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Jose SuchView profile

Professor

• Cybersecurity
• Artificial Intelligence
• User Privacy
• +5 more

Prof. Jose Such is a Professor of Computer Science at King's College London (KCL), affiliated with the KCL Cybersecurity Centre and the Informatics Security Hub. His research focuses on cybersecurity, AI ethics, privacy engineering, and conversational systems. He leads major projects such as REPHRAIN (Phase I & II) and SAIS, funded by EPSRC, addressing privacy, adversarial influence, and secure AI assistants. His work contributes to UN Sustainable Development Goals related to privacy and digital security. Key research areas include large language models (LLMs), smart home security, multi-user privacy conflicts, and ethical AI governance. Prof. Such has published over 80 peer-reviewed papers, with recent emphasis on mitigating privacy risks in conversational AI and developing safety benchmarks for LLMs. He oversees research projects involving multi-disciplinary teams, integrating technical solutions with legal and ethical frameworks. Notable outputs include the MalProtect malware defense system and the CASE-Bench evaluation framework for AI safety. His datasets and tools, such as SkillVet and ELVIRA, address privacy risks in voice assistants and cloud services. Prof. Such collaborates globally, with recent work exploring cross-cultural privacy practices in smart homes and the security challenges faced by marginalized groups. His research bridges technical innovation with societal impact, advocating for transparent and accountable AI systems.

Ameer AbdelhadiView profile

Assistant Professor

• Hardware Acceleration
• Neurotechnology
• Reconfigurable Computing
• +4 more

Dr. Ameer Abdelhadi is an Assistant Professor in the Department of Electrical and Computer Engineering at McMaster University. His research focuses on application-specific custom-tailored computer architectures, hardware-efficient deep learning, neurotechnology, and reconfigurable computing. He holds a PhD from the University of British Columbia and has held academic positions at the University of Toronto, Imperial College London, and Simon Fraser University, alongside industry experience in semiconductor design. Education: PhD in Computer Engineering (University of British Columbia, 2016). Research Interests: Hardware acceleration for machine learning and neurotechnology Reconfigurable computing and FPGAs/ASICs Asynchronous circuits and synchronization protocols VLSI physical design and CAD algorithms Publications span high-impact venues such as IEEE Journal of Solid-State Circuits, IEEE Hot Chips, and IEEE Micro. Notable achievements include the 2017 Best Paper Award at ASYNC for work on synchronization FIFOs. Teaching includes COMPENG 4DV4 (VLSI System Design) and ELECENG 4OI6B (Engineering Design). His lab focuses on advancing hardware systems for next-generation applications in AI and biomedical engineering.

• Computer Networks
• Cybersecurity
• Distributed Systems
• +4 more

Saurabh Bagchi is a Professor at Purdue University, West Lafayette, USA. He holds a PhD in Computer Science from the University of Illinois Urbana-Champaign (2001). His research focuses on distributed systems security, networking, and embedded systems. Key areas include IoT security, cyber-physical systems resilience, and machine learning applications in edge computing. Bagchi's work spans theoretical and applied domains, addressing challenges in distributed algorithms, fault tolerance, and secure communication protocols. His contributions to firmware analysis, serverless computing optimization, and anomaly detection in industrial IoT systems have been widely recognized. He has published over 300 papers in top-tier conferences and journals such as IEEE Transactions on Dependable and Secure Computing, ACM Transactions on Sensor Networks, and CVPR. He collaborates with researchers in academia and industry to advance resilient networked systems, including projects funded by NSF and industrial partnerships. His lab explores cutting-edge topics like federated learning security, edge computing architectures, and game-theoretic approaches to cyber defense.

