Wenwen Wang is an Associate Professor in the School of Computing at the University of Georgia's Franklin College of Arts & Sciences. His research focuses on computer systems, compiler design, and embedded systems security. He holds a Ph.D. in Computer Science from the University of Chinese Academy of Sciences (2014). Education: Ph.D., Computer Science, University of Chinese Academy of Sciences, 2014 His research emphasizes dynamic binary translation, compiler optimization, and secure embedded systems. Notable contributions include frameworks like JavART (JIT compiler optimization) and BSan (memory error detection). He received the 2021 M. G. Michael Award for Sciences from the Franklin College. Wang has secured two NSF grants totaling $1.2 million, including CSR: Small grants for FALCON (2023–2027) and Modernizing Dynamic Binary Translation Systems (2023–2027). He advises three graduate students: Ruili Fang, Yage Hu, and Boyang Yi. His work addresses challenges in cross-architecture virtualization, GPU-based graph computing, and hardware-triggered security mechanisms. Recent projects include Liberator (GPU graph processing) and InvisiGuard (embedded device integrity).
Anton Akusok is a Part-time Lecturer in the Big Data Analytics Master's program at Arcada University of Applied Sciences. He holds a BSc in IT from Moscow (2011), MSc in ML and Data from Aalto University (2014), and a DSc in ML from the University of Iowa, USA (2016). His research focuses on Extreme Learning Machines (ELM), hardware acceleration for ML on mobile devices, and real-time geospatial predictions. He has developed libraries like HPELM and Scikit-ELM, and created the HaSuRiski app for acid sulfate soil prediction in Finland. Research Interests: ELM applications in environmental modeling, federated learning security, mobile edge computing, and geospatial visualization. Key projects include real-time mapping apps with iOS integration and open-source ML tools. Publications (2021-2024) highlight work on federated learning privacy, acid sulfate soil detection, signature verification, and distributed ELM algorithms.
James Collofello is Vice Dean of Academic and Student Affairs at the Fulton Schools of Engineering and a Professor of Computer Science and Software Engineering at Arizona State University. He has held the vice dean position since 2006, overseeing student recruitment, career development, curriculum innovation, and programs like the Fulton Undergraduate Research Initiative (FURI) and Engineering Projects in Community Service (EPICS). His work emphasizes large-scale implementation of programs to enhance student research, leadership, and entrepreneurship skills. Education: Ph.D. Computer Science, Northwestern University (1979) M.S. Mathematics, Northern Illinois University (1977) B.S. Mathematics, Northern Illinois University (1976) Research & Expertise: Collofello focuses on software engineering methodologies, software project management, and quality assurance. He collaborates with industry partners like Honeywell, Motorola, and Boeing to address applied research challenges. His educational research includes engineering retention strategies and K-12 outreach programs. Recent grants involve NIST Summer Undergraduate Research Fellowships, transportation initiatives, and curriculum development for embedded systems. Teaching: Frequently teaches courses on software verification/validation, project management, and process quality control (e.g., CSE 565, CSE 566). Supervises practicum and thesis projects through courses like FSE 580 and CSE 799. Leadership: Manages the Fulton Difference portfolio, including the Grand Challenge Scholars Program and Undergraduate Teaching Assistant program. Coordinates national transportation education initiatives and industry partnerships.
Mauro Tempesta is a Senior Lecturer and Curriculum Coordinator for Security and Privacy at TU Wien's Faculty of Informatics. He teaches courses including 'Fundamentals of Security and Privacy' and 'Introduction to Security'. His research focuses on web security, browser mechanisms, firewall systems, and language-based security approaches. Tempesta's publications demonstrate expertise in analyzing modern web vulnerabilities and developing formal verification methods for security protocols. His recent work explores browser security mechanisms and same-site attacks, contributing to improved security frameworks for web applications.
Ana Lucia Caneca Cavalcanti is a Professor of Computer Science at the University of York, leading the SER research group with expertise in formal methods for safety-critical systems. Her work bridges theoretical software engineering with practical applications in robotics and autonomous systems, emphasizing verification and reliability. BSc in Computer Science, Universidade Federal de Pernambuco, Brazil (1987) MSc in Computer Science, Universidade Federal de Pernambuco, Brazil (1990) DPhil in Computer Science, Oxford University (1997) Her research centers on formal methods, safety-critical software engineering, and real-time systems, with recent focus on robotics. She develops semantic frameworks for refining and verifying complex systems, particularly in adaptive robotic control. Her methodologies address concurrency, object-orientation, and tooling to ensure correctness in high-stakes environments like autonomous vehicles. Current publications reveal a cohesive trend: applying process algebra and architectural patterns to robotic software verification. This work targets safety assurance in adaptive systems, integrating formal semantics with physical robot modeling to mitigate risks in autonomous decision-making. Scientific recognition includes: Royal Society Wolfson Research Merit Award She directs major funded initiatives including RoboSapiens (European Commission, 2024-2026) on human-robot symbiosis, DOMINOS (EPSRC, 2024-2025) for AI disruption mitigation, and the UK Trustworthy Autonomous Systems Verifiability Node (EPSRC, 2020-2024). These projects involve industrial collaborations with Labman Automation and RoboTest, focusing on verifiable safety frameworks. As SER research group lead, she oversees a team advancing formal verification techniques for next-generation autonomous systems, with active partnerships in the High Integrity Systems ecosystem at York.
