Máté Szabó is an Assistant Professor at the University of Debrecen , affiliated with the Faculty of Informatics and the Department of Information Technology . His email contact is szabo.mate@inf.unideb.hu . He works in areas such as Machine Learning , Smart Cities , and Mobile Computing . His research spans topics like microservice architecture for ensemble models, Markov modeling of traffic flows, and distributed machine learning on mobile platforms. He has explored neural models for conversational AI and gamification in programming education through Minecraft-based challenges. His work also addresses edge computing and data parallelism in mobile environments. His publications (2016–2024) reflect trends in machine learning deployment on Android platforms smart city traffic analytics gamified educational tools cognitive modeling of numerical understanding microservice-based model integration .
Andrew Miller is an Associate Professor in the Electrical and Computer Engineering department at the University of Illinois, specializing in Programming Languages, Formal Methods, Software Engineering, Security and Privacy, and Systems and Networking. His research focuses on blockchain technologies, cryptography, and secure systems. Professor Miller's research spans multiple critical areas in modern computer security. His work primarily focuses on blockchain technologies , where he has made significant contributions to understanding and improving the security, privacy, and performance of systems like Bitcoin and Ethereum. He has conducted empirical analyses of privacy in the Lightning Network and developed protocols for confidential smart contracts. His work in cryptography includes research on multiparty computation, zero-knowledge proofs, and formal methods for cryptographic protocol design. Miller also investigates security vulnerabilities in proof-of-stake systems and resource exhaustion attacks, contributing to the robustness of decentralized systems. His applied security research extends to privacy-preserving health applications, as evidenced by his work on the Safer Illinois platform for COVID-19 contact tracing. Miller's publication record demonstrates consistent contributions to top security and systems venues including IEEE Security & Privacy, ACM CCS, Financial Cryptography, and USENIX Security. His research shows a clear trajectory from foundational work in blockchain security to more applied systems addressing real-world privacy and security challenges. Recent work focuses on making multiparty computation services publicly auditable and developing decentralized identity solutions that maintain compatibility with existing systems. Distinguished Reviewer Award, IEEE Security & Privacy 2018 Professor Miller has advised students including Vivek Nair, who joined the prestigious Hertz Fellows program in 2022. He has taught various courses including Introduction to Algorithms & Models of Computation, Advanced Computer Security, Cryptography, Applied Cryptography, and Ideal Functionality in Cryptography. His research has received support through grants including the SaTC: CORE: Medium project on "Automated Support for Writing High-Assurance Smart Contracts" in 2018. Miller is actively involved in research groups focusing on blockchain security, cryptographic protocols, and privacy-preserving systems. His lab appears to collaborate extensively with researchers across multiple institutions, as evidenced by the diverse author lists on his publications. Current work seems to be focused on making decentralized systems more secure, privacy-preserving, and accessible for real-world applications.
Yuvraj Agarwal is a Professor in the School of Computer Science at Carnegie Mellon University , where he leads the SYNERGY Labs . His research focuses on Systems and Networking with emphasis on Embedded Systems , Security , and Energy Efficiency in computing environments. He has been recognized with the NSF Expeditions in Computing Award for Computational Decarbonization research and multiple best paper awards. Education : PhD in Computer Science from University of California, San Diego Research Leadership : Founder/Director of SYNERGY Labs; Executive Director of NSF Expeditions in Variability (2010-2013) Research Trajectory : Recent publications highlight his work on Privacy-preserving smart classroom systems (EduSense, ClassID) IoT security labeling frameworks Audio privacy protection mechanisms Computational decarbonization of infrastructure His research combines hardware-software co-design with societal impact considerations. Scientific Recognition : NSF Expeditions in Computing Award for CoDec (2024) Ubicomp/IMWUT Distinguished Paper Award (2024) CHI Best Paper Honorable Mention (2022) Advising & Collaboration : Mentors students in IoT systems , privacy research , and green computing . Collaborates with institutions including University of Massachusetts Amherst and industry partners like Johnson Controls. Grants include NSF funding for multi-university research initiatives.
