Jack Doerner is an Assistant Professor in the Department of Computer Science at the University of Virginia, within the School of Engineering and Applied Science. He earned his Ph.D. in Computer Science from Northeastern University in 2022 and holds B.S. and B.A. degrees in Computer Science and Studio Art from the University of Virginia (2015). His research focuses on the theoretical and applied aspects of cryptography, with core interests in secure multiparty computation (MPC), threshold signatures, zero-knowledge proofs, and oblivious RAM. His work aims to design efficient, secure, and practical cryptographic protocols, particularly for applications in cryptocurrency and secure computation. His most influential work is a series of highly efficient threshold ECDSA protocols, developed with collaborators like abhi shelat and Yashvanth Kondi. These protocols are secure under standard cryptographic assumptions and have achieved remarkable performance, being implemented by major companies like Coinbase, Visa, and Web3Auth. His research also includes significant contributions to MPC with identifiable abort, coin tossing extension, and the foundational theory of ideal signature functionalities. Best Paper Award, ACM CCS 2017 He has advised research and collaborated extensively, leading to numerous publications in top venues like IEEE S&P, ACM CCS, Eurocrypt, and Crypto. His work often bridges theory and practice, resulting in open-source implementations and widespread adoption. He has no known lab or team name mentioned, but his research is conducted within the broader context of the University of Virginia's computer science research community.
Frank Piessens is a Professor in the Department of Computer Science at Katholieke Universiteit Leuven (Belgium). His work bridges software security, systems security, formal methods, and programming languages. He actively investigates information flow security, with a dual focus on attack techniques and defense mechanisms. Current role: Professor at KU Leuven (Belgium) Research areas: Software Security, System Security, Formal Verification, Programming Languages Research Interests: His defense work includes formal verification for C-like languages, memory safety hardening, micro-architectural side-channel mitigation, and embedded security architectures. On the attack side, he studies transient execution attacks, memory safety exploits, and controlled channel attacks. Recent Article Trends: His publications span secure compilation techniques (2025), control-flow linearization (2024), functional reactive programming (2021-2014), formal verification (2020-2016), and hardware/software co-design security (2022). Keywords cluster around Computer Science , Security , and Programming Languages .
Jasmine Gnanadurai serves as an Associate Professor in the Department of Electrical Engineering & Computer Science at George Fox University's College of Engineering. She teaches a range of courses including Introduction to Computer Science, Software Engineering, Servant Engineering, and Senior Design. Her office is located in Wood-Mar 222, where she holds regular office hours for student consultation. Dr. Gnanadurai's educational background includes: Ph.D. in Computer Science (2017) from Anna University, Chennai, India M.Phil (2006) from Bharathidasan University, Tiruchirappalli, India M.C.A. (2000) from Bharathidasan University, Tiruchirappalli, India B.Sc. in Computer Science (1997) from Bharathidasan University, Tiruchirappalli, India Dr. Gnanadurai's research spans multiple cutting-edge domains in computer science and engineering. Her work in wireless sensor networks has focused on optimization algorithms for zone-based networks, particularly using techniques like DBSCAN clustering and particle swarm optimization. She has made significant contributions to cloud computing architecture, especially in resource allocation and load balancing for peer-to-peer networks. Her expertise extends to machine learning applications across diverse fields including agriculture productivity, student feedback analysis, and crowd behavior recognition. Her recent publications demonstrate a strong interdisciplinary approach, bridging computer science with practical applications in healthcare, education, smart cities, and transportation. She has published extensively on deep learning techniques for EMG-based hand gesture recognition, blockchain applications for electric vehicle charging infrastructure, and immersive technologies for educational settings. These works reflect her commitment to addressing real-world challenges through technological innovation. Dr. Gnanadurai actively contributes to the engineering education mission at George Fox University through multiple channels. She teaches foundational computer science courses, advanced software engineering, and participates in the university's distinctive Servant Engineering program where students develop solutions to humanitarian needs. She also guides senior engineering students through their capstone Senior Design projects, which partner with industry sponsors to solve real-world problems. As part of the College of Engineering, Dr. Gnanadurai works within interdisciplinary teams that collaborate on projects addressing humanitarian needs through the Servant Engineering program. This program connects students with community partners to develop engineering solutions that serve vulnerable populations, reflecting the university's Christian mission of service. Her involvement in Senior Design connects students with industry partners including Xerox, Intel, Garmin, and numerous regional companies, providing students with valuable real-world experience.