Hasan DavulcuView profile

Professor

• Sociocultural Modeling
• Artificial Intelligence
• Machine Learning
• +5 more

Hasan Davulcu is a Professor in the School of Computing and Augmented Intelligence at Arizona State University (ASU). He holds a B.S. in Mathematics from Middle East Technical University (Turkey) and M.S./Ph.D. in Computer Science from Stony Brook University (NY). His research focuses on sociocultural modeling, AI, machine learning, and behavioral analytics for fraud detection. He leads the CIPS-AI Lab, developing data mining tools for semantic information extraction from social media and web data. Affiliations: Senior Global Futures Scientist (Global Futures Scientists and Scholars Program), Co-founder & CIO of ARTIS MAGI (AI-driven behavioral analysis startup). Education: Ph.D. Computer Science (Stony Brook, 2002), M.S. Computer Science (Stony Brook, 1995), B.S. Mathematics (METU, 1993). Research interests include: Sociocultural modeling and persuasive AI. Web/social media mining, information extraction, and database systems. Behavioral analytics for fraud detection and countering extremist influence. Key achievements: 2011 HSCB Focus Exceptional Scientific Achievement Award for work on sociocultural modeling in the DOD Minerva project. Principal Investigator on NSF and DoD grants, including behavioral analytics for financial fraud and social influence analysis of extremist groups. Grants & Projects: NSF PFI:BIC Grant (2014-2019): Behavioral analytics for fraud detection via visual analytics infrastructure. DoD Minerva (2015-2019): Measuring social influence of extremist groups. ONR Projects (2018-2021): Modeling polarization, adversarial framing, and disinformation tracking. Labs/Teams: Cognitive Information Processing Systems (CIPS-AI) Lab, which pioneers data mining techniques for unstructured social media data and semantic representation systems.

Bruce SchneierView profile

Lecturer

• Cybersecurity
• Privacy
• Technology Policy
• +3 more

Bruce Schneier is a Lecturer in Public Policy at the Harvard Kennedy School and a Fellow at the Berkman-Klein Center for Internet and Society at Harvard University. His work focuses on cybersecurity, privacy, and the societal implications of technology. Schneier holds adjunct roles at Inrupt, Inc., and serves on the boards of the Electronic Frontier Foundation and AccessNow. He is a leading voice on AI ethics, data protection, and government surveillance. Education and professional background are not explicitly detailed in the text, though his academic and industry roles indicate extensive expertise in security and public policy. Research interests include the balance between security and privacy, AI governance, and the impact of technology on democracy. His influential writings, including 14 books and hundreds of articles, explore topics like encryption, AI risks, and cyber threats. Recent work emphasizes AI’s societal challenges, such as job displacement, legislative drafting, and election integrity. He has testified before Congress and advised on federal cybersecurity policies. Awards include his fellowship at the Berkman-Klein Center. Schneier collaborates frequently with Nathan Sanders and others on AI-related projects, advocating for transparent and accountable technological development. His advocacy spans academic, corporate, and governmental sectors, emphasizing the need for ethical frameworks in emerging technologies.

• Face Recognition
• Developmental Prosopagnosia
• Neurodiversity in Women
• +3 more

Dr. Anna Bobak is a Senior Lecturer in Psychology at the University of Stirling, UK. She holds a PhD from Bournemouth University (2016) and joined Stirling as a Research Assistant on an EPSRC project under Peter Hancock before transitioning to her current role. Her primary research focuses on individual differences in unfamiliar face recognition, particularly developmental prosopagnosia, and the reliability of face-processing assessments. She also investigates neurodiversity in women, emphasizing lived experiences of autism and ADHD, including camouflaging behaviors and societal awareness. Research Interests: Face Recognition: Examines perceptual strategies, diagnostic criteria (e.g., Balanced Integration Score), and technological applications in forensic contexts. Neurodiversity: Explores gender-specific manifestations of autism and ADHD, societal perceptions, and support mechanisms. Cognitive Methodology: Advances psychometric rigor in face-processing studies and critiques measurement validity. Her work bridges theoretical research and real-world applications, such as evaluating automated face recognition technology’s biases and collaborating on initiatives like #ScienceForUkraine to aid displaced academics. She is affiliated with the Cognition in Complex Environments research group and contributes to global security and resilience themes at Stirling.

He BingshengView profile

Professor

• Big Data Systems
• Cloud Computing
• High Performance Computing
• +4 more

Professor He Bingsheng is a faculty member at the Department of Computer Science, School of Computing, National University of Singapore (NUS), where he also serves as Vice-Dean, Research. He holds a Ph.D. in Computer Science from the Hong Kong University of Science & Technology (2008) and dual bachelor’s degrees in Computer Science & Engineering and Business Administration from Shanghai Jiao Tong University (2003). Education: Ph.D. (HKUST, 2008), B.E./B.B.A. (SJTU, 2003) Prior roles: Microsoft Research Asia (2008-2010), Nanyang Technological University (NTU), Singapore His research focuses on Big Data management systems , particularly on cloud computing and emerging hardware architectures (GPU, FPGA, NVM). He has led projects like ThunderGP, a novel FPGA-accelerated graph processing framework achieving 419x speedup for Covid-19 prevalence estimation. His work spans parallel/distributed systems and graph algorithms , with publications in ACM SIGMOD, VLDB, SC, and IEEE Transactions. The selected articles highlight his contributions to GPU/FPGA optimization , LLM applications , and graph analytics . He has received multiple best paper/demo awards, including IEEE/ACM ICCAD (2017), IEEE IC2E (2016), and ACM SIGMOD (2008). As a PC chair and editorial board member for journals like IEEE TPDS and TCC, he actively shapes academic discourse. PhD Students: Chen Xinyu, Tan Hongshi Courses Taught: CS4225/5425 Big Data Systems for Data Science