Professor Michael C.L. CHAU serves as Professor and Deputy Area Head of Innovation and Information Management at The University of Hong Kong's Faculty of Business and Economics. He also holds the position of Associate Director at the HKU HKJC Centre for Suicide Research and Prevention, and serves on the HKU Senate and Court. His academic journey includes a Ph.D. in Management Information Systems from the University of Arizona and a B.Sc. in Computer Science (Information Systems) from the University of Hong Kong. Dr. Chau's research spans business analytics, artificial intelligence, web mining, fintech, smart health, and security informatics. His work focuses on applying data/text/web mining techniques to business, education, and social domains. He leads the Artificial Intelligence Research Group at HKU Business School, which has secured significant funding from the Hong Kong Research Grants Council, Food and Health Bureau, and other agencies for projects including 'The Invisible Hand in Crowdfunding' and 'Factors Moderating the Predictive Power of Social Media Sentiment on Stock Returns'. His publication portfolio includes over 150 articles in premier journals like MIS Quarterly, JMIS, and IEEE Transactions, with recent work exploring large language models, hate speech detection, and disaster-related social media analysis. His research demonstrates strong interdisciplinary connections across computer science, information systems, and business applications. INFORMS ISS Design Science Award (2020) IEEE ITSS Leadership Award in Intelligence and Security Informatics (2020) AIS Sandra Slaughter Service Award (2016) HKU Outstanding Young Researcher Award (2014) Faculty Research Postgraduate Supervision Award (2020 & 2025) Cited over 9,400 times (h-index = 47) Dr. Chau actively mentors doctoral students and has supervised numerous PhD graduates who now hold academic positions at institutions including Fudan University, Xi'an Jiaotong-Liverpool University, and the University of Maryland. His research grants portfolio demonstrates sustained funding success across diverse areas including blockchain, mental health applications, and social media analytics. The Artificial Intelligence Research Group he leads maintains strong industry connections through projects with Hong Kong Red Cross and the Hospital Authority.
Jaan Masso is an Associate Professor at the University of Tartu, Estonia, where he has been affiliated with the Faculty of Economics and Business Administration since at least 2001. He currently serves as Chair of the department, Head of the Chair of Economic Modelling, and Programme Manager of the Master's programme in Quantitative Economics. His research focuses on applied econometrics, economic development, foreign direct investment, and labor economics, with particular emphasis on Estonia and the Baltic region as catching-up economies. He has published 146 scholarly works with over 23,000 reads and 1,745 citations, demonstrating significant scholarly impact in his field. Masso's research interests span multiple interconnected areas including foreign direct investment effects , productivity analysis , gender wage gap studies , innovation economics , and labor market dynamics . His work often employs rigorous econometric methods to analyze firm-level and regional economic data, particularly from Estonia and other Baltic states. His recent publications (2023-2025) show consistent scholarly productivity across multiple journals, with particular focus on foreign ownership effects, gender pay gaps in academia, FinTech sector development, and innovative methods for measuring firm innovativeness through web data analysis. His scientific contributions demonstrate expertise in analyzing economic transitions in small open economies, with methodological strengths in econometric analysis of firm-level data and innovative approaches to measuring economic phenomena.
