Prof. Michael Weyrich is a faculty member at the Institute of Industrial Automation and Software Engineering (IAS) within the University of Stuttgart , leading the Cluster of Excellence IntCDC . His academic rank is Professor, and he focuses on Industrial Automation , Digital Twins , and Large Language Models (LLMs) for manufacturing and automotive systems. His research explores integrating LLMs into industrial automation for adaptive control, cloud offloading of vehicle functions, and semantic interoperability via Asset Administration Shells . He investigates modular production architectures , connected vehicle systems , and synthetic data generation for autonomous machinery. Recent publications highlight LLM-driven production planning , dynamic sensor calibration , and machine learning for fault detection in electric vehicle powertrains. His work emphasizes real-time data modeling and flexible microservice orchestration .
Soumaya Cherkaoui is a Full Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. Previously, she served as a Full Professor at Université de Sherbrooke and held industrial roles as an aerospace project manager. Her research integrates artificial intelligence with telecommunications, focusing on quantum computing, frugal edge intelligence, and applications in connected vehicles and IoT. Current Position: Full Professor, Polytechnique Montréal Prior Academic Role: Full Professor, Université de Sherbrooke Industry Experience: Aerospace Project Manager Research Interests: Convergence of AI and communications, quantum computing for networking, frugal intelligence at the edge, and applications in autonomous vehicles, industrial IoT, and smart grids. She leads government and industry-funded projects, including a $6 million quantum initiative in 2025. Recent Publication Trends: Her 2025–2024 work emphasizes quantum-enhanced anomaly detection (via QGANs), Open RAN slicing with quantum optimization, and reinforcement learning for secure cognitive radio networks. Topics span 5G/6G, vehicular networks, and zero-trust architectures. Scientific Awards: IEEE Communication Society Distinguished Lecturer (2020) ACM Mirela Notare Award (2023) IEEE Bio-Inspired Computing STC Leadership Award (2023) N2Women: Stars in Networking and Communications (2023) Best Paper Awards at IEEE ICC 2017, IEEE LCN 2021, ICCSPA 2024 Advising and Grants: Supervised 3 Master's students in 2024, with research on quantum GANs and federated learning for vehicular networks. Secured grants like the $6 million quantum project (2025) and participated in CFI-QC government funding (2022). Editorial and Leadership: Served as Associate Editor for IEEE, Wiley, and Elsevier journals. Chaired conferences like IEEE LCN 2019 and IEEE ICC2025, and held leadership roles in IEEE Communications Society committees.
Leah Findlater is an Associate Professor in the Department of Human-Centered Design & Engineering at the University of Washington (College of Engineering). She also holds adjunct and affiliate appointments in Computer Science & Engineering and Disability Studies, respectively, and serves as Associate Director of UW CREATE (Center for Research and Education on Accessible Technology and Experiences). Since 2021, she has led a research team in AI and accessibility at Apple. Her research focuses on creating adaptive technologies that accommodate individual needs, particularly for people with disabilities. Key areas include touchscreen personalization, machine learning interfaces, and sound recognition systems for deaf and hard-of-hearing users. Funding sources include NSF, DoD, and major tech companies. Recent work explores AI-driven tactile graphics, visual privacy management for blind users, and sound recognition systems. Her research combines lab studies, field deployments, and qualitative methods. NSF CAREER Award (2014) She advises through the Inclusive Design Lab, emphasizing mixed-methods research and collaborations with disability communities.
Gennie Gebhart is the Managing Director of Technology at the Electronic Frontier Foundation (EFF), overseeing Engineering & Design, Public Interest Technology, and Technical Operations teams. She concurrently serves as an Affiliate Associate Professor at the University of Washington's Allen School of Computer Science & Engineering. Her leadership spans both applied technology development and academic research in digital rights. Education: Gebhart holds a Master of Library and Information Science from the University of Washington Information School. Prior to EFF, she was a Henry Luce Scholar conducting work in Laos and Thailand. Research Focus: Her work centers on consumer privacy and security ecosystems, with specialized investigations into: Behavioral tracking infrastructures and data broker networks Policy frameworks for digital platforms and content governance Encryption technologies for communications (e.g., secure messaging) Open knowledge systems and equitable information access Honors: Recognitions include the competitive Henry Luce Scholars Program fellowship, supporting immersive professional work in Southeast Asia. Professional Engagement: She contributes to academic communities through program committee roles for computer security research conferences, bridging industry and scholarly discourse on emerging threats.