Sewon MinView profile

Assistant Professor

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +2 more

Sewon Min is an Assistant Professor at UC Berkeley's Electrical Engineering and Computer Sciences (EECS) department and a research scientist at the Allen Institute for AI. Her research focuses on Natural Language Processing (NLP) and Machine Learning, particularly Large Language Models (LLMs), emphasizing data-centric approaches and ethical AI practices. She holds a Ph.D. from the University of Washington (2024) and a B.S. from Seoul National University (2018). Her work includes advancements in retrieval-based models, mixture-of-experts architectures, and data privacy in LLMs. Notable projects include FlexOlmo (flexible data use in LLMs) and OLMoE (open mixture-of-experts models). She has been recognized with the ACM Doctoral Dissertation Award Honorable Mention (2025) and WAGS/ProQuest Innovation in Technology Award. Recent articles highlight her contributions to reasoning models, data tracing (OLMoTrace), and scalable retrieval systems (MassiveDS). She leads the Berkeley NLP Group and collaborates with BAIR, exploring topics like model transparency and ethical data usage.

Qian LouView profile

Assistant Professor

• Deep Learning
• Computer Vision
• Natural Language Processing
• +3 more

Qian Lou serves as an Assistant Professor in the Department of Computer Science at the University of Central Florida and is an active member of the university's Cybersecurity and Privacy Cluster. His research program targets critical challenges in deep learning systems, specifically enhancing efficiency, privacy, and security for applications in computer vision and natural language processing. His academic foundation includes: Ph.D. in Computer Engineering from Indiana University, Bloomington M.S. in Computer Engineering from Indiana University Bloomington B.S. in Computer Science from Shandong University Lou's research spans deep learning methodologies with specialized focus on computer vision and natural language processing systems. His work integrates cybersecurity principles into machine learning architectures, particularly through privacy-preserving techniques and secure computational frameworks. This interdisciplinary approach bridges computer systems architecture with practical AI deployment challenges, emphasizing efficiency optimizations for resource-constrained environments. His scholarly recognition includes: 2018 AAMAS Best Paper Finalist 2016 AAMAS Best Demonstration Paper Finalist University of Southern California Merit Fellowship Professionally, Lou contributes extensively to the academic ecosystem through program committee service and peer review activities for leading conferences and journals in artificial intelligence and computer science. His industry experience at Samsung Research AI Center informs his applied research perspective and technology transfer approach. Within UCF's Cybersecurity and Privacy Cluster, Lou collaborates on cross-disciplinary initiatives addressing real-world security vulnerabilities in AI systems, working alongside researchers from engineering, data science, and policy domains to develop robust computational frameworks.

Veysel Murat İstemihan GençView profile

Professor

• Power Systems
• Transient Stability Assessment
• Machine Learning in Power Systems
• +7 more