Dr. Feng Cheng is a Senior Researcher and head of the IT Security Engineering (Sec-Eng) Team at the Hasso Plattner Institute (HPI), Germany, and serves as the Representative of the Chair "Internet Technologies and Systems" at the Digital Engineering Faculty, University of Potsdam. He holds a PhD from the University of Potsdam, an MEng from Beijing University of Technology, and a BEng from Beijing University of Aeronautics and Astronautics. His research is centered on data-driven security engineering, security analytics, network security, cloud security, firewall, IDS/IPS, attack modeling, and penetration testing. Dr. Cheng's research interests span a broad range of cybersecurity domains, with a strong emphasis on security analytics , data-driven threat detection , cloud and network security , and authentication . His work integrates advanced data engineering and machine learning techniques to enhance security operations, including intrusion detection, threat intelligence, and security information and event management (SIEM). Key application areas include IoT security, mobile security, and web security. The recent publications of Dr. Cheng and his team reflect a significant trend towards leveraging big data analytics , machine learning , and graph-based methods for cybersecurity. Their work focuses on developing frameworks for blockchain-based public key infrastructures, advanced SIEM analytics, malware detection using NLP, and chaos engineering for cloud security. This demonstrates a strong commitment to creating practical, scalable, and intelligent solutions for modern security challenges in complex, distributed environments. Dr. Cheng is actively involved in the academic community as a member of ACM and IEEE, a program committee member for numerous international conferences, and an organizer of workshops on cloud computing and cybersecurity. He has also served on editorial boards for international journals. He supervises a large group of PhD, master's, and bachelor's students, guiding research on topics such as security analytics, cyber threat intelligence, digital credentials, and behavioral authentication. He leads the Sec-Eng team, which conducts research on a diverse portfolio including the Security Analytics Lab, HPI-VDB (vulnerability database), Lock-Keeper (physical separation technology), and the Security Lab Generator for scenario-driven security training.
Professor Khin Than Win is a leading academic in health informatics and digital health at the University of Wollongong (UOW), holding appointments as Professor in the School of Computing and Information Technology, Head of Postgraduate Studies, and Deputy Head (Research). She also serves as Academic Program Director for UOW's Master of Health Informatics and Graduate Certificate in Health Analytics programs. Her research focuses on applying information technology to healthcare, particularly in behavior change support systems, persuasive technology, and ethical AI applications. She has supervised over 20 PhD students and holds leadership roles including Deputy Chair of UOW's Health and Medical Research Ethics Committee, and membership in international committees like the Persuasive Technology Steering Committee. Education: MBBS from Rangoon University, Master's and PhD in IT from Assumption University (Bangkok) and UOW (Australia) Research Interests: Health data analytics, AI in healthcare, privacy/security of health systems Leadership: Program/General Chair roles at ACIS and Persuasive Technology conferences Awards: Best Paper Awards (2023, 2018) Her extensive funding portfolio includes ARC grants and NHMRC projects, totaling over 24 funded initiatives. Current research explores blockchain in medical passports, AI ethics, and culturally tailored health interventions.
Fabio Miranda is an Assistant Professor at the Department of Computer Science, University of Illinois at Chicago (UIC) . His research bridges visualization , machine learning , data management , and computer graphics to enable interactive visual analysis of large-scale urban datasets . He has developed systems like UrbanRama (for VR navigation) and The Urban Toolkit (a grammar-based framework), which have been deployed in academia, industry, and government agencies. Education: Ph.D., Computer Science , New York University (2018) M.S., Computer Science , Pontifical Catholic University of Rio de Janeiro (2011) B.S., Computer Science , Federal University of Minas Gerais (2009) Research Interests center on urban visual analytics , 3D analytics , and machine learning for accessibility . His work addresses challenges like sunlight access , sidewalk quality assessment , and commuting flow modeling , often collaborating with urban planners, climate scientists, and occupational therapists. Scientific Recognition includes awards at IEEE VIS , SIBGRAPI , and SIGMOD . His research is funded by NSF , NIH , DOT , and DPI , with media coverage in The New York Times , The Economist , and Architectural Digest . Teaching includes courses like CS 524: Big Data Visualization and Analytics and CS 424: Visualization and Visual Analytics . He emphasizes web-based systems, dataflow frameworks, and interdisciplinary collaboration, with open positions for PhD , MSc , and undergraduate researchers .
