Eric P. Xing is a Professor at the Language Technologies Institute of Carnegie Mellon University , and currently serves as President of the Mohamed bin Zayed University of Artificial Intelligence . His work bridges machine learning methodology with computational biology and large-scale AI systems . Research Focus: Developing machine learning theory for high-dimensional, dynamic data Building foundation models for biology (AIDO, scLong, ProteinAligner) Designing scalable AI architectures (Pollux, LLM360, PAN) Advancing interpretable and controllable NLP systems Scientific Leadership: Founded the SAILING Lab at CMU Co-chaired ICML 2014 and ICML 2019 Recipient of the Jay Lepreau Best Paper Award (OSDI 2021) Education & Mentorship: Advises PhD students across machine learning and computational biology Alumni include faculty at ETH Zurich, University of Chicago, and UC San Diego
Ioannis Tzimas is a Professor at the Department of Electrical and Computer Engineering of the University of Peloponnese. He is a highly active researcher with numerous publications in areas of Service-Oriented Architectures, Web Engineering, Big Data, and Artificial Intelligence applications. University: University of Peloponnese Department: Department of Electrical and Computer Engineering Academic Rank: Professor Email: tzimas@uop.gr Ioannis Tzimas received his education from the Department of Computer Engineering and Informatics of the University of Patras, where he also completed his PhD in Web Engineering. His research spans multiple interdisciplinary domains at the intersection of computer science and practical applications. Service-Oriented Architectures and Information Systems Web Data Engineering and Web Modeling Big Data Management and Data Science Machine Learning and Artificial Intelligence Applications Digital Ecosystems and Digital Transformation for the Public Sector Bioinformatics Professor Tzimas' recent research output demonstrates a strategic focus on applying advanced computational techniques to address contemporary challenges. His work shows particular expertise in labor market analysis using large language models, electricity demand forecasting in Greece, and social protection systems. His publications reveal a pattern of bridging theoretical computer science with practical, real-world applications across multiple sectors. Since 2018, he has served as an international consultant to the World Bank in the field of information systems and digital transformation, working on projects across Europe, Africa, the Caribbean, the Pacific Islands, and China. His earlier career included significant technical leadership roles at the University of Patras and other Greek institutions. Technical Manager of the Graphics, Multimedia and Geographic Systems Laboratory (1996-2018) Technical Coordinator of the Internet and Multimedia Technologies Research Unit (1997-2011) Scientific Manager of the Network Management Center of the TEI of Messolonghi (2009-mid 2013)
Anastasios Zafeiropoulos serves as Assistant Professor at Harokopio University of Athens, specializing in Spatial Data Management and Analysis within the Postgraduate Studies Program for “Applied Geography and Spatial Management” (Direction C: Geoinformatics). His academic role encompasses teaching “Spatial Databases” and advancing research at the intersection of geospatial technologies and distributed computing systems. His research program focuses on Spatial Databases, Internet of Things (IoT), Cloud/Edge Computing, and 6G Network Orchestration, with significant extensions into Knowledge Graph applications for Sustainable Development Goals (SDGs) and socio-emotional learning in education. Key innovations include the EduCardia methodology for student competency assessment and frameworks for climate vulnerability analysis using knowledge graphs. Analysis of his 2024-2025 publications reveals three dominant thrusts: (1) AI-driven orchestration of 6G services across the computing continuum using reinforcement learning; (2) Knowledge Graph applications for SDG interlinkage analysis and materials science; (3) EU-funded IoT/Edge Computing project ecosystems. His work consistently bridges theoretical networking concepts with practical sustainability and educational applications. Dr. Zafeiropoulos actively contributes to EU-funded initiatives in IoT and Edge Computing standardization, particularly through AIOTI WG Standardisation. His project portfolio includes NEPHELE multi-cloud ecosystem development and O-RAN slice admission control research, demonstrating strong industry-academia collaboration in next-generation networking. He leads the development of innovative tools including Palindrome.js for distributed system visualization and the EmoSocio open-access emotional intelligence model, reflecting his commitment to translating research into practical educational and environmental solutions.