Veysel Murat İstemihan Genç is a Professor in the Department of Electrical Engineering at Istanbul Technical University (ITU), College of Engineering. His research is centered on modern power systems, with a focus on transient stability, cybersecurity, and integration of renewable energy sources. He actively leads multiple research projects and supervises graduate students in advanced power system technologies. Research Interests: His work spans key areas including transient stability assessment, machine learning applications in power systems, cyber-attack detection in AGC systems, and dynamic security evaluation under high renewable penetration. He employs cutting-edge techniques such as ensemble learning, deep neural networks, and hybrid optimization algorithms. Publication Trends: Recent publications (2023–2025) highlight a strong trend toward integrating AI and machine learning for real-time transient stability prediction, cybersecurity in distributed energy systems, and performance optimization of solar and wind-integrated grids. His work frequently addresses challenges in low-inertia systems and false data injection attacks. Scientific Projects: Strengthened Machine Learning-Based Dynamic Security Evaluation for Transient Stability under False Data Injection Attacks (BAP, 2025) Analysis and Control Methods for Stability of Large-Scale Low-Inertia Power Systems (BAP, 2023–2024) Dynamics Security Evaluation of Renewable-Rich and Cyber-Attacked Power Systems (BAP, 2022–2024) Risk-Based Stability Assessment and Corrective Control Methods in Power Systems (BAP, 2019–2022) Wide-Area Monitoring Protection and Control System Design Using Advanced Signal Processing and Machine Learning (TÜBİTAK, 2018–2020) Advising and Grants: He is the principal investigator (PI) on multiple funded research projects from BAP and TÜBİTAK, indicating strong grant acquisition and leadership. His supervision of 27 ongoing theses reflects an active role in mentoring graduate students in electrical engineering and power systems. Labs and Teams: While specific lab names are not mentioned, his projects suggest leadership in a research group focused on smart grid technologies, AI-enabled power system security, and renewable integration at Istanbul Technical University.

Rebecca LissnerView profile

Assistant Professor

• U.S. Foreign Policy
• Grand Strategy
• National Security
• +12 more

Rebecca Lissner is a Senior Fellow for U.S. Foreign Policy at the Council on Foreign Relations (CFR) and a former professor at the U.S. Naval War College, where she served in the Strategic and Operational Research Department within the College of Operational and Strategic Studies. She has held senior national security roles in the Biden-Harris administration, including Deputy Assistant to the President and Principal Deputy National Security Advisor to the Vice President, advising on U.S.-China competition, Ukraine, AI, and climate policy. AB in Social Studies, Harvard University MA and PhD in Government, Georgetown University Lissner’s research focuses on American grand strategy, the future of the liberal international order, and U.S. global leadership. She explores how the United States can adapt its foreign policy to maintain influence amid rising powers and domestic political shifts. Her work emphasizes reimagining, rather than restoring, the post-World War II international system through strengthened alliances, democratic coalitions, and strategic innovation. Her recent publications reveal a consistent focus on grand strategy, U.S. foreign policy after Trump, NATO and European security, and the evolving liberal order. These works span journals like Foreign Affairs , Foreign Policy , and Washington Quarterly , highlighting her expertise in strategic planning, crisis management, and alliance politics. Themes include the resilience of international institutions, the need for strategic coherence, and the importance of proactive leadership in shaping global norms. Scientific awards and honors are not explicitly mentioned in the provided texts. Lissner has advised national security leadership and presidential campaigns, including those of Biden, Harris, and Clinton. She has contributed to major policy documents such as the Biden administration’s National Security Strategy and led contingency planning on Russia-Ukraine. Her media engagement includes commentary for CNN, MSNBC, BBC, and writing in The Atlantic and Washington Post , demonstrating broad influence in both policy and public discourse. She has held research affiliations at Georgetown University, Perry World House at the University of Pennsylvania, Yale’s International Security Studies, and Columbia’s Saltzman Institute, reflecting a robust academic network. While no formal lab or team is specified, her collaborative work with Mira Rapp-Hooper and leadership in government strategy teams indicate active participation in high-level research and policy teams.

• Academic Writing
• Occupational Career Development
• Higher Education Policy
• +3 more

Montse Castelló Badia is a Full Professor at the Blanquerna School of Psychology, Education and Sports Sciences (Universitat Ramon Llull), leading the Psychology and Speech Therapy Department. She serves as Principal Investigator (PI) of the SINTE research group (Seminari Interuniversitari sobre Identitat i Noves Trajectòries Educatives) and collaborates in multiple interdisciplinary projects focusing on academic and non-academic career pathways. Her research interests center on academic writing practices, professional trajectories of researchers, and educational policy analysis. Key themes include PhD holders' transition to non-academic careers, workplace wellbeing, and legislative frameworks impacting higher education systems, particularly in Spain and Latin America. Recent work explores burnout and engagement dynamics among PhD professionals in non-academic sectors, leveraging mixed-methods approaches. Her publications analyze disciplinary variations in career outcomes and propose pedagogical interventions for ethical AI use in academic writing. Castelló Badia has secured 24+ research grants since 2003, including national (Ministerio de Ciencia) and institutional projects. She co-leads initiatives investigating employers' perceptions of PhD candidates and publishes extensively in indexed journals like Higher Education and Studies in Higher Education . Her work is anchored in the SINTE research group, fostering collaborations across universities to address evolving educational trajectories and identity formation in academic contexts.