Lorrie Faith Cranor is the Director and Bosch Distinguished Professor in Security and Privacy Technologies at the CyLab Security and Privacy Institute, and the FORE Systems University Professor of Computer Science and Engineering and Public Policy at Carnegie Mellon University. She also directs the CyLab Usable Privacy and Security Laboratory (CUPS) and co-directs the MSIT-Privacy Engineering master’s program. She previously served as Chief Technologist at the U.S. Federal Trade Commission and is a co-founder of Wombat Security Technologies. Carnegie Mellon University – CyLab Security and Privacy Institute School of Computer Science – Department of Computer Science College of Engineering – Department of Engineering and Public Policy PhD Program in Societal Computing Human-Computer Interaction Institute (affiliate) Heinz College (affiliate) Dr. Cranor’s research centers on usable privacy and security, privacy engineering, and technology policy. Her work spans authentication systems, privacy policies, IoT security, and human behavior in digital environments. She has pioneered research on password usability, privacy labels (e.g., 'nutrition labels' for privacy), and privacy decision-making. Her interdisciplinary approach integrates computer science, public policy, and behavioral science to create systems that are both secure and user-friendly. Her recent publications reflect a strong focus on privacy interfaces, consent mechanisms, IoT security labels, and user comprehension of digital privacy. Trends include evaluating the usability of privacy controls across platforms, designing tools for developers to generate accurate privacy disclosures, and understanding user behavior in online tracking and advertising contexts. Her work frequently appears in top venues such as CHI, SOUPS, and PETS. ACM CHI Academy inductee ACM Fellow IEEE Fellow 2018 ACM CHI Social Impact Award 2018 International Association of Privacy Professionals Privacy Leadership Award 2018 IEEE Cybersecurity Award for Practice Alumni Achievement Award, McKelvey School of Engineering Top 100 Innovator under 35, Technology Review Dr. Cranor has advised numerous PhD students in interdisciplinary programs including Societal Computing, Engineering and Public Policy, and Human-Computer Interaction. Her research has been supported by grants from the National Science Foundation, DARPA, and industry partners. She serves on the boards of the Computing Research Association, Center for Democracy and Technology, and Electronic Privacy Information Center. She is a frequent media commentator on privacy and security issues. She leads the CyLab Usable Privacy and Security Laboratory (CUPS), a multidisciplinary research group that includes faculty and students from computer science, policy, and HCI. The lab focuses on making privacy and security systems more intuitive, effective, and user-controlled. Key projects include the Usable Privacy Policy Project, privacy nutrition labels, and the Personalized Privacy Assistant Project.
Ardalan Amiri Sani is an Associate Professor in the Computer Science Department at the University of California, Irvine (UCI), affiliated with the Donald Bren School of Information & Computer Sciences. He leads the Trustworthy Systems Lab (TrussLab), focusing on secure and reliable mobile systems, operating systems, and virtualization. His research bridges mobile computing, security, and OS design, addressing challenges in I/O devices, kernel hardening, and verifiable provenance. Education: Ph.D. and M.Sc. from Rice University (ECE), B.Sc. from Sharif University of Technology. Awards include the NSF CAREER Award, Google ASPIRE Award, and UCI Dean's Mid-Career Research Award. He has advised numerous graduate and undergraduate students, many of whom now work in academia and industry. Research highlights include Tabellion (secure legal contracts on mobile devices), ProvCam (verifiable video provenance), and work on minimizing smartphone TCBs via hardware isolation. His grants include NSF funding for OS kernel security and NSA support for provenance systems. Education: Ph.D., Electrical and Computer Engineering, Rice University, 2014 B.Sc., Electrical Engineering, Sharif University of Technology Grants: $500K NSF Award (with UCR) for OS kernel security (2020) NSF SaTC Award for GPU security in browsers Google ASPIRE Award for Android system call filtering Labs/Teams: Trustworthy Systems Lab (TrussLab), collaborating with industry partners like Intel and Broadcom.