Haoyu Wang is a Researcher in the Computer and Information Science department at the University of Pennsylvania . He previously held research positions at Shanghai Jiao Tong University and interned at Google DeepMind , Amazon AWS , ByteDance , AI2 , Tencent AI Lab , and Goldman Sachs . Education : PhD in Computer and Information Science (2021–Present), MS in Computer and Information Science (2019–2021), BS in Computer Science (2015–2019). His research focuses on Event-Centric NLP/NLU , LLM Reasoning and Planning , Knowledge Graph , and Pose Estimation in Computer Vision . His work includes event causality identification, semantic classification in context, and synthetic control for temporal reasoning. He has contributed to multimodal hallucination analysis and safety in reasoning models through projects like RESIN-11 and Devil's Advocate . His publications span venues like EMNLP , EACL , and ACL . His recent articles analyze LLM limitations in NP-hard problems , clinical trial prediction , event causality , and hallucination in vision-language models . He has served as PC Member for conferences including ACL , NAACL , NeurIPS , and EMNLP since 2019.
Zachary Collier is a Visiting Professor at Radford University, where he teaches Operations Management. He holds a Ph.D. in Systems Engineering from the University of Virginia, a Master of Engineering Management from Duke University, and a Bachelor of Science in Mechanical Engineering from Florida State University. His research focuses on Risk Management , Supply Chain Security , and Hardware Security , leveraging interdisciplinary tools from operations research, economics, and systems engineering. Former engineer in accident reconstruction and the US Army Corps of Engineers Fellow of the Center for Risk Management of Engineering Systems at University of Virginia Visiting Scholar at the Center for Hardware and Embedded Systems Security and Trust (CHEST) Recent research explores semiconductor supply chains , zero trust principles , and resilience modeling for hardware systems. He has authored influential publications on topics such as comorbidity data analysis for pandemic response and blockchain risk assessment . Scientific awards include recognition as a Fellow at the University of Virginia and contributions to SAE International standards . Co-authored industry standards for SAE International Publications in NewsWeek, The Hill, and SupplyChainBrain Expertise in decision modeling for emerging risks
Michael Benedikt is a Professor of Computer Science at the University of Oxford and a Governing Body Fellow of University College. He holds the role of Director of the Advanced MSc in Computer Science program. His research focuses on databases, Web data management, logical methods in computer science, and theoretical computer science. Benedikt's work intersects with artificial intelligence, machine learning, and algorithms, with contributions to query languages, data integration, and formal methods. Education: Ph.D. in Mathematics, University of Wisconsin, 1993 Prior roles: Distinguished Member of Technical Staff at Bell Laboratories (1994–2006), visiting researcher at Yahoo! Labs Research Interests: Databases and information exchange Web and Web 2.0 data management Logical methods in computer science Formal verification and query optimization Applications in AI and machine learning Key Projects: FOX : Query-driven data acquisition from web-based sources PDQ : Proof-driven query answering over web-based data TRANCE : Transforming nested collections efficiently Awards: Best Paper Award at ICALP 2017 (Track B) EPSRC Established Career Fellowship (2015–2020) Advising & Grants: Directed the MSc in Advanced Computer Science program Supervised PhD students including Chia-Hsuan Lu and past advisees such as Luying Chen and Ben Spencer Received funding for projects like the ERC DIADEM initiative Labs & Teams: Active in the Department of Computer Science’s research groups, including the Algorithms At Large and Databases teams.
Jun Shen is a Professor at the School of Computing and Information Technology, University of Wollongong. He specializes in computational intelligence, cloud computing, and big data applications, with a focus on AI-driven solutions for real-world challenges in transport systems, healthcare, education, and environmental management. He has secured over 40 research grants totaling AU$4.5 million and supervised 26 completed PhD projects. His work spans interdisciplinary areas including bioinformatics, smart manufacturing, and digital health. Research interests include bio-inspired algorithmic optimization, AI in arts/media, and edge computing for IoT systems. He has pioneered research centers in applied computing since 2014 and holds editorial roles in top journals like IEEE Transactions. As an IEEE Distinguished Lecturer, he actively promotes AI ethics and interdisciplinary collaboration. Recent publications emphasize adversarial machine learning defenses, UAV systems, and multimodal data fusion. His supervision includes projects in intelligent transport systems, cloud computing, and e-learning. Grants include projects on resilient energy systems and UAV geolocation verification. Leadership roles include leading over 20 researchers and chairing conferences. He advocates for digital transformation in public services and has conducted fieldwork at MIT, UCI, and Georgia Tech.
