Tijay Chung is an Associate Professor at the College of Engineering , Virginia Tech , specializing in Internet Security and Internet Measurement . His work bridges theoretical and applied aspects of cybersecurity, focusing on secure communication protocols and infrastructure. Education Ph.D., Computer Science and Engineering, Seoul National University (2015) B.S., Computer Science and Engineering, Pohang University of Science and Technology (2009) Research Interests Chung's research centers on improving certificate revocation mechanisms, DNSSEC, and TLS security. He explores vulnerabilities in web encryption, develops decentralized cryptographic solutions, and analyzes internet governance protocols like BGP and RPKI. His work also extends to privacy in contact-tracing technologies and understanding content distribution dynamics in peer-to-peer systems. Recent publications highlight trends in : Enhancing TLS and DNSSEC operational security Decentralized cryptographic accumulators for revocation Longitudinal studies of PKI and certificate ecosystems Privacy guarantees in Bluetooth Low Energy (BLE) systems Advising No student names were explicitly listed in the provided materials.
Christian Newman is an Associate Professor in the Department of Software Engineering at the Golisano College of Computing and Information Sciences, Rochester Institute of Technology (RIT). He serves as the Graduate Program Director and has expertise in software engineering methodologies, refactoring techniques, and source code analysis. His research focuses on improving code quality, developer practices, and automated documentation. Education: Newman holds a BS, MS, and Ph.D. from Kent State University. His academic background aligns with his current research in software engineering and empirical studies. Research Interests: His work emphasizes identifier naming standards, technical debt management, refactoring strategies, and code reuse. He explores how developers perceive and implement refactoring tools, as well as the role of large language models (LLMs) in programming education and code generation. Publications: Newman's recent work includes studies on identifier semantics, part-of-speech tagging for code analysis, and the performance of LLMs in introductory programming tasks. His research often combines empirical studies with tool development, such as SATDBailiff for technical debt tracking and TSDetect for test smell detection. Teaching & Advising: He teaches courses like SWEN-250 (Personal Software Engineering), SWEN-331 (Engineering Secure Software), and graduate-level thesis supervision. His courses emphasize secure development, software design principles, and team-based projects. Tools & Contributions: Newman has developed tools like srcSlice (static slicing), srcType (type resolution), and SCALAR (identifier analysis). These tools support software evolution, code comprehension, and empirical research in the field.
Dr. Jose R Juan Sanchez is a full Professor at the Faculty of Law, Universitat de València, specializing in Procedural Law within the Institute of Criminology and Criminal Science (ICCP). He serves in the Administrative Department and leads the NCPJ New conflicts and judicial process research group. Doctorate in Law (1997) from Universitat de València Thesis: Autonomous Communities as Parties in Civil Proceedings Supervised by Dr. Manuel Ortells Ramos His research focuses on procedural law, judicial management, and legal reforms. He investigates tribunal jurisdiction, victim rights, and data protection in criminal proceedings. Recent work includes Photovoice analysis of pandemic healthcare systems and efficiency in Spanish criminal justice. Key article trends span judicial reforms (2015-2024), victim rights in EU legal frameworks (2020-2023), digital justice systems (2016-2017), and social justice in legal education (2022-2023). His work bridges law, criminology, and policy analysis. Current affiliations: Universitat de València, ICCP Institute Research group: NCPJ New conflicts and judicial process
Pradeep Lall is the MacFarlane Endowed Distinguished Professor and Alumni Professor in the Department of Mechanical Engineering at Auburn University’s Samuel Ginn College of Engineering. He serves as Director of the Auburn University Electronics Packaging Research Institute (EPRI) and holds a joint courtesy appointment in the Department of Electrical and Computer Engineering. A leader in flexible hybrid electronics and harsh environment systems, Dr. Lall has built a world-renowned research program focused on additive manufacturing, electronics reliability, and sustainable materials. Ph.D. in Mechanical Engineering, University of Maryland M.B.A. in Finance and Strategy, Northwestern University M.S. in Mechanical Engineering, University of Maryland B.E. in Mechanical Engineering, Delhi College of Engineering Dr. Lall’s research centers on Flexible Hybrid Electronics (FHE) , Harsh Environment Electronics , Semiconductor Packaging , and Prognostics Health Management . His work leverages additive manufacturing techniques such as Aerosol-Jet, InkJet, and screen printing to develop conformal, robust, and sustainable electronic