Dr. Mohammad Iftekhar Husain is a Professor and Graduate Coordinator in the Department of Computer Science at California State Polytechnic University, Pomona (Cal Poly Pomona). He serves as the Inaugural Director of the PolySec Cyber Lab, a federally funded center for cyber security and forensics education, research, and outreach (~$2.5M in grants), and directs the university's Virtual Reality Lab. His career spans over a decade of leadership in cyber security program development, extramural funding, and academic governance. Education: B.S., Computer Science, Yamagata University (Japan) M.S. & Ph.D., Computer Science and Engineering, SUNY-Buffalo Dr. Husain's research focuses on data privacy in social networks, neurophysiological cyber security solutions, and blockchain applications. He has secured $18.4M in principal investigator grants, including NSF SFS, EAGER, and REU Site projects, and trained students placed in top institutions like UC campuses, MIT Lincoln Lab, and government agencies such as NSA and DHS. His work on brainwave authentication earned a US patent (USPTO 10,198,566) and media coverage in Time Magazine and PC Magazine . Scientific Awards: 2016 College of Science Distinguished Teaching Award Early Promotion and Tenure (2016) 2020 Faculty Learning Community for Leadership Pipeline Development Cohort As academic leader, he founded the Cal-Bridge CS Ph.D. pathway program for underrepresented students, chairs the CPP Academic Senate Academic Programs committee, and led university IT initiatives including Cyber Security Cluster Hiring and High-Performance Computing Lab development.
Florina Almenares Mendoza is an Associate Professor at the Telematics Engineering Department of Carlos III University of Madrid , where she also serves as the Director of the University Master's Degree in Cybersecurity. Her research focuses on addressing security challenges in emerging technologies such as IoT, post-quantum cryptography, and privacy-preserving systems. Email: florina.almenares@uc3m.es Contact: 916246234 Location: 4.0.F06 - Quevedo Towers (Leganés) Research Interests Florina's work spans cybersecurity , Internet of Things (IoT) , and post-quantum cryptography , with a focus on scalable authentication, quantum-resistant protocols, and privacy. She explores machine learning applications for security, federated identity management , and smart grid security frameworks. Recent Publications Her recent research includes papers on DNSSEC soft delegation, hybrid quantum security for TLS/IPsec, PUF-based authentication in IoT, and blockchain-enabled auditability. These studies emphasize IoT security , quantum-resistant algorithms , and privacy-enhancing technologies .
Farinaz Koushanfar is a Professor in the Department of Electrical and Computer Engineering at the Jacobs School of Engineering, University of California San Diego (UCSD) . She holds the Siavouche Nemat-Nasser Endowed Chair and serves as Founding Co-Director of the Center for Machine-Intelligence, Computing and Security . Her affiliations include NSF Trust-Hub (Co-PI) and NSF TILOS AI Institute . She also serves on the Editorial Board of The Proceedings of the IEEE . Research Focus: Prof. Koushanfar leads research in secure and efficient computing , including robust/safe AI , hardware/system security , AI-based optimization , and cryptographically secure privacy-preserving computing . Her work pioneered logic obfuscation/locking for chip security, automated co-design of AI systems , watermarking/tracing of deep learning models , and physical proofs of provenance . She explores co-design with cryptographic constructs for privacy preservation and manages nonlinearities in ciphertext domains. Article Trends: Recent publications show expertise in neural watermarking (deepfakes, media authentication), zero-knowledge proof frameworks , Trojan attack defenses in ML models, secure federated learning , and hardware acceleration of cryptographic protocols . Her work combines machine learning , cryptography , and physical design security across 2022-2025 publications. Scientific Awards: Fellow of ACM Fellow of IEEE Fellow of National Academy of Inventors (NAI) Fellow of Kavli Foundation of NAS Inducted to NAI 2024 Fellows Advising & Leadership: She has advised multiple PhD students who became faculty at top universities (e.g., Stanford, Purdue). She chairs conferences like ACM WiSec 2024 and co-led the NSF SaTC decadal review. Her lab ( ACES Lab ) produces award-winning graduates like Bita Rouhani (DAC Under-40 Innovators) and Shehzeen Hussain (UCSD Best Dissertation Award).
