Students

Michael presenting at the School’s Graduate Research Workshop

Michael had presented his research, “Calibrating Differential Privacy Noise in Federated Learning Based on Explainability and Decision-Boundary Signals” at the School of Industrial & Intelligent Systems Engineering Graduate Research Workshop. The research, a collaboration with researchers from Yonsei University in South

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Michael presenting at the School’s Graduate Research Workshop

Michael had presented his research, “Calibrating Differential Privacy Noise in Federated Learning Based on Explainability and Decision-Boundary Signals” at the School of Industrial & Intelligent Systems Engineering Graduate Research Workshop. The research, a collaboration with researchers from Yonsei University in South

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New accepted paper: Differential Privacy Configurations in the Real World: A Comparative Analysis

Exciting news: our paper “Differential Privacy Configurations in the Real World: A Comparative Analysis” was just accepted to IEEE Transactions on Knowledge and Data Engineering. Another great paper of Michael Khavkin‘s Ph.D.! Preprint is available here. Differential Privacy is the

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New accepted paper: Differential Privacy Configurations in the Real World: A Comparative Analysis

Exciting news: our paper “Differential Privacy Configurations in the Real World: A Comparative Analysis” was just accepted to IEEE Transactions on Knowledge and Data Engineering. Another great paper of Michael Khavkin‘s Ph.D.! Preprint is available here. Differential Privacy is the

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Lest We Forget: Using Machine Learning to Archive October 7 Testimonies

Graduate student Talya Ben Shitrit, advised by Prof. Joachim Meyer from The Department of Industrial Engineering at the The Iby and Aladar Fleischman Faculty of Engineering, are using advanced machine learning methods to process the vast amounts of testimonies from

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Lest We Forget: Using Machine Learning to Archive October 7 Testimonies

Graduate student Talya Ben Shitrit, advised by Prof. Joachim Meyer from The Department of Industrial Engineering at the The Iby and Aladar Fleischman Faculty of Engineering, are using advanced machine learning methods to process the vast amounts of testimonies from

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Rottem’s seminar talk

Rottem Button gave her (great) seminar talk on: “Did Informal Contact Tracing make COVID-19 Quarantines better?”

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Rottem’s seminar talk

Rottem Button gave her (great) seminar talk on: “Did Informal Contact Tracing make COVID-19 Quarantines better?”

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Congrats to Noam Sheena!

Very happy to announce that Noam Sheena has just received a Faculty Excellence award.

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Congrats to Noam Sheena!

Very happy to announce that Noam Sheena has just received a Faculty Excellence award.

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Michael presenting at the 24th Industrial Engineering & Management Conference

Michael Khavkin had presented his research at the 24th Industrial Engineering & Management Conference on April 28th. The title and the abstract of the talk: The impact of privacy guarantees and user decisions on the performance of machine learning models The growing

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Michael presenting at the 24th Industrial Engineering & Management Conference

Michael Khavkin had presented his research at the 24th Industrial Engineering & Management Conference on April 28th. The title and the abstract of the talk: The impact of privacy guarantees and user decisions on the performance of machine learning models The growing

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New paper accepted to Decision Support Systems

Super excited to share that the paper “Investigating the Impact of Differential Privacy Obfuscation on Users’ Data Disclosure Decisions” by Michael Khavkin and Eran Toch was just accepted to Decision Support Systems. Link to the journal proof: https://doi.org/10.1016/j.dss.2025.114474 The Question Differential Privacy

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New paper accepted to Decision Support Systems

Super excited to share that the paper “Investigating the Impact of Differential Privacy Obfuscation on Users’ Data Disclosure Decisions” by Michael Khavkin and Eran Toch was just accepted to Decision Support Systems. Link to the journal proof: https://doi.org/10.1016/j.dss.2025.114474 The Question Differential Privacy

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