systems. His innovations include the Flexible Biometric Band for monitoring workers in hazardous environments and additively printed antennas for aerospace applications. His recent focus includes eliminating PFAS from electronics and developing water-based inks for eco-friendly manufacturing. The 15 most recent publications reflect a strong trend toward sustainability , additive manufacturing , and real-world applications in defense, aerospace, automotive, and healthcare. His work bridges fundamental research with industrial realization, particularly through partnerships with NextFlex and federal agencies. Themes include reliability under shock and vibration, sensor development for extreme environments, and workforce training in advanced manufacturing. Dr. Lall has received numerous scientific honors, including: SMTA Founder’s Award (2024) SEMI FlexTech R&D Achievements Award (2023) ASME Avram Bar-Cohen Memorial Medal (2022) IEEE Biedenbach Outstanding Engineering Educator Award (2020) IEEE Sustained Technical Contributions Award (2018) NSF Alex Schwarzkopf Prize (2016) Fellow of ASME, IEEE, NextFlex, and Alabama Academy of Science Dr. Lall has secured over $2 million in annual research funding from SRC, NSF, and NextFlex, leading large-scale projects on sustainable electronics and workforce development. He mentors numerous graduate and undergraduate students and leads the NSF-CAVE3 Center. As founding faculty advisor of the SMTA student chapter, he promotes student engagement in electronics manufacturing. His lab, EPRI, features a full prototyping line for additive electronics and collaborates with industry and government to advance domestic manufacturing capabilities. EPRI, under Dr. Lall’s leadership, partners with the Auburn University Research and Technology Park, the Office of Economic Development, and multiple colleges to drive technology commercialization and workforce education in electronic packaging. The institute is at the forefront of the national effort to reestablish U.S. leadership in semiconductor packaging and advanced electronics manufacturing.
Onur Mutlu is a Professor of Computer Science at ETH Zurich, affiliated with the Department of Information Technology and Electrical Engineering. He also holds adjunct professorships at Carnegie Mellon University and Bilkent University. His research focuses on computer architecture, systems security, bioinformatics, and energy-efficient computing. He has pioneered work on memory-centric computing paradigms, RowHammer security vulnerabilities, and bio-inspired computing systems. He teaches courses such as Digital Design & Computer Architecture and supervises the SAFARI research group, which explores cutting-edge topics in memory systems, AI accelerators, and genomics. Recent activities include keynote talks at ISCA, HiPEAC, and IEEE conferences, emphasizing emerging hardware-software co-design principles. Key contributions include foundational work on memory reliability, cross-layer system design, and accelerating genomic data analysis. His research has been showcased in over 200 publications and industry collaborations with tech leaders like Intel, Huawei, and Micron.
Simon Yang is a Professor in the School of Engineering at the University of Guelph, part of the College of Engineering and Physical Sciences. His research focuses on artificial intelligence, robotics, sensors, control systems, and bio-inspired intelligence. He has contributed to advanced robotics applications, including mobile robot navigation, underwater vehicle control, and agricultural automation. Dr. Yang holds editorial roles for journals such as the International Journal of Robotics and Automation and IEEE Transactions on Cybernetics . His work bridges theoretical advancements with practical implementations in areas like sensor networks, machine learning, and multi-agent systems. Recent projects include developing robust control frameworks for autonomous systems, digital twin applications, and bio-inspired neural network algorithms. His research emphasizes real-world challenges in robotics, environmental monitoring, and precision agriculture, with a focus on integrating AI-driven solutions for enhanced decision-making and system reliability. Professional contributions include advisory roles in multiple journals and conference committees, reflecting his leadership in the field.
Vidar Hepsø is a Professor at the Department of Computer Technology and Informatics, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU). His work bridges anthropology of science and technology with practical challenges in digitalization, energy transition, and remote operations. Research focuses on digital infrastructures, socio-technical systems, and human factors in oil and gas industries Active in NTNU Applied Information Technology and NTNU Energy Transition Initiative Publications emphasize open-source ecosystems, autonomous systems, and environmental monitoring His scholarly output spans computer-supported collaborative work, IT infrastructure governance, and risk-informed anomaly detection in subsea systems. He leads projects connecting digital innovation with offshore wind and petroleum geoscience.
