Prof. Izack Cohen

Funded MSc/PhD positions for AI, modeling and optimization research.
If you have IE/DS/IS/Math/EE/CS background, contact to hear more.

Can deep learning understand a complex process from video better when it also knows the expected process behind it?
For example, can an AI system analyze a surgical or manufacturing video and identify the current stage more accurately by also using a model of the expected workflow?
Can AI search methods solve complex scheduling problems more effectively than traditional optimization approaches?
For example, can we develop AI search methods to build better schedules for hospital staff, production lines, or project teams when resources are limited and constraints interact in complicated ways?
How can AI search methods help us compare what should have happened with what actually happened in large, complex processes?
For example, can we efficiently detect and explain deviations between an intended business process and what really happened in a hospital, factory, or information system?
How much data do we really need before we can trust a model of how a real process works?
For example, how many observed cases are needed before we can confidently learn a reliable model of patient flow, customer service, or production behavior?

Aviv Gerasi, 2023, MSc, Conformance checking between a process model and stochastic observations – a comparative analysis (w/Gonen singer)
Danit Abukasis, 2022, MSc, An adaptive machine learning algorithm for the resource-constrained classification problem (w/ Gonen Singer)
Iyar Zaks, 2022, MSc, Capacitated machine scheduling for grid computing (w/ Carmel Domshlak)
Eli Bogdanov, 2022, MSc, Conformance checking over stochastically known event logs (w/ Avigdor Gal)
Elisheva Shukrun, 2021, MSc, Predicting waiting time in queueing systems: comparison of queueing theory and machine learning models (w/ Paul Feigin)
Noemie Balouka , 2019, PhD, Multi-mode resource constrained project scheduling problem with value and uncertainty considerations
Noa Zychlinski, 2018, PhD, Analysis of hospital networks via time-varying fluid models with blocking (w/ Avishai Mandelbaum)
Naama Avital, 2016, MSc, Operational management of supply chain with spare parts (w/ Yale Herer)
Nehemia Yaron, 2016, MSc, Parallel testing in project management settings: The impact of new information (w/ Avraham Shtub)
Chen Epstein, 2015, MSc, Motion and task planning for autonomous Dubins vehicles (w/ Tal Shima)
Elad Landau, 2014, MSc, Multi-echelon supply chains of repairable parts (w/ Avraham Shtub)
Noa Zychlinski, 2012, MSc, Developing fluid models for mass casualty events (w/ Avishai Mandelbaum)