The Conference Program Committee

Program Committee Members

Meet the Program Committee Members making CyberSec&AI Connected 2021 the best conference yet
with their hand-picked speakers, workshop presenters, panelists, and moderators.
Petr Somol
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Petr Somol

AI Research Director at Avast

Petr Somol has been active in machine learning research for more than 25 years. He obtained his PhD from the Faculty of Mathematics and Physics at Charles University in Prague. He worked as a researcher at Cambridge University, UK, and at the Czech Academy of Sciences.
After years of academic research he moved to industry. Having tasted the work of a Software Engineer at Oracle, he later joined Cisco Systems as Head of Research responsible for developing the Machine Learning based engine underlying Cognitive Threat Analytics. From February 2020, Petr assumes the role of AI Research Director at Avast. In this role, Petr focuses on solving fundamental AI problems in Threat Defense.
Cavallaro 1 min
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Lorenzo Cavallaro

Professor of Computer Science and Founder & Leader of the System Security Research Lab at King's College London

Lorenzo Cavallaro is a Professor of Computer Science and Chair in Cybersecurity (Systems Security) in the Cybersecurity group of the Department of Informatics at King’s College London, where he leads the Systems Security Research Lab, working at the intersection of program analysis and machine learning for systems security

Lorenzo holds a PhD in Computer Science from the University of Milan (2008), held Postdoctoral and Visiting Scholar positions at Vrije Universiteit Amsterdam (2010-2011), UC Santa Barbara (2008-2009), and Stony Brook University (2006-2008), and worked in the Information Security Group at Royal Holloway, University of London (Assistant Professor, 2012; Associate Professor, 2016; Full Professor, 2018).

He received the USENIX WOOT Best Paper Award in 2017, and regularly presents and publishes research, and sits on the technical program committee of top-tier and well-known international conferences, including IEEE S&P, USENIX Security, ACM CCS, NDSS, USENIX Enigma, WWW, ACSAC, DIMVA, and RAID.

Richard Chow
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Richard Chow

University Research Manager and Scientist in the University Research and Collaboration office within Intel Labs

Richard Chow is University Research Manager and Scientist in the University Research and Collaboration office within Intel Labs. He guides several of Intel’s academic research centers in the areas of security, networking, autonomous systems, and machine learning.

Before his current role at Intel Labs, Richard helped found and served as chair of SW SAFE. In this role he was responsible for review and approval of security architectures of software products across Intel. In the past, Richard held positions as Research Scientist at PARC, Research Scientist at Samsung Electronics R&D, and Security Architect at Yahoo and Motorola. His work concentrates on privacy, big data, mobile, and machine learning. He has over 20 granted US patents and over 30 peer-reviewed conference papers, journals, and book chapters. He was awarded runner-up for the 2010 PET Award for Outstanding Research in Privacy Enhancing Technologies. He has given invited talks at academic conferences and industry venues such as the RSA Conference, BlackHat, and OWASP.
Richard has a Ph.D. in mathematics from UCLA and a B.A. in mathematics from the University of Pennsylvania.

Axel Legay
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Axel Legay

Professor of software security at UC Louvain

Axel Legay is Professor at UC Louvain. He also used to work at Inria as team leader in cyber security. He received his Ph.D. in Computer Science from the University of Liège, Belgium. His main research interests are in formal verification, testing, and cyber security .

He is a founder and major contributor of statistical model checking (a statistical variant of model checking effectively used in industry), proveline (product lines analysis) , and malware analysis. He wrote more than 300 publications and he is a referee for top journals and conferences in those areas; He wrote several open source tools, and he has been institution PI for more than 30 projects.Richard has a Ph.D. in mathematics from UCLA and a B.A. in mathematics from the University of Pennsylvania.

Fabrizio Biondi
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Fabrizio Biondi

AI Staff Scientist at Avast

Fabrizio Biondi obtained his PhD at the IT University of Copenhagen in 2014, developing techniques for the computation of information leakage of systems modeled as Markovian processes. He served as a Maitre des Conferences at CentraleSupelec and Chair of Cybersecurity in Threat Analysis for Region Bretagne, before moving to Avast as an AI Research Manager.

Fabrizio’s work focuses on developing and deploying machine learning solutions to automate security processes, detect and analyze malware, and detect vulnerabilities.