Taiwo Amoo is an Assistant Professor of Business and Quantitative Methods at Brooklyn College, CUNY , where he has been employed since 1999. His academic career spans institutions including Baruch College (substitute and adjunct roles, 1993-1999) and Kaduna Polytechnic, Nigeria (1987-1988). With a PhD in Operations Research (University of Exeter, 1992) and a BSc in Statistics (University of Ibadan, 1986), Amoo specializes in operations management, statistical analysis, and educational innovation. Current position: Assistant Professor (Brooklyn College, CUNY) Key expertise: Operations Management, Queueing Theory, Rating Scale Methodology Technological proficiency: SAS, SPSS, Oracle Database Systems His research focuses on optimizing rating scale design , integrating technology in education , and interdisciplinary approaches to business programs . Publications from 2000-2002 examine biases in survey construction, humor as an educational tool, and the relevance of traditional disciplinary structures in modern academia. Notable awards include PSC CUNY Grants and recognition as the Best Statistics Student at the University of Ibadan. Current affiliations: Brooklyn College (CUNY) Past affiliations: Baruch College (CUNY), University of Exeter, Kaduna Polytechnic
Dr. Huadong Mo is a Senior Lecturer at the School of Systems and Computing, University of New South Wales (UNSW) Canberra, Australia. He holds a B.E. degree in automation from the University of Science and Technology of China (2012) and a Ph.D. in systems engineering and engineering management from the City University of Hong Kong (2016). Prior to his current position, he was a research associate at ETH Zurich's Reliability and Risk Engineering Lab (2016-2019) and a Lecturer at UNSW Canberra (2019-2021). Dr. Mo's educational background includes a strong foundation in systems engineering with international experience across China, Switzerland, and Australia. His career trajectory demonstrates a progression from academic research to faculty positions with increasing responsibilities in teaching and research leadership. His research focuses on enhancing the resilience, performance, and security of complex systems using learning-based algorithms, primarily in power and energy systems, cyber-physical systems, and manufacturing systems. He applies data analytics to understand system evolution under uncertainties, with particular emphasis on prognostics and health management, sustainable transportation, robust operation of power systems under extreme events, and reinforcement learning-based asset management. His work bridges theoretical advances with practical applications in critical infrastructure. Analysis of Dr. Mo's recent publications reveals a strong focus on energy systems, particularly in the integration of machine learning with power grid management, battery storage systems, and resilience against cyber threats. His research shows a clear trajectory toward increasingly complex system integration, with growing emphasis on multi-vector energy communities, cross-domain prediction, and uncertainty-aware energy management. The interdisciplinary nature of his work spans electrical engineering, computer science, and operations research. 2024 IEEE SMC Early Career Award 2023 Visiting Research Fellowship (Jean d'Alembert Pour Fellowship) Gold Medal in 2024 China International College Student Innovation Competition (as supervisor) Arc PGC Supervisor Award (2021) IEEE SMC Outstanding Chapter Award (2021) Alumni Achievement Award from City University of Hong Kong (2019) Dr. Mo actively supervises numerous HDR students working on cutting-edge research topics including battery health monitoring, quantum control, reinforcement learning for power systems, and explainable AI for energy management. He leads multiple significant research grants totaling over 3 million AUD, including projects funded by ARC, Energy Innovation Fund, and international collaborations with institutions like ETH Zurich, Cambridge, and Tsinghua University. His research group maintains strong international connections, facilitating student exchanges and collaborative research. As Postgraduate Course Coordinator of Systems Engineering and Chair of IEEE SMC ACT Chapter, Dr. Mo plays a significant role in academic leadership and professional community building. His research team collaborates with industry partners on practical implementations of their theoretical work, particularly in the energy sector.
