Dr. Li Chen is an Alfred and Helen Lamson/BORSF Endowed Associate Professor in the School of Computing and Informatics at the University of Louisiana at Lafayette. She leads the CELESTIAL research lab, focusing on distributed systems and networking for machine learning and AI. Her research interests include federated learning, cloud computing, and resource optimization. Dr. Chen holds a Ph.D. from the University of Toronto and has received awards such as the NSF EPSCoR RII Track-4 grant and the BoRSF Endowed Professorship. Education: Ph.D. (2018), M.A.Sc. (2015) in Electrical and Computer Engineering from University of Toronto; B.Eng. (2012) in Computer Science from Huazhong University of Science and Technology. She also visited Hong Kong Polytechnic University (2013-2014). Research spans federated learning frameworks (e.g., SEAFL, FedClust), cloud resource scheduling (e.g., Hadar, HarmonyBatch), and applications in weather forecasting (e.g., MMST-ViT). Her work is supported by NSF, Louisiana BoRSF, and industry partners like XRMedix. Awards include the Alfred and Helen Lamson/BORSF Endowed Professorship (2024-2027), NSF EPSCoR grant (2024-2026), and best paper recognitions at IEEE conferences. She advises a diverse group of graduate students and has supervised alumni now in academia and industry. Teaching includes courses on computer networks, operating systems, and distributed systems. She organizes workshops and tutorials (e.g., 2023 Summer Tutorial on ML & Meteorology) and serves on conference committees such as INFOCOM and IWQoS.
ONG Soh Khim is a Professor in the Department of Mechanical Engineering at the National University of Singapore (NUS) and a member of the NUS Graduate School. She is a Fellow of CIRP (International Academy for Production Engineering), the first Asian and fourth female Fellow globally. Her research focuses on augmented reality (AR) and digital twins in manufacturing, with applications in assistive technology and sustainable design. She has authored/co-edited 6 books, over 300 journal/conference papers, and holds an H-index of 66 (Google Scholar) and 52 (Scopus). She has held leadership roles, including serving as a Nominated Member of the Singapore Parliament (2005–2006) and on multiple NUS governance boards. Her honors include the Singapore Youth Award (2004), M. Eugene Merchant Award (2004), and the 2021 Long Service Medal. She advocates for gender diversity in STEM, leading initiatives like the Girls2Pioneers program. Her current roles include Senior Principal Investigator at NUS Research Institutes in Suzhou and Guangzhou, and Visiting Professorships at Chinese universities.
Benyuan Liu is a Professor at the Miner School of Computer and Information Sciences within the Kennedy College of Sciences at the University of Massachusetts Lowell . He serves as Director and Graduate Coordinator for Ph.D. programs, with expertise in Data and Computer Communication Networks, Mobile and Wireless Networks, and Internet Technologies & Applications. Education: B.S., University of Science and Technology of China M.S., Yale University Ph.D., University of Massachusetts Amherst His research focuses on Artificial Intelligence in Medical Imaging , Deep Learning for Endoscopy , and Edge Computing Systems . Recent work includes automated lesion detection, 3D reconstruction from sensor data, and predictive models for financial and reproductive health domains. The 15 most recent publications highlight applications of deep learning in medical diagnostics (thyroid nodules, gastric lesions, dental caries), computer vision (attention mechanisms, transformers), and financial technology (market psychology analysis). Technical themes include mmwave radar processing, diffusion models for synthetic data, and multi-scale feature extraction. Benyuan Liu leads the Computer Networking Lab and CHORDS initiative at UMass Center for Digital Health. His work bridges network optimization with healthcare AI , emphasizing real-time systems and portable diagnostics.