Dominik Moritz is an Assistant Professor at the Human-Computer Interaction Institute (HCII) of Carnegie Mellon University and Machine Learning researcher at Apple. He leads the Data Interaction Group and develops systems for interactive data visualization. Ph.D. in Computer Science from University of Washington (2019) B.S. in Computer Science from Hasso Plattner Institute (2013) His research focuses on: Human-Centered Machine Learning Data Visualization Toolkits Interactive Systems Design Accessibility in Visual Analytics Scalable Web-Based Visualization Recent publications address visualization design knowledge formalization (Draco), cross-filtering frameworks (Mosaic), and accessibility evaluation (Chartability). He has received Best Paper Honors at VIS and EuroVis conferences. Professional Collaborations: Co-founder of Vega-Lite visualization grammar Collaborations with Jeff Heer, Bill Howe, Jock MacKinlay Projects with Microsoft Research and Google Research
Nick Nikiforakis is an Associate Professor in the Department of Computer Science at Stony Brook University, with an affiliation to the National Security Institute. His research focuses on web security, privacy, software security, and intrusion detection, with particular emphasis on analyzing online ecosystems, domain squatting, honeypot deployment, and client-side defense mechanisms. He completed his PhD in Computer Science at KU Leuven (Belgium), and holds an MSc in Parallel and Distributed Systems and a BSc in Computer Science from the University of Crete, Greece. His work has been funded by NSF and ONR grants, including projects addressing vulnerability scanning, social engineering defenses, and mobile browser security. Nikiforakis' awards include a Distinguished Paper Award at NDSS 2017 and a Best Paper Award at ISC 2014. He teaches courses CSE 508 (Computer Security), CSE 509 (Advanced Topics in Security), and CSE 361 (Data Structures and Algorithms). His research explores cutting-edge threats like blockchain naming system abuse, cryptocurrency scams, and adversarial AI-driven misinformation campaigns.
Brad Karp is a Professor of Computer Systems and Networks at University College London (UCL) , holding this position since 2005. His career spans multiple institutions and roles, including a Senior Lecturer (2005-2014) and Reader (2007-2014) at UCL, Adjunct Assistant Professor at Carnegie Mellon University , and Senior Staff Researcher at Intel Research Pittsburgh . He earned his PhD in Computer Science from Harvard University (2000) , preceded by an M.Sc. (1995) and B.Sc. (1992) in the same field from Harvard and Yale respectively. Research Interests : Systems security (operating systems, web browsers, application security) Wireless networking (multi-antenna capacity, interference management) Network routing (robustness, low-latency protocols) Distributed systems (DHTs, sensor networks) Scientific Contributions focus on optimizing network performance, enhancing security architectures, and developing practical routing algorithms. His work on gradient compression (2024) and low-latency routing topologies (2018) demonstrates continued relevance in network design. Earlier publications like OpenDHT (2005) and Polygraph (2005) established foundational contributions in distributed systems and security. Awards & Recognition : Royal Society-Wolfson Research Merit Award (2005-2010) Best Paper Award (Usenix 2014) Professional Activities include program committee roles for ACM SIGCOMM (2009, 2011-2017), HotNets (2008-2017), and NSF review panels. He has examined PhD theses at the University of Cambridge (2010) and contributed to the HotNets Steering Committee (2009-2014).
