Avishai Mandelbaum is a professor (emeritus) at the Faculty of Industrial Engineering and Management (IE&M), Technion, Israel. He has a B.Sc. in Mathematics and Computer-Science and an M.A. in Statistics, all summa cum laude from Tel-Aviv University. His Ph.D. is in Operations-Research, from Cornell University. After graduation, in 1983, he joined the Graduate School of Business at Stanford University. He then returned to Israel in 1991, as an Alon Young Scientist, to assume a position at the Technion. He served as IE&M Dean in 2015-2018, during which IE&M transformed into becoming "data-driven"; in particular, he led the creation and accreditation of Technion's pioneering undergraduate program in Data-Science & Engineering.
Prof. Mandelbaum is a Fellow of INFORMS and MSOM. He was an associate editor of the leading journals in his field, for example Mathematics of Operations Research, Management Science and Queueing Systems. He created the function and had been serving, over many years, as the faculty adviser for IE&M outstanding students. His research and teaching have enjoyed various prizes, within Technion and beyond, in particular the Yanai Prize for Academic Excellence at the Technion (inaugural class). His research covers stochastic models (analysis, asymptotics, control) and statistics, with applications to queueing theory/science, service systems (e.g. tele-services, hospitals) and data science.
In 2007, Prof. Mandelbaum co-founded, with Prof. Paul Feigin, theTechnion SEE Laboratory; and he has been serving as the lab's academic director ever since. Technion SEELab is collecting and maintaining a unique rich repository of data from ample service operations, mainly hospitals and telephone call/contact-centers. Data granularity is at the level of the individual customer-server transaction (event logs). And through its data, the SEELab has been supporting worldwide research and teaching of Service- and Data-Science, Engineering and Management.
- Course described in Service Engineering: Data-Based Course Development and Teaching. INFOMRS Transactions on Education, Volume 11, Number 1, 2010; Special issue on "Teaching Service and Retail Operations Management" (2009). Short version (PDF-202KB), Full version (PDF-3.65MB), (Link).
PhD: Probability and Stochastic Processes -- foundations, modelling, stochastic calculus; Dynamic Programming, Stochastic Control; Queueing, Fluid and Diffusion Networks; Linear Complementarity; Service Networks.
Undergraduate: Probability, Stochastic Processes, Statistics, Service Operations, Queueing Theory and Practice; Service Engineering and Management.
MBA: MIS/DSS, Computer Implementations of Mathematical Models, Linear and Integer Programming, Simulation, Production and Operations Management -- cases and theory.
Stochastic Networks: Fluid, Diffusion and Strong Approximations; Time and State-dependent Models; Stability, Harris Recurrence and Ergodicity; Service Engineering, Manufacturing, Project-management and Product-development Networks.