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The 9th International Symposium on Cyber Security, Cryptology, and Machine Learning (CSCML 2025) is an international forum for researchers and practitioners in the theory, design, analysis, implementation, or application of cybersecurity, cryptography, and machine learning systems and networks, and, in particular, of conceptually innovative results.

Keynote Speakers 
(under construction)

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Leslie Valiant
Turing Award Winner

Leslie Valiant is a British-American computer scientist known for his pioneering work in theoretical computer science, particularly in computational learning theory and complexity theory. He introduced the Probably Approximately Correct (PAC) learning model, a key concept in machine learning, and developed the #P-completeness theory for computational counting problems. For his contributions, he received the Turing Award in 2010 and is currently a professor at Harvard University.

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Leslie Valiant

Turing Awsrd Winner

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In 2022 Dr. Dor chaired the national committee to select the Israel Prize for technology and innovation. Dr. Dor holds a Ph.D. and M.S degree in computer science from Tel-Aviv University, in addition to graduating cum laude for her Bachelor of Science degree. 

Her research about graph decomposition, median selection and geometric pattern matching in d-dimensional space has been published in several influential scientific journals.

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Alex "Sandy" Pentland
Stanford HAI Fellow, Toshiba Professor, MIT

Alex "Sandy" Pentland is an American computer scientist known for his pioneering work in computational social science, wearable computing, and artificial intelligence. He is a Toshiba Professor at MIT and a HAI Fellow at Stanford, with significant contributions to privacy regulations and data transparency. Forbes even recognized him as one of the "7 most powerful data scientists in the world", alongside tech giants like Google’s founders.

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Alex 'Sandy' Pentland 

Stanford HAI Fellow, Toshiba Professor MIT

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In 2022 Dr. Dor chaired the national committee to select the Israel Prize for technology and innovation. Dr. Dor holds a Ph.D. and M.S degree in computer science from Tel-Aviv University, in addition to graduating cum laude for her Bachelor of Science degree. 

Her research about graph decomposition, median selection and geometric pattern matching in d-dimensional space has been published in several influential scientific journals.

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Alon Kaufman
CEO and Co-Founder at Duality Technologies

Dr. Alon Kaufman is the Co-Founder and CEO of Duality Technologies, a company specializing in secure data collaboration. With over 20 years of experience in the hi-tech industry, he has led industrial research and corporate innovation teams, focusing on data science, AI, and cybersecurity. Before founding Duality, he served as RSA’s global director of Data Science & Innovation, where he played a key role in advancing fraud risk analytics. Kaufman holds a Ph.D. in Computational Neuroscience and Machine Learning from the Hebrew University and an MBA from Tel Aviv University. He is also a public speaker and educator, sharing his expertise on big data, cybercrime, and security.

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Alon Kaufman 

CEO and Co-Founder at Duality Technologies

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In 2022 Dr. Dor chaired the national committee to select the Israel Prize for technology and innovation. Dr. Dor holds a Ph.D. and M.S degree in computer science from Tel-Aviv University, in addition to graduating cum laude for her Bachelor of Science degree. 

Her research about graph decomposition, median selection and geometric pattern matching in d-dimensional space has been published in several influential scientific journals.

Sponsored By:

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In Cooperation With:

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Academic Track

Submission deadline: June 29, 2025
Acceptance notification: July 29, 2025
Camera-ready copy due: August 16, 2025

Entrepreneurship (Pitch) Track

Submission Deadline:

November 17, 2025

Acceptance Notification:

November 20th, 2025

PhD and Masters Track 

Submission Deadline:

November 17, 2025

Acceptance Notification:

November 20, 2025

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©2021 by International Symposium on Cyber Security Cryptology and Machine Learning.

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