Paul R. Genssler is a Dr.-Ing. researcher at the Chair of AI Processor Design (AI-Pro) within the Technical University of Munich (TUM), actively advancing hardware solutions for artificial intelligence under Prof. Hussam Amrouch. His work bridges computer engineering and emerging technologies, focusing on overcoming fundamental limitations in conventional computing architectures through brain-inspired paradigms. His research spans critical domains in next-generation computing: Hyperdimensional Computing for robust pattern recognition and bioinformatics applications Neuromorphic and In-Memory Computing architectures for energy efficiency Reliability engineering for emerging memory technologies (FeFET, etc.) Quantum computing support systems including cryogenic embedded electronics Machine learning-driven transistor aging prediction and mitigation Analysis of his 15 most recent publications (2023-2024) reveals a dominant trend toward hyperdimensional computing as a unifying framework for addressing reliability challenges in emerging technologies. His work consistently integrates in-memory computing techniques to bypass von Neumann bottlenecks while targeting real-world applications like genome matching and unsupervised learning. A significant portion focuses on error-resilient implementations for unreliable nanoscale devices, demonstrating exceptional cross-stack expertise from transistor physics to algorithm design. As a core member of TUM's AI Processor Design group affiliated with the Munich Institute of Robotics and Machine Intelligence (MIRMI), Genssler collaborates extensively on projects spanning cryogenic quantum control systems, FPGA-based AI resilience, and monolithic 3D integration. The team operates at the intersection of semiconductor physics, computer architecture, and machine learning, with strong industry connections evident through publications at DATE, ASP-DAC, and ICCAD.
Claes Beckman is a part-time senior researcher in the Division of Communication Systems at KTH Royal Institute of Technology. He was appointed Professor in antenna systems at KTH in 2013 and previously served as Professor in microwave engineering at HIG in 2004. Beckman was the founding director of the research center Wireless@kth in 2001. His career spans over 40 years across academia, government, and industry, with significant contributions to wireless communications, antenna systems, and spectrum management. Beckman's research interests focus on wireless communications systems, particularly antenna design, MIMO technology, 5G networks, and mobile connectivity solutions for challenging environments including transportation systems and remote regions. His work bridges theoretical research with practical implementation, resulting in numerous patents, products, and industry standards. Recent research has examined satellite-cellular integration, high-reliability communication for transportation systems, and private 5G networks for industrial applications. Analysis of his recent publications reveals a strong focus on practical wireless communication challenges, with particular emphasis on real-world implementation issues in mobile and transportation environments. His work spans theoretical antenna design, field measurements, network performance analysis, and spectrum policy considerations, reflecting his unique position at the intersection of academic research, industry application, and regulatory frameworks. Beckman has advised close to 100 M.Sc. students, 7 licentiate, and 3 PhD theses throughout his career. He has secured over $30 million in research funding through multiple Vinnova, KK-foundation, and SSF projects, including serving as KTH's Principal Investigator for the EU FP7 METIS project on 5G. His industry experience includes roles as a microwave design engineer for Ericsson and research manager for Allgon Systems. Beckman serves as a technical expert for Icomera AB and technical consultant to Proan t AB. He has significant regulatory experience, having served on international standards committees (ETSI and 3GPP) and consulted for the Swedish National Regulator for Post- and Telecommunications (PTS), the Swedish Competition Authority, Swedavia, Teracom, and the Swedish Armed Forces.
Yuqing Wang is a Postdoctoral Researcher in the Department of Computer Science at the University of Helsinki, Finland, actively contributing to software engineering research with expertise in anomaly detection for microservices and test automation maturity. Contactable via yuqing.wang@helsinki.fi and phone +358505934630/+358294151310, Wang participates in major EU and Academy of Finland projects including LUMI AI Factory (2025-2028) and MuFAno (2023-2026). Research focuses on two interconnected domains: anomaly detection in cloud-native systems using meta-learning for cross-system log analysis and trace categorization, and test automation maturity assessment frameworks. Recent work pioneers datasets like LO2 for microservice API anomalies and tools like LogLead for integrated log processing, while earlier studies establish quantitative links between test automation maturity and product quality in open-source ecosystems. Publications reveal an evolving trajectory from foundational test automation maturity models (2018-2020) toward advanced AI-driven anomaly detection (2024-2025), with 2022-2023 bridging both domains through empirical studies on agile practices and maturity impacts. Current work emphasizes cross-system generalization and multimodal fusion for microservice reliability. No scientific awards are documented in available sources. Wang contributes to two significant grants: the EU Horizon Europe LUMI AI Factory developing AI service infrastructure (2025-2028), and the Academy of Finland MuFAno project advancing multimodal anomaly detection for microservices (2023-2026). These projects drive collaboration with industry partners on real-world system reliability challenges.
