustainability, and social responsibility.
  • Models and Applications of Inventory Management (OIT 624), Stanford GSB. Doctoral-level models and methods in inventory management.
  • Modeling Workshop, INSEAD. Models for uncertain and strategic supply networks, operations and finance, sustainable supply chains, technology adoption, learning, experimentation, and online platforms.

Executive education

I have developed and taught sessions for senior executives on:

  • responsible data analytics and AI, including Stanford Executive Program, Data Analytics, Digital Transformation, and custom programs;
  • analytics and AI for operational decisions, including the Future COO Program; and
  • process analysis, operations and value-chain management, supply disruptions, and resilience in global supply chains, including the Stanford SEED Program for Developing Economies.

Teaching recognition

  • Faculty Peer Recognition Award for Teaching, Stanford GSB (2023)
  • Dean’s Commendation for Excellence in MBA Teaching, INSEAD (2021 and 2022)
  • Earlier teaching honors include the Outstanding Teaching Assistant Award at MIT Sloan (2010) and the Derek Bok Prize at Harvard (2006)

Course evaluations

I believe in being transparent about teaching outcomes while respecting the context in which students provide feedback. The public summaries report quantitative results and response rates, but exclude comments designated for instructor-only review, student-identifying information, and evaluations of course assistants.

View course evaluation summaries