Professor Vlad Mykhnenko is Professor of Geography and Political Economy in the University of Oxford Department for Continuing Education, and a Research Fellow in Sustainable Urban Development at St. Peter's College, Oxford. He serves as Academic Director for Social Sciences at Oxford Lifelong Learning and has been with the Department since January 2017, initially taking up an Associate Professorship in Sustainable Urban Development. His academic career spans multiple institutions including the University of Birmingham, Al-Farabi Kazakh National University, the University of Nottingham, the University of Glasgow, and the Central European University. Professor Mykhnenko's educational background includes: PhD in Political Economy from Darwin College, the University of Cambridge (2005) MA in International Relations and European Studies from the Central European University (1999) MA (1998) and BA (1996) in International Relations from Taras Shevchenko National University of Kyiv As an economic geographer specializing in geographical political economy, Professor Mykhnenko challenges conventional wisdom about urban and regional development. His research initially focused on transition economies of Eastern Europe (particularly Polish Upper Silesia and the Ukrainian Donbas) before expanding to cities and regions worldwide. He has produced over 140 research outputs and secured £16 million in external research funding, with £2 million as Principal Investigator. His current research initiatives focus on green steel - rebuilding Ukraine's iron and steel sector post-war without fossil fuels - and sustainable urban development in Kazakhstan. His publication record demonstrates significant scholarly impact across diverse areas including urban shrinkage, post-war reconstruction, geopolitical analysis, and future trends in technology and governance. The breadth of his research interests spans from analyzing spatial economic patterns in African cities to examining the implications of the metaverse for future business practices. Professor Mykhnenko has substantial policy impact, with research quoted in at least 79 policy documents by 49 organizations across 21 countries. His work contributes to UN Sustainable Development Goals, with 30% directly attributed to SDG11: Sustainable Cities and Communities. He has advised governments, intergovernmental organizations, and multinational enterprises, including serving on a UN expert group to shape the New Urban Agenda and providing expert evidence to the UK House of Commons on Ukraine's recovery. In early 2025, he was appointed a commissioner for the Lancet Commission on Ukraine. Professor Mykhnenko has taught over 3,100 students across various institutions and currently contributes to Oxford's MSc in Sustainable Urban Development program. He has supervised numerous doctoral students and received recognition for his teaching excellence, including Fellow of the Higher Education Academy status and a Postgraduate Certificate in Academic Practice. His commitment to research-led teaching has resulted in innovative pedagogical approaches documented in peer-reviewed academic publications.
Salvatore Ruggieri is a Full Professor in the Department of Computer Science at the University of Pisa, where he teaches in the Master Programme in Data Science and Business Informatics. He is affiliated with the KDD LAB, a joint research group of ISTI-CNR and the University of Pisa, and actively contributes to national and European AI initiatives such as XAI, NoBIAS, TAILOR, and SoBigData.eu. His research focuses on data mining and knowledge discovery, with a strong emphasis on ethical AI. Key areas include discrimination discovery and prevention, fairness, privacy, explainable AI (XAI), causal inference, and classification algorithms. He has led significant projects such as ENFORCE, a national FIRB project on legal and computational enforcement of non-discrimination and privacy rights in ICT systems (2010–2014), and has served as program chair for the XIII Italian Symposium on Artificial Intelligence (2014). The recent publications (2018–2023) highlight a consistent trend in interpretable and fair machine learning, including selective classification, stability of interpretable models, and causal reasoning for fairness. His work often involves collaboration with leading researchers like Dino Pedreschi and Riccardo Guidotti, and appears in top venues such as AAAI, IEEE TKDE, and WIREs. His scientific honors include the award for the best Ph.D. thesis in Theoretical Computer Science from the Italian Chapter of EATCS. Best Ph.D. Thesis in Theoretical Computer Science, Italian Chapter of EATCS He advises and collaborates with numerous researchers in the KDD LAB and has contributed to major grants and research initiatives in AI and data science. He is involved in educational programs, including the National Ph.D. in Artificial Intelligence - Society, and promotes interdisciplinary research at the intersection of computer science, law, and ethics. Ruggieri is a member of the KDD LAB, where he leads research in ethical and transparent AI. He is also part of large collaborative networks such as SoBigData.eu and HumanE-AI-Net, which aim to build socially responsible and human-centered AI systems.
