labs
seminars
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Statistics-Powered ML: Reliable Black-Box Inference from Untrusted Data
Abstract AI systems are increasingly shaping people’s lives, opportunities, and scientific progress. But how can we trust the inferences of such complex, black-box systems? This question becomes even more urgent in the presence of two core challenges that are ubiquitous in high-stakes applications: data scarcity and test-time distribution shift. These issues not only limit… Continue Reading Statistics-Powered ML: Reliable Black-Box Inference from Untrusted Data
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Process Mining in Stochastic Settings
Abstract: Alignment-based conformance checking constructs optimal correspondences between observed process executions and normative models, enabling precise identification of deviations for root-cause analysis and process improvement. However, two fundamental challenges limit its applicability in modern settings: exponential state-space growth, which renders exact methods infeasible for very long traces, and uncertainty introduced when activity labels are inferred… Continue Reading Process Mining in Stochastic Settings
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Cohen, (Aya) Ayala
Professor Ayala Cohen is the Head of the Statistics Laboratory that operates within the Technion Research and Development Foundation Ltd. and is part of the Faculty of Industrial Engineering and Management. Its staff includes in addition to Professor Cohen, two statisticians, with a Ph.D degree, and Professor Paul D. Feigin, who serves as a consultant.… Continue Reading Cohen, (Aya) Ayala
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Levin, Asaf
Professor Asaf Levin joined the Technion in 2008. He received his Ph.D. in Operations Research from Tel Aviv University in 2003. From 2003 to 2004 he was a Postdoctoral Fellow at the Minerva Optimization Center, the Technion, then, he joined the Department of Statistics at the Hebrew University of Jerusalem as a lecturer. Prof. Levin… Continue Reading Levin, Asaf
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Data Science
In an era where information is created at a dizzying pace and changes constantly and decisions require the creation of in-depth analysis, the ability to make sense of large quantities of data is a necessary and sought-after power. A master’s degree in Data Science offers tools and knowledge that will enable you to face the great challenges of the 21st century in all areas of life: medicine, social media, finance, urban planning, smart cities and more. Continue Reading Data Science
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Information Management Engineering
Ongoing developments in information technologies are enabling the creation of information systems in a variety of fields, with an ever-increasing scale and sophistication. At the same time, users’ demands from information systems are also growing. Information system engineers are required to develop applications and products whose complexity and intricacy are constantly increasing. These systems utilize the latest technologies such as communication and distributed systems, command and control using artificial intelligence, data organization and retrieval, organizational resource management systems, e-commerce systems, integrated hardware and software systems and decision support systems. Continue Reading Information Management Engineering