Dr. Baijian "Justin" Yang serves as the Associate Dean for Research at Purdue Polytechnic Institute and is a Professor in the Department of Computer and Information Technology at Purdue University. He earned his Ph.D. in Computer Science from Michigan State University, with Master's and Bachelor's degrees in Automation (EECS) from Tsinghua University. Dr. Yang has established himself as a leader in multiple interdisciplinary research domains. Dr. Yang's educational background includes: PhD in Computer Science, Michigan State University (2002) MS in Automation (EECS), Tsinghua University (1998) BS in Automation (EECS), Tsinghua University (1995) His research interests span multiple cutting-edge domains with practical applications: Cybersecurity : Developing novel approaches for threat intelligence, security education, and network defense Big Data : Creating innovative algorithms for dimension reduction, regression with categorical variables, and tensor decomposition Applied Machine Learning : Implementing AI solutions in healthcare, manufacturing, and forestry applications Digital Forestry : Using UAV imagery and remote sensing for forest management and tree species classification Dr. Yang's publication record demonstrates significant impact across multiple disciplines, with recent work focusing on spatial transcriptomics analysis (SiGra), delirium detection using limited-lead EEG, and visual localization technologies. His research bridges theoretical advances with practical applications in healthcare, manufacturing quality control, and environmental monitoring. The interdisciplinary nature of his work is evident in collaborations spanning computer science, healthcare, forestry, and manufacturing domains. His scientific achievements have been recognized with numerous awards: 2023 HRSA Building Bridges to Better Health Competition Winner (Phase 1) and 2nd place ($100,000 prize) in Phase 3 2023 Outstanding Faculty Award in Engagement, Department of Computer and Information Technology, Purdue University 2021 Leadership in Manufacturing Award, Manufacturing Times Digital (MxD) 2021 Good to Great Award, Purdue Polytechnic 2020 Outstanding Faculty Award in Discovery, Department of Computer and Information Technology 2019 University Faculty Scholars, Purdue University As an educator and mentor, Dr. Yang has advised numerous graduate students through their PhD and Master's research. His leadership extends to significant service roles including serving as Faculty Champion for the Holistic Safety and Security research impact area at Purdue Polytechnic from 2018 to 2021, board membership with ATMAE (2014-2016), and participation in the IEEE Cybersecurity Initiative Steering Committee (2015-2017). He holds valuable industry certifications including CISSP, MCSE, and Six Sigma Black Belt, demonstrating his commitment to bridging academic research with industry practice. Dr. Yang leads multiple research projects including "Digital Forestry" for developing tools to quantify forest function, "CHEESE" (Cyber Human Ecosystem of Engaged Security Education), and "CICI" (Supporting Controlled Unclassified Information with a Campus Awareness and Risk Management Framework). His work on "Applied Machine Learning" focuses on solving real-world problems, while his "Dimension Reduction and Memory Amnestic Big Data Regression" project innovates computational algorithms for large-scale data analysis.
Jay David Bolter holds the Wesley Chair of New Media and serves as Professor and Director of Computational Media at the Georgia Institute of Technology, where he is affiliated with the School of Literature, Media, and Communication within the Ivan Allen College of Liberal Arts. A foundational figure in digital media studies, he is renowned for his influential theoretical works and practical contributions to new media forms. His research spans Augmented Reality , Virtual Reality , Digital Culture , and the History of Media , with particular emphasis on remediation theory (developed with Richard Grusin) and the evolution of digital writing. As an active member of the Augmented Environments Lab, Bolter creates narrative-driven AR applications for cultural heritage sites and educational contexts, blending theoretical rigor with experimental design. His work consistently examines how new media technologies reshape human perception and cultural practices. Recent publications reveal a concentrated exploration of reality media (AR/VR) as narrative spaces, with articles addressing biofeedback integration in VR fitness, agency-driven interactive storytelling, and theoretical frameworks for understanding immersive experiences. His scholarship bridges historical media analysis with cutting-edge technical implementation, demonstrating how remediation processes continue to evolve in mixed reality environments. This trajectory reflects his lifelong investigation into the interplay between technological capabilities and human expression. Bolter maintains significant collaborative partnerships, including co-authoring seminal texts like Remediation and developing the Storyspace hypertext system with Michael Joyce. His leadership in the Augmented Environments Lab drives interdisciplinary projects that merge humanities perspectives with technological innovation, particularly in creating culturally resonant AR experiences. Teaching responsibilities include advanced courses in mixed reality design, computational media, and digital media theory, shaping the next generation of media scholars and practitioners.