Jay Aikat is the Vice Dean of the School of Data Science and Society at the University of North Carolina at Chapel Hill since July 2022, and a Research Professor in the Department of Computer Science. She previously served as Chief Operating Officer at RENCI (2016–2022) and held leadership roles in IT at UNC-Chapel Hill’s School of Information and Library Science. Aikat holds a Ph.D. in Computer Science from UNC-Chapel Hill, with earlier degrees in Electrical and Electronics Engineering and Computer Science. Her research focuses on experimental methods in networking, Internet traffic modeling, cloud security, and data science education. Notable contributions include work on airborne network topology management, cloud computing security frameworks, and pedagogical innovations in big data training. She has collaborated with institutions like NIEHS (National Institute of Environmental Health Sciences) and contributed to national-scale research infrastructure projects through GENI and COMBINE initiatives. Her publication trends reflect deep engagement with network experimentation, cybersecurity challenges in cloud environments, and scalable solutions for dynamic wireless systems. Aikat has also authored foundational work on web traffic evolution and protocol benchmarking, emphasizing reproducible methodologies in networking research. Her professional trajectory includes bridging academic research with applied IT leadership, fostering interdisciplinary collaborations across computer science, environmental health, and data science domains. Current efforts focus on expanding data science education and driving innovation through the School of Data Science and Society.
Robbert van Renesse is a Professor in the Department of Computer Science at Cornell University, Ithaca, NY. He is a member of the Systems and Networking group. His research focuses on distributed systems, particularly fault tolerance and scalability. He co-authored Chain Replication and contributed to projects like Harmony (a model checker for concurrent systems) and EGOS (a minimalist operating system). He has held roles such as Chair of ACM SIGOPS and Editor-in-Chief for ACM Transactions on Computing Systems. His work spans academic contributions, industry collaborations (e.g., Exotanium, Inc.), and over 30 conference/workshop papers annually since the 1990s. Education: M.Sc. (1985) and Ph.D. (1989) in Mathematics/Computer Science from Vrije Universiteit Amsterdam under Andrew Tanenbaum. Professional experience includes roles at AT&T Bell Labs, Cornell since 1991, and co-founding companies like Reliable Network Solutions and D.A.G. Labs. Research interests include blockchain technology (e.g., Bitcoin-NG for scalability), consensus protocols (BFT and Turtle consensus), and system frameworks like Ovid and Escher. His publications emphasize distributed algorithms, replication, and security. He advises over 30 Ph.D. students and co-founded Exotanium, Inc. in 2018. Notable contributions: Chain Replication (OSDI 2004), Horus toolkit (commercialized as Sphinx), and foundational work in Amoeba OS. His recent work explores metastable failures and programmable memory segments.
Frank Piessens is a Professor in the Department of Computer Science at KU Leuven, Belgium. His work spans both offensive and defensive aspects of software and systems security, with a focus on formal verification, programming languages, and security architectures. He has served as program chair for major security conferences like POST 2016, IEEE Euro S&P 2018-2019, and IEEE SecDev 2021-2022. Software Security Systems Security Formal Methods Programming Languages Information Flow Security His research bridges theoretical and practical domains. On the defensive side, he has advanced formal verification for C-like languages, memory safety hardening, and micro-architectural side-channel mitigation. On the attack side, he has contributed to transient execution and memory safety exploitation frameworks. His recent work (2024) explores compiler support for control-flow linearization using architectural mimicry, while earlier publications (2021-2014) cover functional reactive programming, secure compilation, and dependently typed verification. Frank has consistently engaged with academic communities, serving on program committees for ACM CCS, Usenix Security, and IEEE Security & Privacy. He co-authored key papers in venues like POPL, ICFP, and PriSC. His lab, Distrinet, focuses on distributed systems and security research. No explicit details about scientific awards or student advisement are present in the provided data.