Karlyn D. Stanley is a Senior Policy Researcher at the RAND Corporation and a Professor of Policy Analysis at the RAND School of Public Policy. She also serves as an Adjunct Professor at the Walsh School of Foreign Service, Georgetown University, where she teaches on the ethical dilemmas of emerging technologies. Her work bridges law, technology, and public policy, with a focus on autonomous vehicles, artificial intelligence, and telecommunications. Her research interests include the legal and policy dimensions of autonomous vehicles, AI governance, privacy law, liability frameworks, and resilient infrastructure. She has led major studies on AV regulations across multiple countries and U.S. states, and on AI’s impact on copyright and privacy. Her expertise informs policymakers, including Congressional staff, through concise briefs and public presentations. Her recent publications reflect a strong trend in technology policy, particularly in autonomous systems and AI regulation. Her work spans comparative legal analysis, risk-based frameworks, and resilience planning, especially in critical infrastructure and national security contexts. Science, Technology, and Innovation Policy Autonomous Vehicles Artificial Intelligence AI Governance Technology Law Privacy and Cybersecurity Scientific Awards: No specific awards mentioned in the provided text. She advises on high-impact research projects and teaches graduate-level courses at Georgetown and RAND. Her work is supported by federal agencies and involves collaboration across disciplines and institutions. She has led studies for the U.S. Army, Department of Defense, and Congress, demonstrating significant grant and policy engagement. She is involved in research teams at RAND focused on technology, security, and public policy. Her projects often involve interdisciplinary collaboration, including legal experts, engineers, and policymakers, particularly in areas like AI ethics, autonomous systems, and infrastructure resilience.
Benjamin Recht is a Professor in the Department of Electrical Engineering and Computer Sciences and Department of Statistics at the University of California, Berkeley. Previously, he was an Assistant Professor in the Department of Computer Sciences at the University of Wisconsin-Madison. Recht received his BS in mathematics from the University of Chicago and his MS and PhD from the MIT Media Laboratory, followed by a postdoctoral fellowship at Caltech's Center for the Mathematics of Information. His research interests span Machine Learning, Optimization, Control Theory, and Statistics , with a focus on both theoretical foundations and practical applications. Recht's work addresses fundamental questions in reproducibility, generalization, and robustness of machine learning systems, while also developing novel methods for control, computer vision, and data analysis. Recht's recent publications reveal a strong focus on reproducibility in machine learning , with papers like "The Mechanics of Frictionless Reproducibility" (2024), alongside continued contributions to statistical learning theory ("Interpolating Classifiers Make Few Mistakes", 2023) and computer vision ("Plenoxels", 2022; "K-planes", 2023). His work increasingly addresses societal implications of AI , including papers on systemic harm detection and post-deployment evaluation. NSF Career Award Alfred P. Sloan Research Fellowship 2012 SIAM/MOS Lagrange Prize in Continuous Optimization Presidential Early Career Award for Scientists and Engineers 2014 Jamon Prize 2015 William O. Baker Award for Initiatives in Research 2017 and 2020 NeurIPS Test of Time Awards Recht has advised numerous PhD students who have gone on to faculty positions at top universities and research roles at leading technology companies. His work on optimization algorithms has been widely influential, including the development of methods like HOGWILD! for parallel stochastic gradient descent. He co-founded the Conference on Learning for Decision and Control and has served on editorial boards for the Journal of Machine Learning Research and Mathematical Programming. His research group spans both theoretical and applied work, with connections to healthcare (adaptive medication tapering), computer vision (radiance fields), and social impact (systemic harm detection in deployed systems).
Yan Solihin is a Professor and Director of the Cybersecurity and Privacy Faculty Cluster at the University of Central Florida. He holds the Charles N. Millican Professorship in Computer Science and serves as a leader in the College of Engineering. Ph.D. in Computer Science – University of Illinois at Urbana-Champaign Bachelor’s in Computer Science – Bandung Institute of Technology Bachelor’s in Mathematics – Indonesia Open University Master’s in Computer Engineering – Nanyang Technological University His research focuses on computer architecture , cybersecurity , and memory systems , particularly in areas like: Secure Execution Environment Trustworthy cloud and enclaves Side-channel analysis (microarchitecture, timing, caches) Memory encryption and integrity verification Persistent memory systems He has significantly influenced technologies such as Intel’s Cache Allocation Technology and Secure Guard eXtension’s Memory Encryption Engine. Scientific Awards : 2023 HPCA Test of Time Award 2004 NSF CAREER Award 2005 & 2010 IBM Faculty Partnership Awards IEEE Fellow (2017) ACM Distinguished Speaker (2019-2022) Multiple Hall of Fame and Best Paper recognitions At UCF, Solihin expanded the Cyber Security and Privacy Cluster, developed a master’s program in cybersecurity, and established an NSF-funded scholarship program for cybersecurity students.