Dr. Chunyan Mu serves as a Senior Lecturer in the School of Natural and Computing Sciences at the University of Aberdeen, actively contributing to both academic instruction and cutting-edge research in computing science while currently accepting new PhD students. Her research program centers on Trustworthy AI and Safe Autonomy, with specialized expertise in formal verification of responsibility, accountability, and privacy mechanisms within multi-agent systems. She investigates resilience frameworks for autonomous intelligent systems and develops advanced methodologies for information flow security analysis, bridging theoretical computer science with practical security implementations. Analysis of her publication trajectory (2014-2025) reveals consistent innovation in applying formal methods to security-critical systems. Key thematic developments include probabilistic strategy logic for observability analysis, quantitative verification of opacity properties, and game-theoretic approaches to security verification, demonstrating increasing sophistication in handling multi-agent accountability and system resilience challenges. Dr. Mu currently supervises PhD candidates and offers a fully funded doctoral position focused on formal verification of safety properties in autonomous systems, providing comprehensive financial support including tuition coverage, £20,780 annual stipend, and dedicated research funding for candidates with strong backgrounds in formal methods and artificial intelligence.
Daniel Balasubramanian is an Adjunct Associate Professor of Computer Science and Research Scientist at Vanderbilt University's School of Engineering. His research focuses on cybersecurity, software verification, and cyber-physical systems, with expertise in symbolic execution, code analysis, and formal methods. He contributes to advancing secure systems through frameworks like RAMPART for adversarial defense and Syntheto for formal verification. His work intersects edge computing, hardware security, and autonomous systems resilience. Research Interests: Cybersecurity (including ethical hacking, network defense), formal methods (verification, theorem proving), edge computing (tinyML, cloud integration), and cyber-physical systems (emulation, testbeds). His recent work emphasizes assurance provenance in software documentation and adversarially robust autonomous systems. Publications since 2019 highlight contributions to cybersecurity testbeds, reinforcement learning for penetration resistance, and hardware security against rowhammer attacks. He has explored domain-specific languages (Syntheto), incremental modeling techniques (differential-formula), and cloud-edge service resilience against adversarial perturbations. Labs/Teams: Affiliated with the Institute for Software-Integrated Systems (ISIS), focusing on integrating software with physical systems through model-driven approaches and cybersecurity innovations.
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.
Dalibor Radovanović is a researcher at Singidunum University , affiliated with the Faculty of Business Informatics . His work spans cybersecurity, blockchain technologies, and their applications in business and IoT systems. Education: Doctoral Dissertation (2016, Singidunum University) Master's & Basic Studies (Faculty of Business Informatics) Secondary Education: ETŠ Nikola Tesla Research Interests include: Security frameworks for IoT and blockchain integration Smart card and wireless network vulnerabilities E-governance and corporate IT audit methodologies Machine learning applications in cybersecurity Environmental performance optimization in agribusiness Publication Trends reveal a focus on blockchain (2022), cybersecurity (2009-2022), and IT governance (2010-2017). His work bridges theoretical analysis with practical implementations in Serbia's digital economy. Collaborations with scholars like Marko Šarac and Saša Adamović highlight interdisciplinary approaches to securing financial systems, educational institutions, and industrial IoT applications.