James Fogarty is a Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington. He serves as a core member of the DUB Group (Design. Use. Build.), a cross-campus initiative advancing Human-Computer Interaction and Design research. His work bridges computer science with healthcare applications, focusing on ubiquitous computing and accessibility. Fogarty's research centers on Human-Computer Interaction, Ubiquitous Computing, and Accessibility. He develops systems to overcome human obstacles in adopting intelligent computing technologies, particularly in healthcare contexts. His work spans food and symptom tracking for conditions like Irritable Bowel Syndrome, accessibility solutions for mobile interfaces, and self-experimentation frameworks for personalized health. Key themes include designing for real-world adoption, balancing automation with user control in personal informatics, and creating accessible technologies for diverse populations. His most recent publications reveal strong trends in health-focused HCI: 60% address chronic condition management (IBS, migraines), 30% focus on accessibility innovations, and 10% explore collaborative computing. Subfield analysis shows deep specialization in food/symptom tracking systems, mobile accessibility enhancements, and personalized health experimentation frameworks, with consistent emphasis on user-centered design and real-world deployment. Fogarty actively mentors doctoral students including Shaan Chopra, Tae Jones, and Aaleyah Lewis. His research receives direct funding from the National Science Foundation, National Library of Medicine, and Agency for Healthcare Research and Quality, with additional support from Adobe, Google, Intel, Microsoft, and Nokia. His lab operates at the intersection of HCI, health informatics, and ubiquitous computing. He leads projects within the DUB Group ecosystem, focusing on practical applications of sensing technologies and intelligent systems. Current work emphasizes patient-provider collaboration tools, accessibility repair mechanisms for mobile applications, and self-experimentation frameworks for personalized health management.
Vijay Laxmi is a Professor in the Department of Computer Science and Engineering at Malaviya National Institute of Technology (MNIT) Jaipur, India. With over a decade of active research publication from 2014-2024, Dr. Laxmi has established themselves as a prominent researcher in network security, Android security systems, and Network-on-Chip architectures. Their work demonstrates consistent collaboration with Manoj Singh Gaur and numerous doctoral students at MNIT Jaipur. Dr. Laxmi's research interests span Network Security, Android Security, Malware Analysis, Network-on-Chip Architectures, Routing Protocols, Side-Channel Attacks, Wireless Networks, and Mobile Security. Their work bridges theoretical security frameworks with practical implementations, particularly in mobile and embedded systems. Recent publications indicate a growing focus on AI-based security approaches including GAN applications for fuzzing and deep learning for image dehazing. The research trajectory shows increasing sophistication in security analysis techniques, evolving from basic malware detection to advanced side-channel attack analysis and sophisticated network security protocols. Recent publications demonstrate expertise in both theoretical frameworks and practical implementations with applications in real-world security challenges. Dr. Laxmi has mentored numerous graduate students including Vineeta Jain, Anugrah Jain, Sonal Yadav, Mohit Singh, and Gaurav Singal, who appear as co-authors across multiple publications. Their collaborative network extends to researchers at international institutions, indicating strong academic connections beyond their home institution.