Devin G. Pope is the Steven G. Rothmeier Professor of Behavioral Science and Economics at the University of Chicago's Booth School of Business. His research examines psychological biases in economic decision-making using observational data across diverse markets including healthcare, voting, transportation, and consumer behavior. Pope has published extensively in top economics journals (American Economic Review, Quarterly Journal of Economics), general science publications (Science, Nature), and interdisciplinary outlets (Management Science, Psychological Science). His research interests bridge behavioral economics and psychology, focusing on vaccination incentives , racial bias measurement , consumer decision heuristics , and observational data analysis . Recent work leverages smartphone data to study religious attendance patterns, voting wait times, and geographic mobility. Pope's research methodology emphasizes real-world field experiments and large-scale observational datasets to identify psychological biases affecting economic outcomes. Notable scientific contributions include: Co-editing the American Economic Review Amazon Scholar appointment (2019-2021) Robert King Steel Faculty Fellowship Steven G. Rothmeier Professorship Pope advises PhD students and teaches graduate courses including Behavioral Economics and Workshop in Behavioral Science. His research has received significant external funding for pandemic response studies and behavioral interventions. Pope maintains active research collaborations across economics, psychology, and public health disciplines through the Booth School's research centers and workshops.
Børge Rokseth is an Associate Professor at the Department of Engineering Cybernetics , Norwegian University of Science and Technology (NTNU). His work focuses on integrating advanced methodologies for safety and risk control in autonomous maritime systems. He has held academic positions since at least 2014, with a consistent record of research collaboration and publication. Research Areas: Maritime risk analysis, autonomous ship systems, safety engineering, dynamic positioning systems, systems-theoretic process analysis (STPA) Key Publications: 15 most recent articles cover topics like trajectory prediction for autonomous vessels, hybrid power systems safety, machine learning in risk assessment, and dynamic positioning system reliability His publications (2014-2025) emphasize safety-critical systems in marine environments. Common themes include: Application of STPA for hazard analysis in autonomous shipping Development of risk-informed control systems Integration of machine learning with engineering risk assessment Comparative studies of different ship autonomy levels As a supervisor, Rokseth has guided master's students including Ane Joramo Stokke and Ludvig Vik Løite. His work has been presented at international conferences such as the European STAMP Workshop, International Conference on Conceptual Modeling, and the International Seminar on Safety and Security of Autonomous Vessels.
David A. Plaisted is a Research Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. He joined UNC-Chapel Hill as a full professor after serving on the faculty of the Computer Science Department at the University of Illinois at Urbana-Champaign until 1984. His academic career spans several decades with significant contributions to automated reasoning and computational logic. Bachelor's degree in Mathematics from the University of Chicago (1970) Ph.D. in Computer Science from Stanford University (1976) Professor Plaisted's research focuses on mechanical theorem proving, term rewriting systems, logic programming, and algorithms. His work in term-rewriting systems investigates methods of combining them with first-order theorem provers, including techniques for applying efficient permutation group algorithms to equational theorem proving. In mechanical theorem proving, he has developed a sequence of methods including clause linking with semantics and ordered semantic hyper-linking. His research in logic programming includes developing tests to eliminate the occurrence check in Prolog while maintaining semantics. His work spans theoretical foundations to practical applications in program verification and generation. His recent publications demonstrate continued innovation in automated reasoning, particularly in semantic guidance for theorem proving. His work shows a consistent focus on improving the efficiency and effectiveness of automated deduction systems, with recent contributions to SGGS (Semantically-Guided Goal-Sensitive) theorem proving and analysis of the relationship between semantics and unification in proof systems. Professor Plaisted has served on numerous program committees and editorial boards including the Journal of Symbolic Computation, Information Processing Letters, Mathematical Systems Theory, and Fundamenta Informaticae. He is currently on the editorial board of ACM Transactions on Computational Logic and the electronic Journal of Functional and Logic Programming. He has organized significant conferences including serving as co-chair of the Second International Conference on Rewriting Techniques and Applications in 1987. He has spent several sabbaticals at prestigious institutions including SRI in Menlo Park (1982-1983), the Max-Planck Institute and University of Kaiserslautern in Germany (1993-1994), and research visits to groups in Grenoble and Nancy, France (1998).