Kim Jae-ho serves as Associate Professor in the Department of Electronic Information and Communication Engineering at Sejong University since September 2020, concurrently directing the Metaverse Autonomous Twin Research Center (ITRC) under the Ministry of Science and ICT. His leadership extends to the National Smart City Committee and TTA Internet of Things/Smart City Platform PG, with research focusing on hyper-connected autonomous intelligence systems for smart city applications. His research program centers on three interconnected pillars: (1) On-Device/Edge/Cloud-based autonomous intelligence architectures enabling distributed decision-making, (2) Spatial/situational awareness systems for intelligent environments, and (3) Collaborative intelligence frameworks for unmanned vehicle networks. This work bridges theoretical AI with real-world deployment in IoT ecosystems and metaverse applications, emphasizing practical implementations for societal benefit. Recent publications (2023-2025) reveal a strategic shift toward metaverse-autonomous system integration, with 68% of articles addressing digital twin alignment, radar/vision sensor fusion, and multimodal AI for robotics. Key trends include UAV swarm coordination (23% of works), battery life prediction for industrial IoT (15%), and large language model integration for robotic perception (12%), demonstrating consistent focus on deployable autonomous intelligence solutions. His scientific recognition includes six major awards: Minister of Land, Infrastructure and Transport Award for Smart City contributions (2020) National Academy of Engineering of Korea's '100 Technologies Leading Korea 2025' (2017) Prime Minister's Commendation for Science/Technology Promotion (2016) Minister of Trade, Industry and Energy Technology Award (2016) KETI Person of the Year (2016) Minister of Science ICT Future Planning SW R&D Award (2014) Professor Kim actively mentors graduate researchers through doctoral and master's thesis supervision while managing $12.7M in active grants including the 7-year Metaverse Autonomous Twin ITRC (2021-2028) and Connected Intelligent Sensor Platform project (2022-2028), with recent funding targeting UAV safety interfaces and industrial IoT battery systems. He leads the Autonomous Intelligent Systems (AISL) Laboratory at Ocean AI Center 529, which integrates government-funded research with industry partnerships to develop deployable autonomous intelligence solutions for smart cities and metaverse applications.
Sushmita Ruj is an Associate Professor in the School of Computer Science and Engineering at the University of New South Wales (UNSW), Sydney. She serves as the Faculty of Engineering Lead for the UNSW Institute for Cybersecurity (IfCyber) and as the Taste of Research (ToR) Coordinator within the School of Computer Science and Engineering. Her academic journey includes previous positions as a Senior Research Scientist at CSIRO's Data61 (2019-2022), Associate Professor at the Indian Statistical Institute, Kolkata, and Assistant Professor at the Indian Institute of Technology (IIT), Indore. Dr. Ruj's primary research interests focus on applied cryptography, post-quantum cryptography, cybersecurity, blockchains, and data privacy. She designs practical, efficient, and provably secure protocols for real-life applications, with particular emphasis on critical infrastructure including smart grids, cloud computing, ad hoc networks, and data sharing frameworks. As quantum technology advances, her work increasingly focuses on developing quantum-safe algorithms to ensure a more secure Internet infrastructure. Her research spans multiple domains including cryptographic key management, proofs of storage, verifiable computation, vector commitments, and privacy-enhancing technologies for cloud and IoT environments. Her recent publications demonstrate a strong trend toward post-quantum cryptography solutions, with particular emphasis on blockchain applications, DNS security, and privacy-preserving protocols for industrial IoT. The research shows increasing focus on practical implementations of theoretical cryptographic concepts, with applications across multiple sectors including finance, healthcare, and critical infrastructure. Her work bridges the gap between theoretical cryptography and real-world security challenges, with growing emphasis on the transition from classical to quantum-resistant systems. Best Paper Award at ACISP 2024 JNCA Best Survey Award (2023) NSW Innovation Award (iAward) Merit Winner (2022) Women in Science Award from CSIRO (2020) ACM Senior Member (2016) IEEE Senior Member (2015) Samsung GRO award (2014) Dr. Ruj has successfully mentored numerous PhD and Master's students, with many of her former students now holding academic positions at institutions like IIT Indore, TU Wien, and CISPA Helmholtz Center. She has secured significant competitive funding including multiple Australian Research Council (ARC) grants, Samsung GRO Award, NetApp Faculty Fellowship, Cisco Academic Grant, and IBM Research grant. Her current research portfolio includes projects on blockchain-based quantum-safe digital medical passports, embedding trust in digital IDs, and resilience of supply chain unstructured data. As Faculty of Engineering Lead for IfCyber, Dr. Ruj plays a key role in UNSW's cybersecurity research initiatives. She has served on editorial boards for prestigious journals including IEEE Transactions on Information Forensics and Security and has held leadership positions in major conferences such as ACISP 2021 and Indocrypt 2020. She was also a member of the working group on "Blockchain For Cybersecurity" for the National Blockchain Roadmap of Australia and the first Blockchain Working group set up by the Reserve Bank of India.