Aravind Machiry is an Assistant Professor at Purdue University's Electrical and Computer Engineering Department and a founding member of the Purdue Systems and Software Security (PurS3) Lab . His research focuses on system security, particularly vulnerability detection, prevention, and secure system development using static/dynamic program analysis, fuzzing, type systems, and machine learning. Designing practical solutions for software and embedded system security Recipient of NSF CAREER and Amazon Research awards Active participant in SPLASH 2025 as OOPSLA Review Committee member His recent work includes automated vulnerability detection in embedded software, spatial memory safety enhancements, and security analysis of GitHub workflows. He has received recognition for his research through multiple distinguished paper awards and industry funding. Selected scientific awards include NSF CAREER Award (2024) Amazon Research Award (2022) Test of Time Award at FSE 2023 for DynoDroid Distinguished Paper Award at OOPSLA 2022 for 3c Qualcomm Innovation Fellowship (2025) His research team has developed frameworks like ARGUS for taint analysis of CI/CD workflows and FuzzUEr for UEFI interface fuzzing, discovering hundreds of critical vulnerabilities in open-source projects and thousands of command injection flaws in GitHub repositories.
Emma Dauterman serves as an Assistant Professor in the Department of Computer Science within Stanford University's School of Engineering. Her current teaching responsibilities include foundational and advanced courses in computer security and privacy systems. Her research focuses on computer and network security with emphasis on privacy-preserving architectures and secure system design . Key domains include cryptographic protocols, vulnerability mitigation, and privacy-enhancing technologies for modern computing environments. This work bridges theoretical security models with practical implementation challenges in networked systems. While no recent publications are listed in the available data, her course offerings indicate active research in privacy systems and advanced security frameworks. Teaching responsibilities demonstrate expertise across core security principles and cutting-edge research applications. As a faculty advisor for CS 499/499P Advanced Reading and Research, she mentors graduate students in independent security research projects. No major grants or external funding sources are specified in the current profile. No laboratory affiliations or research teams are explicitly mentioned, though her course specialization suggests involvement in Stanford's security research ecosystem.
Dr. Bei Jiang is an Associate Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta , Canada. She holds the Canada CIFAR AI Chair and is affiliated with the Alberta Machine Intelligence Institute (Amii) . Her academic journey includes a PhD in Biostatistics (2014) from the University of Michigan, MS (2008) and BS (2004) from the University of Alberta and Beijing University of Technology, respectively. Current Positions : 2021–Present (Associate Professor), 2022–Present (CIFAR AI Chair) Past Appointments : Assistant Professor (2015–2021), Postdoctoral Fellow at Columbia University (2014–2015), Research Assistant at University of Michigan (2009–2013) Research Interests : Dr. Jiang specializes in methods for joint modeling of longitudinal and health outcome data , Bayesian hierarchical modeling , functional and imaging data analysis , and statistical machine learning . Her work integrates kernel machine regression , differential privacy , and synthetic data generation to address challenges in heterogeneous health data and neuroimaging. Scientific Awards : Highlights include the 2015 SAMSI New Research Fellow , multiple Rackham Conference Travel Awards (2013, 2012), and prestigious NSERC scholarships (2009–2012). She has also received the J Gordin Kaplan Graduate Award (2008) and Statistical Society of Canada Travel Award (2008). Grants : $375,000 (CIFAR AI Chairs, 2022–2027), $480,000 (MITACS Accelerate, 2022–2025), and $210,000 (Canadian Statistical Sciences Institute, 2022–2025) Students and Postdocs : She mentors numerous PhD , MSc , and Postdoctoral Fellows , including Junxi Zhang (2023–Present), Enze Shi (2022–Present), and former advisees like Wenxing Guo (now Lecturer at University of Essex) and Yafei Wang (Assistant Professor at University of Alberta).