Gary Allen is a Senior Lecturer in the Department of Computer Science at the School of Computing and Engineering, University of Huddersfield. He is an active member of the Centre for Planning, Autonomy and Representation of Knowledge, the Centre for Sustainable Software Engineering, the Centre for Sustainable Computing, and an affiliate of the Centre for Autonomous and Intelligent Systems. He holds a PhD in Software Development Methods for Educational Use and has been with the university since 1990, first as a research assistant and then as a full-time lecturer since 1995. His research interests include: Software Engineering Distributed and Client-Server Systems Aspect-Oriented Programming Object-Oriented Analysis and Design Design Patterns Java Programming and JavaSpaces Software Engineering Education Integrated Project Support Environments His recent publications reflect a strong focus on software quality, empirical evaluation of programming paradigms, and educational applications of software engineering. He has contributed to studies on automated testing adoption, hybrid programming systems, and UML extensions, demonstrating a consistent thread in software design, modularity, and educational technology. His scientific contributions are aligned with sustainable computing and autonomous systems, supporting UN Sustainable Development Goals. He actively participates in peer-review for journals such as the Journal of Software: Evolution and Process and international conferences. He supervises PhD students and has been involved in multiple research supervision activities. His work integrates teaching and research, particularly in practical and pedagogical aspects of computer science. He is also engaged in activities related to knowledge representation and intelligent systems through his centre affiliations.
Giulia Fanti is an academic researcher affiliated with Carnegie Mellon University in the Computer Science Department . Her research focuses on privacy-preserving technologies, blockchain systems, and machine learning mechanisms, with significant contributions to federated learning, differential privacy, and cryptocurrency network design. Key Research Areas : Privacy in blockchain, Generative Adversarial Networks (GANs), Federated Learning, Game Theory applications to decentralized systems. Recent Publications : Her work explores liquidity provisioning in decentralized finance, truncated consistency models for image generation, and private data valuation frameworks. She has contributed to venues like NeurIPS, ICLR, and SIGMETRICS, often addressing privacy-utility tradeoffs.
Antonio Garrido del Solo is a Professor in the Department of Computer Systems at the School of Computer Engineering, University of Castilla-La Mancha (UCLM). He has been affiliated with UCLM since 1986, becoming a Catedrático (Full Professor) in the area of Computer Architecture and Technology (ATC) in 2003. He served as Director of the School of Engineering at UCLM (2000-2008), Director of the Information Technology section at the Regional Development Institute (IDR) of UCLM (1996-2000), and Deputy Director of the Informatics Department at UCLM (1993). Professor Garrido earned his Licentiate in Physical Sciences from the University of Granada in 1986 and his Doctorate from the University of Valencia in 1991. Since 1993, he has been the co-founder of the High-Performance Networks and Architectures (RAAP) research group at UCLM, which currently includes 23 doctors. His academic leadership includes heading the Computer Architecture and Technology area from 2008 to 2021. His research interests span wireless networks, multimedia communications, video transcoding, software-defined networking, edge computing, and energy efficiency in networks. Professor Garrido has focused on digital image processing, broadband video transmission, video transcoding, and multimedia data transmission over wireless networks. His recent work demonstrates a strong emphasis on software-defined networking applications for wireless LANs, particularly in multicast transmission, load balancing, and energy efficiency. His publication record shows a clear evolution from video transcoding and wireless communications to software-defined networking and edge computing. The past decade reveals a significant shift toward SDN-based solutions for wireless networks, with particular attention to quality of service, resource allocation, and energy efficiency in enterprise WLAN environments. His work often combines theoretical networking principles with practical implementations for real-world applications. Professor Garrido has been deeply involved in university quality evaluation since 2000, serving as an external evaluator for Spain's National University Quality Evaluation Plan (PNECU), ANECA's Evaluation Plan (PEI), and multiple ANECA programs including VERIFICA, MONITOR, and ACREDITA. Since 2018, he has been a member of the EURO-INF seal commission, which he has chaired since 2022. He has also collaborated with regional quality agencies (ACCUEE, AQUIB, DEVA) in evaluating university programs and faculty. His research has been supported by numerous competitive research projects, including MECODIVI (2018-2021), excellence networks in computer architecture and advanced communications (2017-2019), and multiple projects focused on multimedia content delivery, wireless sensor networks, and energy management systems. He has led the RAAP research group for nearly three decades, securing funding from both regional and national sources. Professor Garrido co-founded the RAAP (High-Performance Networks and Architectures) research group at UCLM in 1993, which has grown to include 23 doctors. The group has maintained a consistent research focus on network architectures, wireless communications, and multimedia systems, while adapting to emerging technologies like software-defined networking and edge computing. Their collaborative approach has resulted in numerous publications in top-tier networking journals and conferences.