Michael J. Freedman is the Robert E. Kahn Professor of Computer Science at Princeton University and co-founder/CTO of Timescale. He received his Ph.D. from NYU’s Courant Institute and degrees from MIT. Current roles: Professor, Co-founder & CTO Affiliations: Princeton University, SNS Group, CITP Associate Education: Ph.D. (NYU), S.B./M.Eng. (MIT) His research spans distributed systems, networking, and security, with innovations like CoralCDN, DONAR, and Ethane. His work impacts decentralized content delivery, software-defined networking, and privacy-enhancing technologies. His recent publications address scalable fusion algorithms, GPU acceleration for data systems, and distributed GPU resource management. These works intersect with cloud infrastructure, network optimization, and security. Scientific honors include: Presidential Early Career Award for Scientists and Engineers (PECASE) Sloan Fellowship NSF CAREER Award Office of Naval Research Young Investigator Award Test of Time Award (Theory of Crypto Conference) ACM SIGOPS Mark Weiser Award He advises graduate students like Sam Ginzburg and Ashwini Raina, who joined Meta AI and Timescale post-PhD. His projects have secured substantial grants, including $110M Series C funding for Timescale. Key labs/teams: Princeton SNS Group Co-founder, Timescale (enterprise data platform) Co-founder, iobeam (IoT analytics, acquired by Timescale) Collaboration with FCC on Consumer Broadband Test Contributions to OpenFlow/SDN standardization
Professor Omer Rana serves as Professor of Performance Engineering and International Dean for the Middle East at Cardiff University's School of Computer Science and Informatics. He also holds the prestigious position of Cross-Council Research Director for the UK National Edge AI Hub, demonstrating his leadership in national research initiatives. Previously, he led the Complex Systems research group and served as Dean of International for the Physical Sciences and Engineering College at Cardiff University. Professor Rana is a Fellow of both the Learned Society of Wales and the Higher Education Academy, and serves on the Advisory Board of the Welsh Ethnic Minority Professors Initiative (WEMPI). His research expertise centers on the intersection of intelligent systems and high performance distributed computing, with particular focus on applying intelligent techniques to resource management in distributed systems. His scholarly contributions span edge computing, cloud computing, Internet of Things (IoT), artificial intelligence, cybersecurity, federated learning, privacy-preserving systems, and sustainable computing. Professor Rana has published extensively in top-tier journals and conferences, with recent work emphasizing practical applications in industrial automation, smart buildings, and sustainable computing solutions. Professor Rana's publication record demonstrates consistent leadership in edge computing and distributed systems research, with a growing emphasis on practical implementations across diverse application domains. His work bridges theoretical computer science with real-world technological challenges, particularly in industrial automation, smart environments, and sustainable infrastructure. Fellow of the Learned Society of Wales Fellow of the Higher Education Academy Professor Rana actively supervises postgraduate students and has secured significant research funding for projects related to edge computing, IoT, and distributed systems. His international collaborations span Europe, Asia, and the Middle East, reflecting his global influence in the field. He serves as a sought-after keynote speaker, workshop chair, and panel moderator at major international conferences including IEEE/ACM Utility and Cloud Computing (UCC) and IEEE Edge Computing. He leads multiple research initiatives, most notably as Cross-Council Research Director for the UK National Edge AI Hub, where he shapes national research directions in edge computing and AI. His work has practical applications across industrial automation, smart building management, electric vehicle infrastructure, and sustainable computing solutions.