Morten H. Christiansen is the William R. Kenan, Jr. Professor of Psychology at Cornell University and holds a concurrent position as Professor of Cognitive Science at Aarhus University's School of Communication and Culture and the Interacting Minds Centre. His research focuses on the interplay between biological and environmental factors in language evolution, acquisition, and processing. Key methodologies include computational modeling, neuroimaging, and experimental psychology. He is an elected member of Denmark’s and Norway’s Royal Academies of Sciences and a Fellow of the Association for Psychological Science and Cognitive Science Society. His work spans over 250 papers and four edited volumes, with his monograph The Language Game (2022) proposing a novel theory of language emergence through improvisation. Research interests emphasize multiword chunking, statistical learning, and individual differences in language processing. Current projects explore Danish language challenges, computational models of cultural evolution, and the impact of large language models (LLMs) on human cognition. Christiansen directs the Cognitive Science of Language Lab, teaches undergraduate and graduate courses (e.g., PSYCH 2150: Psychology of Language), and collaborates internationally on projects like the Danish Gigaword Corpus. His recent work highlights language as an emergent system shaped by interactive and ecological pressures.
Lillian Lee is a Professor of Computer Science at Cornell University, affiliated with the College of Computing and Information Science. Her research bridges natural language processing (NLP) and social interaction, focusing on how computational methods can analyze and facilitate socially embedded processes. She co-developed the course “Natural Language Processing and Social Interaction” and leads the Cornell NLP Group. Her work spans sentiment analysis, computational social science, and multimodal interaction, with notable contributions to understanding language features in persuasion, online debate dynamics, and humor comprehension. Key research interests include analyzing digital traces of social interaction, evaluating AI systems through human-centered criteria, and exploring the interplay between language structure and societal influence. Recent projects examine pivotal moments in mental health counseling, cross-cultural historical narratives on Wikipedia, and the role of wording in message propagation. Awards: ACM Fellow, ACL Distinguished Service Award (2021), Test of Time Award, Fellow of the Association for Computational Linguistics Labs/Teams: Member of the Cornell Natural Language Processing Group Advising: Mentored numerous students whose work has driven impactful projects in NLP and computational social science
Charles Gillan is a Senior Lecturer at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science, affiliated with the High Performance and Distributed Computing department and the Institute of Electronics, Communications & Information Technology. His research bridges HPC systems, AI applications in healthcare, and computational physics. Key projects include managing ICU patient care via neural networks, exascale-ready mathematical packages, and edge computing architectures. Research interests focus on high-performance computing (HPC), quantum computing, real-time data analytics, and electron-molecule scattering simulations. Notable contributions include developing microserver architectures for edge analytics and advancing AI-driven clinical decision support systems. Gillan has collaborated on interdisciplinary projects like food authenticity testing using spectroscopy and improving ventilator management in intensive care units. Publications span AI in healthcare, HPC system design, and computational methods for physics problems. He has secured funding for initiatives such as the KTP partnership with Foods Connected Ltd and the HANDHELD olfactory detection project. Gillan's work emphasizes practical applications of advanced computing across healthcare, engineering, and cybersecurity domains.
Meng Xu is an Assistant Professor in the Cheriton School of Computer Science at the University of Waterloo, Canada. He is affiliated with the Cryptography, Security, and Privacy (CrySP) group and the Cybersecurity and Privacy Institute (CPI). His research focuses on system and software security, emphasizing secure-by-design languages (e.g., Rust, Move), automated program analysis, and runtime defense techniques. Education : Ph.D., Computer Science (2020), Georgia Institute of Technology B.Eng. and B.Business (First Class Honors), Nanyang Technological University (2014) Research Interests : Secure-by-design languages Automated security analysis (fuzzing, symbolic execution) Runtime defense mechanisms (moving target defense, secure hardware) Key Awards : EAPLS Best Paper Award (2022) USENIX Security Distinguished Paper Award (2018) Grants & Funding : BlackBerry Research Grant (CAD $200,000) Amazon Research Award (USD $60,000) NSERC Discovery Grant (CAD $170,000) Labs & Collaborations : CrySP (Cryptography, Security, and Privacy Group) Cybersecurity and Privacy Institute (CPI)