Dr. Xiao Su is Associate Dean for Graduate Studies and Research at the Charles W. Davidson College of Engineering, San José State University, and a faculty member in the Computer Engineering Department. She joined SJSU in Fall 2002 after working at Inktomi Corporation. Dr. Su holds a Ph.D. from the University of Illinois, Urbana-Champaign (2001) and teaches courses in networking and security. Her research spans computer networking, multimedia communications, network security, and cloud computing. She has secured over $2.5M in research funding from NSF, NASA, Intel, and HP. Major grants include a $400K NSF CAREER Award (2006-2012) for multimedia streaming research and a $1.5M NASA grant for airport traffic optimization. Publications show strong focus on cloud-based media distribution, peer-to-peer networks, and security systems. Recent work emphasizes cloud storage optimization, mobile computing applications, and secure video transmission. Her 50+ publications demonstrate consistent innovation in distributed systems design and multimedia networking. Applied Materials Faculty Award for Excellence in Teaching (2012) College of Engineering Faculty Award for Excellence in Scholarship (2010) National Science Foundation CAREER Award (2006) As principal investigator, she has led 8+ major grants establishing research infrastructure and curriculum enhancements. She serves on NetApp's Academic Alliance advisory board and maintains active industry collaborations in Silicon Valley. A senior member of IEEE and ACM, Dr. Su has chaired technical committees for IEEE ICME and other international conferences.
Dr. Muhammad Asad is a Lecturer in Computer Science at the School of Engineering, Computing and Mathematics. With 13+ years of research experience, his work focuses on federated learning, wireless communication systems, and IoT network optimization. Primary Role: Lecturer in Computer Science Key Research Areas: Federated Learning, Wireless Communication, and IoT Security His research spans communication-efficient AI systems, blockchain-integrated learning frameworks, and energy optimization in sensor networks. Recent work includes security-enhanced federated learning protocols for vehicular networks and healthcare analytics. Publications (2018-2024) demonstrate consistent contributions to fields including: Privacy-preserving machine learning IoT-oriented network architectures Blockchain-based security systems Medical imaging diagnostics
Professor Alan Wee-Chung Liew serves as Head of School at Griffith University's School of Information and Communication Technology, Australia. He joined Griffith University in 2007 after holding positions as Assistant Professor at Chinese University of Hong Kong and Senior Research Fellow at City University of Hong Kong. Professor Liew's research spans Artificial Intelligence, Machine Learning, Medical Imaging, Computer Vision, and Bioinformatics . His work focuses on developing AI solutions for healthcare applications, image analysis, and pattern recognition problems. He leads methodological innovations in machine learning algorithms while maintaining strong connections to real-world applications. His recent publications demonstrate a clear trend toward interdisciplinary AI applications, particularly in medical imaging, healthcare analytics, and trustworthy AI systems. The research shows increasing focus on explainability, privacy preservation, and practical deployment of AI solutions in critical domains. Professor Liew has received significant recognition including: Fellow of the Queensland Academy of Arts and Sciences Fellow of the Australia Computer Society Senior member of IEEE (USA) Stanford University's World's Top 2% Scientists (Computer Science: AI & Image Processing) He actively supervises numerous PhD students across diverse AI topics including medical imaging, graph neural networks, and trustworthy AI. His research is supported by substantial funding from government agencies including ARC, NHMRC, and international collaborations. Professor Liew co-leads the AI4Health lab and the TrustAGI lab , which focus on developing ethical, reliable, and safe AI technologies with strong industry and hospital partnerships.