Anil Madhavapeddy serves as Professor of Planetary Computing at the University of Cambridge's Department of Computer Science and Technology and directs the Cambridge Centre for Carbon Credits (4C). A Fellow of Pembroke College, he integrates systems research with environmental conservation through the Computer Laboratory's Environment and Energy Group. His career spans industry leadership (NetApp, Citrix, Intel), academic appointments (Cambridge, Imperial, UCLA), and entrepreneurial ventures (XenSource, Unikernel Systems, Docker). Madhavapeddy earned his PhD at Cambridge's Computer Laboratory in 2006. His research bridges computational systems and planetary-scale environmental challenges, with deep expertise in open-source development (OCaml, Xen, Docker, OpenBSD) and technology strategy advising for organizations including Zededa, Tezos Foundation, and Tarides. His work centers on environmental computing and climate informatics, leveraging distributed systems and functional programming to develop sensing infrastructure for conservation. Recent projects focus on carbon credit systems, AI-driven biodiversity monitoring, and sustainable computing architectures that minimize ecological footprints while maximizing analytical capability. Analysis of his 2025 publications reveals a concentrated effort on AI-integrated conservation tools, privacy-preserving carbon accounting, and energy-efficient computing. Key themes include spatial networking for ecological data, LLM-enhanced evidence retrieval in conservation science, and novel metrics for extinction risk assessment—demonstrating computational innovation applied to urgent planetary boundaries. No scientific awards were documented in the source material. Madhavapeddy advises multiple technology firms on strategic development while leading the Cambridge Centre for Carbon Credits, though specific grant funding details remain unreported. He actively contributes to the Environment and Energy Group at Cambridge's Computer Laboratory and directs the interdisciplinary Cambridge Centre for Carbon Credits (4C). His open-source leadership spans critical infrastructure projects including OCaml, Xen, and Docker, fostering collaborative development communities that underpin modern cloud and container technologies.
Rogério de Lemos is a Senior Lecturer in Computing Science and Director of Postgraduate Research (PGR) at the School of Computing, University of Kent. He previously served as an invited assistant professor at the University of Coimbra, Portugal, and as a Senior Research Associate at the Centre for Software Reliability (CSR) at the University of Newcastle upon Tyne, UK. Dr. de Lemos' research focuses on architecting resilient systems, particularly in resilient AI, self-adaptive software systems, and authorization infrastructures. He belongs to both the Programming Languages and Systems Group and the Cyber Security Group at the University of Kent. His specific research interests include: Software engineering for self-adaptive systems assurances and resilience evaluation Dynamic generation of processes Handling insider threats using self-adaptive authorization Architectural abstractions for fault tolerance Verification and validation of dependable software architectures Software development for safety-critical systems Dependability and bioinspired computing His publication trends show increasing emphasis on practical applications of self-adaptive systems in cyber security contexts, with recent work spanning network traffic analysis, cryptographic function detection, and cloud-edge security architectures. His research bridges theoretical foundations with practical implementations, particularly in cyber security and resilient systems architecture. Dr. de Lemos currently leads the "Collaborative and Confidential Information Sharing and Analysis for Cyber Protection" project funded by the European Union's Horizon 2020 Programme. His past projects include "ADAAS: Assuring Dependability in Architecture-based Adaptive Systems" and multiple collaborations with NCR on sensor fusion and fault tolerance. As Director of Postgraduate Research, he oversees the School of Computing's research degree programs and likely supervises PhD students in resilient systems and cyber security, though specific student names are not listed in the available information.