Panayiotis KoliosView profile

Assistant Professor

• Autonomous Systems
• Intelligent Transportation Systems
• Cyber-Physical Systems
• +7 more

Panayiotis Kolios is an Assistant Professor at the Department of Computer Science, University of Cyprus (UCY). Previously, he served as a Research Assistant Professor at the KIOS Research and Innovation Centre of Excellence (2013–2024) and a Visiting Lecturer at UCY. He holds a BEng and PhD in Telecommunications Engineering from King’s College London (2008 and 2012, respectively). His research focuses on networked intelligent systems, emergency management using AI and UAV technologies, and cyber-physical systems. Education: BEng in Telecommunications Engineering, King’s College London, 2008 PhD in Telecommunications Engineering, King’s College London, 2012 Research Interests: His work centers on autonomous systems, intelligent transportation, and emergency management. Key areas include AI-driven disaster response, UAV-based surveillance, and algorithmic optimization for critical infrastructure. He develops solutions for real-time situational awareness and decision-support in emergencies. Recent work trends show a focus on multi-UAV coordination, disaster management platforms (like AIDERS), and AI applications in emergency response. His team’s 2023 win in the Cooperative Aerial Robots Inspection Challenge highlights advancements in UAV inspection algorithms. Scientific Awards: First Prize in Cooperative Aerial Robots Inspection Challenge (CDC 2023) Grants and Advising: He has secured over €40 million in EU and industrial grants, leading projects like PREDICATE, SWIFTERS, and AIDERS. His team advises on emergency response strategies and has trained first responders through EU-funded programs such as the Exchange of Experts training. Labs and Teams: He leads the Security and Emergency Response Group at KIOS CoE and established the Cyprus Civil Defence Aerial Observation Unit. His team collaborates with institutions like the Cyprus Police and Fire Service to operationalize UAV technologies in disaster scenarios.

Kathleen M. CarleyView profile

Professor

• Network Science
• Social Cybersecurity
• Computational Social Science
• +4 more

Kathleen M. Carley is a full professor at Carnegie Mellon University's School of Computer Science with courtesy appointments in Engineering and Public Policy, Heinz School, and Electrical and Computer Engineering. As director of the Center for Computational Analysis of Social and Organizational Systems (CASOS) and the Center for Informed Democracy and Social-Cybersecurity (IDeaS) , she leads interdisciplinary research at the intersection of network science, cognitive modeling, and cybersecurity. Ph.D. in Sociology from Harvard University SB degrees in Economics and Political Science from MIT Her research focuses on Dynamic Network Analysis (DNA) and Social-Cybersecurity (SC) , developing tools like ORA (network analysis), AutoMap (semantic mining), Construct (influence simulation), and BotHunter (bot detection). She has over 400 publications and 15+ active research projects addressing disinformation, cognitive security, and organizational resilience. Recent work examines LLM-powered bots , multi-platform misinformation dynamics , and public health analytics . As an IEEE Fellow, she contributes to standards in computational social science while teaching courses on network analysis and complex socio-technical systems.

• Political Science
• International Relations
• Totalitarianism Studies
• +3 more

Henrique Varajidás is a lecturer at Universidade Lusófona (Lusophone University), with a focus on political science and historical analysis of totalitarianism. He holds a Licenciatura in Political Science and International Relations, a PhD in the same field with specialization in security and defense, and a Master’s in Law focused on cross-cultural business practice. Licenciatura: Political Science and International Relations PhD: Political Science and International Relations (Security and Defense) Master: Law (Cross-Cultural Business Practice) His research primarily examines totalitarianism through comparative frameworks, analyzing regimes like Nazi Germany, Stalinist USSR, and Khmer Rouge Cambodia. Key themes include: Historiographical methodology in totalitarian studies Counterfactual analysis of political violence Racial sciences in early Nazi ideology Philosophical foundations of authoritarian power Foreign policy villainization techniques Ends vs means in totalitarian governance His publications reveal a strong focus on circular causality in regime analysis, Kantian moral philosophy, and technological implications in authoritarian systems. Awards and recognition are not explicitly mentioned in available sources. Varajidás has advised students on topics related to totalitarianism and regime analysis. His work appears in journals like Frontiers in Political Science and Práticas da História . He maintains contact via email at hen***@ulusofona.pt .