Mitchell L. Neilsen is a Professor in the Department of Computer Science at Kansas State University's College of Engineering, where he also serves as the graduate program director. He holds the Warren and Gisela Kennedy - Carl and Mary Ice Keystone Research Scholar position and maintains an active research program with multiple ongoing projects. His educational background includes a Ph.D. in Computer Science (1992), M.S. in Computer Science (1989), and M.S. in Mathematics (1987), all from Kansas State University, plus a B.S. in Mathematics Education from the University of Nebraska-Kearney (1982). After beginning his career as an assistant professor at Oklahoma State University, he returned to K-State in 1996. Research Interests: Cyber-Physical Systems: Design, Analysis, Verification of systems integrating computing, networking, and physical processes Distributed Systems: Algorithms, design, and analysis of distributed computing systems Scientific Computing: Computational Fluid Dynamics, Finite Element Analysis, High Performance Computing, and Simulation Application Areas: Agriculture technology, Dam safety analysis, Mobile applications, Natural resources management, and Real-time Embedded Systems His research program shows clear evolution toward agricultural technology applications, particularly high-throughput phenotyping, while maintaining strong foundations in cyber-physical systems and scientific computing. Recent publications indicate increasing integration of machine learning and computer vision techniques into traditional research areas. Research Funding: National Science Foundation U.S. Department of Agriculture Sandia National Laboratories Department of Homeland Security Private industry partners Dr. Neilsen has mentored numerous graduate students through their M.S. and Ph.D. programs, with recent advisees focusing on applications in agricultural technology, dam safety, and embedded systems. His advising approach emphasizes practical applications of theoretical computer science concepts. Current Teaching (Fall 2024): CIS 450 - Computer Architecture and Operations CIS 625 - Concurrent Software Systems CIS 720 - Advanced Operating Systems
Dr. Chao Fan is an Assistant Professor in Civil Engineering and Environmental Engineering and Earth Sciences at Clemson University, affiliated with the Glenn Department of Civil Engineering. His research focuses on climate change adaptation, socio-environmental systems dynamics, and urban resilience, leveraging AI and data science. He holds a Ph.D. from Texas A&M University (2020), an M.S. from UC Davis (2017), and a B.S. from China University of Mining and Technology (2016). Dr. Fan's work integrates interdisciplinary approaches to address challenges in disaster management, smart cities, and environmental justice. Key interests include social sensing for infrastructure disruptions, equity in urban mobility networks, and leveraging digital twins for resilience planning. His recent publications explore topics like wildfire impacts, PM2.5 exposure inequity, and carbon market mechanisms for infrastructure adaptation. Professional memberships include ASCE, ACM SIGKDD, AGU, and AAAS. His lab (fanchaolab.com) develops innovative solutions for climate adaptation and equitable urban systems, emphasizing fairness in AI-driven models and network analysis.
Dr. Jody Clarke-Midura is a Professor and Associate Dean of Graduate Studies in the Emma Eccles Jones College of Education and Human Services at Utah State University. She holds an Ed.D. from Harvard Graduate School of Education, an M.Ed. in Technology in Education, and a B.A. in English and Women’s Studies from the University of Massachusetts. Her research focuses on designing playful, technology-enhanced learning environments to foster STEM engagement and computational thinking in K-12 and early childhood education. Key areas include game-based learning, computational thinking integration, and technology-enhanced assessments. She collaborates on interdisciplinary teams and leads externally funded projects. Clarke-Midura co-directs the Playful Explorations Lab (PEL), which designs STEM learning experiences for elementary classrooms. Her work emphasizes hands-on, student-driven exploration and connects theory to classroom practice. She mentors graduate and undergraduate students, supporting their research development. Her publications address topics like formative assessments, computational thinking assessment frameworks, and the role of coding toys in early math learning. She has contributed to curriculum models integrating computer science and mathematics, and explored cultural relevance in co-design processes. Professional activities include leading graduate studies administration, advising on educational technology initiatives, and advancing inclusive pedagogical practices.
Kevin W. Hamlen is the Louis A. Beecherl, Jr. Distinguished Professor in the Department of Computer Science at the University of Texas at Dallas. He serves as Executive Director of UT Dallas' Cyber Security Research and Education Institute. His research focuses on language-based security , binary software hardening , cyberdeception , and formal program verification . He has received multiple grants from agencies like AFOSR, NSF, DARPA, and industry partners including Lockheed Martin and Intel. PhD and MS from Cornell University BS from Carnegie Mellon University His research explores automated approaches to software security through techniques like binary disassembly , control-flow integrity , and honey-patching . He has pioneered methods for malware defense and cloud/web/mobile security . Recent work examines adaptive cyberdeception and GPU-based security frameworks . His publications span binary code manipulation , malware mitigation , and blockchain security . Key awards include the NSF IUCRC Technology Breakthrough Award and two CSAW Best Paper 2nd Prizes . He advises numerous PhD students, many of whom now work at Google, IBM, and Microsoft. His book Autonomous Cyber Deception (Springer, 2019) with Ehab Al-Shaer and Cliff Wang provides comprehensive coverage of adaptive cyberdeception strategies.