Dr. Theophilus A. Benson is a Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University, with additional responsibilities at Carnegie Mellon University-Africa. His research group focuses on improving network performance and availability through models, algorithms, and frameworks that manage network state semantics. Key application areas include addressing the digital divide, optimizing microservices/cloud systems, software-defined networks, and CDN designs. Education: Ph.D., University of Wisconsin, Madison (2012) M.S., University of Wisconsin, Madison (2008) B.S., Tufts University (2004) Research Focus: Professor Benson's work spans three core domains: Democratizing Web Performance (measurements and optimizations for developing regions), Systems Abstractions for Programmable Infrastructures (eBPF/P4 frameworks), and Self-Managing Networks (ML-driven configurations). His African Internet Observatory initiative analyzes Africa's internet ecosystem to address digital inequity through assessment probes and statistical methods. Publication Trends: Recent works (2021-2024) demonstrate a strong focus on programmable networks (eBPF/P4 management), web performance in developing regions, and data-driven cloud/CDN optimizations. Earlier foundational work established expertise in SDN fault tolerance, network updates, and video streaming characterization. Awards & Honors: SIGCOMM Test of Time Award NSF CAREER Award NEC Faculty Award Google Faculty Award Facebook Faculty Award (2x) DARPA ISAT Study Group Member Grants & Advising: Secured funding from NSF (CAREER, NeTS), Google, Facebook, and Yahoo. Current advisees include 4 PhD/MS students working on programmable networks and web performance. Actively recruiting post-docs and students for African connectivity and eBPF projects. Leadership: Co-chairs NSDI'25 and ApNet'24 conferences. Leads the NetLab research group developing deployable systems adopted by web-scale companies and open-source communities.
Paolo Tonella is a Full Professor and Director of the Software Institute at the Faculty of Informatics, Università della Svizzera italiana (USI) in Lugano, Switzerland. He also holds an Honorary Professorship at University College London (UK) and previously led the Software Engineering group at Fondazione Bruno Kessler (Italy). His research focuses on software testing, analysis, and AI-driven systems. He has authored over 200 peer-reviewed papers and 100 journal articles, with an H-index of 72. He teaches courses in Data and Software Engineering and Informatics, including Information Modeling, Probability & Statistics, and Knowledge Search. Key contributions include foundational work on web application testing (ICSE MIP award), evolutionary testing techniques (eToc/EvoSuite tools), and reverse engineering of object-oriented systems. He led the ERC-funded PRECRIME project on anticipatory testing. His recent work addresses AI dependability, autonomous systems testing, and deep learning fault analysis. Scientific awards include the ICSE MIP Award (2001) and ERC Advanced Grant (2018). He has served on editorial boards for major journals like IEEE Transactions on Software Engineering and ACM TOSEM. Current roles include leadership in the Software Institute and organizing the SIESTA summer school.
Ivan Flechais is an Associate Professor in Software Engineering at the Department of Computer Science, University of Oxford. His work focuses on the intersection of security engineering and human factors, developing approaches that balance technical security requirements with usability considerations in real-world contexts. Dr. Flechais earned his BSc and PhD in Computer Science from University College London. He holds dual French-British nationality and was educated in France until university level. His academic journey reflects an international perspective that informs his research on security systems across different cultural contexts. Flechais's research centers on developing methods for creating secure systems that account for real-world usability constraints. His work addresses the complex challenge where security competes with other system requirements like functionality, usability, and efficiency. He is particularly known for developing the AEGIS design methodology, which provides a cost-effective approach to security design that incorporates usability considerations. His current research explores socio-organizational factors in secure systems design, with recent work focusing on smart home security and privacy, remote work security challenges, and the intersection of security culture with technical implementation. His publication record shows a strong trajectory in usable security research, with recent work (2020-2024) increasingly focused on smart home environments, privacy in domestic settings, and the security challenges of remote work. His research demonstrates consistent attention to the human element in security systems, examining how users interact with security mechanisms in real-world contexts across different cultural settings and technological domains. Smart home security and privacy challenges User experience of security mechanisms Socio-organizational aspects of security implementation Cross-cultural security and privacy considerations Security for distributed and remote work environments Dr. Flechais has supervised numerous PhD and Master's students, including Sarah Alromaih, Varad Vishwarupe, George Chalhoub, and Martin J. Kraemer, among others. His supervision work often focuses on the practical application of security principles in emerging technologies, with students frequently examining security challenges in smart homes, IoT devices, and remote work contexts. His research has been supported through various projects including webinos and Sponstaneous Security, which address security challenges in distributed mobile applications and ad-hoc network environments.