As a co-founder of the MatesLab hackspace he is a free software advocate who has worked on honeypots, malware detection, distributed scanning (dnmap) keystroke dynamics, Bluetooth analysis, privacy protection, intruder detection, robotics, microphone detection with SDR (Salamandra) and biohacking.

He received the USENIX WOOT Best Paper Award in 2017, and regularly presents and publishes research, and sits on the technical program committee of top-tier and well-known international conferences, including IEEE S&P, USENIX Security, ACM CCS, NDSS, USENIX Enigma, WWW, ACSAC, DIMVA, and RAID.

Sebastian Garcia

Sebastian García

Assistant Professor at Czech Technical University in Prague, and Founder of the Stratosphere Lab

Sebastian Garcia is a malware researcher and security teacher who has extensive experience in machine learning applied to network traffic. He created the Stratosphere IPS project, a machine-learning-based, free software IPS dedicated to protecting civil society. He likes to analyse network patterns and attacks with machine learning.

As a researcher in the AIC group of Czech Technical University in Prague, he believes that free software and machine learning tools can help better protect users from abuse of their digital rights. He has taught in several countries and universities and worked on penetration testing for both corporations and governments. He has given many presentations at industry events including Ekoparty, DeepSec, Hacktivity, Botconf, Hacklu, InBot, SecuritySessions, ECAI, CitizenLab, ArgenCor, Free Software Foundation Europe, Virus Bulletin, BSides Vienna, HITB Singapore and CACIC.

As a co-founder of the MatesLab hackspace he is a free software advocate who has worked on honeypots, malware detection, distributed scanning (dnmap) keystroke dynamics, Bluetooth analysis, privacy protection, intruder detection, robotics, microphone detection with SDR (Salamandra) and biohacking.

He received the USENIX WOOT Best Paper Award in 2017, and regularly presents and publishes research, and sits on the technical program committee of top-tier and well-known international conferences, including IEEE S&P, USENIX Security, ACM CCS, NDSS, USENIX Enigma, WWW, ACSAC, DIMVA, and RAID.

Fralick min
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Celeste Fralick

Senior Principal Engineer and Chief Data Scientist

Celeste Fralick is the Senior Principal Engineer and Chief Data Scientist for McAfee. She is responsible for McAfee’s technical analytic strategy that integrates into McAfee consumer and enterprise products as well as internal Business Intelligence.

Celeste brings over 36 years of industry experience to McAfee. Prior to Intel’s divestiture of McAfee, she was Chief Data Scientist in Intel’s Internet of Things Group where she developed Machine Learning and Deep Learning analytics for over eight different markets. Celeste chairs McAfee’s Analytic Center of Excellence, and was a technical leader in Intel’s data science and biotech strategies, product qualification, and product life cycle programs.

Active in various industry and academic boards, journal editorial staffs, and consortiums, her experience spans analytics, systems, IoT engineering, semiconductor process and product development, regulatory, medical device, and quality/reliability domains. She holds a PhD in Biomedical Engineering from Arizona State University, concentrating on predictive analytics and neuroscience, and is currently authoring Springer’s ‘Intelligent Analytics’.

Jan Kohout
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Jan Kohout

Machine Learning Researcher

Jan Kohout is a machine learning researcher at Cisco Systems. He has been with Cisco since 2013, focusing on applications of machine learning in computer network security, specifically in anomaly detection and behavior modeling. Jan received his Ph.D. in Computer Science at the Czech Technical University, Faculty of Electrical Engineering, and his Master’s Degree at Faculty of Mathematics and Physics, Charles University in Prague.

Currently, Jan Kohout is leading the development of threat detection capabilities that combine multiple sources of input data, and he is also coordinating research collaborations between Cisco and academic institutions.

Branislav Bosansky
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Branislav Bosansky

Principal AI Scientist at Avast and Associate Professor at Czech Technical University in Prague

Branislav Bosansky has a long track record of research in algorithmic and computational game theory and applications of game-theoretic methods for security problems. He received his PhD at the Faculty of Electrical Engineering, at the Czech Technical University in Prague in 2015.

Afterwards, he spent 1 year as a postdoc researcher at the Aarhus University in Denmark and then rejoined Artificial Intelligence Center at the Czech Technical University in Prague. Branislav joined Avast in 2019 as a principal researcher with the aim of improving automated decisions based on game-theoretic reasoning. He is co-author of more than 35 papers at the top AI conferences and journals, and regularly participates as a member of program committees for top AI conferences (IJCAI, AAAI, AAMAS).

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