Max Cohen is a Postdoctoral Scholar Research Associate in the Department of Mechanical and Civil Engineering at the California Institute of Technology (Caltech). His research focuses on safety-critical control systems, adaptive control, and the integration of control barrier functions with reinforcement learning. He explores theoretical frameworks for robust control design in nonlinear systems, emphasizing safety guarantees through formal verification methods. His work addresses challenges in automated vehicle navigation, hybrid systems, and rehabilitation engineering using functional electrical stimulation (FES). Key research directions include uncertainty quantification in adaptive systems, layered control architectures, and safe exploration strategies in model-based reinforcement learning. Publications span topics like control barrier function synthesis, temporal logic-guided learning, and reduced-order modeling for safety-critical applications. Current research trends emphasize bridging formal methods with data-driven control paradigms to ensure safe operation in complex robotic and cyber-physical systems. No scientific awards or grants are explicitly mentioned in the provided information. His office is located in Gates-Thomas Laboratory (Room 300), and he actively contributes to interdisciplinary projects at Caltech's engineering division.
Florian Eugster serves as Associate Professor of Auditing at the University of St. Gallen (HSG), Switzerland, where his research and teaching focus on auditing, financial accounting, and valuation. Based in St. Gallen at Tigerbergstrasse 9 (Office 57-106), he maintains an active academic profile with international collaborations and editorial responsibilities. His educational foundation includes a summa cum laude PhD in Finance from the University of Zurich (2009–2013), complemented by pedagogical training from the Stockholm School of Economics (2017) and CEIBS (2015). Earlier degrees comprise a Master of Arts in Business Administration (summa cum laude, 2007–2009) and Bachelor of Arts in Banking and Finance (2004–2007), both from the University of Zurich, with a visiting period at the University of Toronto’s Rotman School (2012–2013). Eugster’s research spans critical domains in accounting: Auditing : Investigating audit quality determinants, materiality judgments during crises, and digital transformation’s impact on assurance processes Financial Accounting : Analyzing valuation techniques, supply chain disclosures, and cross-cultural earnings reporting practices Contemporary Issues : Pioneering studies on climate-related disclosures, passive investor influences, and green bond verification mechanisms His scholarly output demonstrates increasing engagement with ESG factors and regulatory challenges in global markets. Analysis of his 15 most recent publications reveals a methodological emphasis on archival data spanning US, UK, Chinese, and Swiss contexts. Key trajectories include the growing intersection of digitalization with auditing standards, heightened scrutiny of climate disclosures, and the evolving role of institutional investors in financial oversight. His work consistently addresses regulatory gaps while maintaining technical rigor in accounting measurement. Eugster contributes to academic governance as a member of the European Accounting Review editorial board, reflecting peer recognition of his expertise. This service represents his primary documented scholarly contribution beyond publications. As an educator, he supervises doctoral research through courses like ‘Topics in Accounting Research’ and ‘Empirical Archival Methods’, while teaching bachelor/master courses in auditing, financial statement analysis, and valuation. His executive education involvement includes the CAS Internal Auditing program. Project leadership in ‘Weiterentwicklung IKS/RCM @ HSG’ demonstrates institutional engagement with risk control systems, though specific grant funding details remain undisclosed. While no dedicated laboratories are mentioned, his ‘Advanced Auditing & Audit Data Analytics’ course indicates integration of computational methods into assurance practices, suggesting emerging work in audit technology applications.
Agostino Cortesi is a Full Professor at Ca' Foscari University of Venice , affiliated with the Department of Environmental Sciences, Informatics and Statistics. He serves as Rector's Delegate for Research Quality Assessment and Deputy Coordinator of the Scientific Committee for the Innovation Ecosystem Project. His academic career includes a PhD in Applied Mathematics and Informatics from the University of Padova (1992), a postdoctoral fellowship at Brown University, and visiting professor roles at institutions such as the University of Illinois and École Normale Supérieure Paris. Research interests focus on software engineering , static analysis , security applications , and abstract interpretation . He has pioneered techniques for formal verification of software systems and explored cybersecurity in e-Government and robotics. His work spans over 200 publications in top journals and conferences (e.g., ACM TOPLAS, IEEE TSE, POPL, PLDI). Key contributions include advancements in abstract domains for behavioral property verification and security-oriented analysis frameworks. He has held leadership roles including Vice-Rector at Ca' Foscari, Dean of Computer Science programs, and Chair of the Department of Computer Science. Cortesi coordinates EU Horizon 2020 projects (e.g., Families_Share €1.6M) and regional initiatives like CEVID (€360K). He founded Factors , a university spin-off focused on robotic systems verification, which won the 2020 Veneto SmartCup ICT Prize. Education: PhD in Applied Mathematics and Informatics (1992, University of Padova) Editorial Roles: Co-Editor-in-Chief of Springer’s 'Services and Business Process Reengineering', and member of editorial boards for 'Computer Languages' and others Grants: Over €3M in EU and regional funding for projects in cybersecurity, Industry 4.0, and digital innovation Teaching includes courses on Software Correctness , Data Programming , and Computer Networks across Computer Science and Management programs. His research lab actively engages in industrial partnerships with Cisco, Leonardo, and AGID (Italy’s Digital Agency).
Kathleen A. McKee is an Associate Professor at the Regent University School of Law since 1999. She has held leadership roles including Director of Experiential Learning, Director of the LL.M. in Human Rights (2016–2017), and Director of the Center for Advocacy (2015–2016). Her academic background includes an LL.M. in Labor Law from Georgetown University, a J.D. from Catholic University Columbus School of Law, and a B.A. from the State University of New York at Albany. Her research focuses on human rights law, legal education, and policy analysis, with notable work on human trafficking, access to justice, and international parental abduction. Her publications span decades, reflecting expertise in both contemporary issues like modern slavery and longstanding challenges in legal aid accessibility. McKee is an admitted attorney in Virginia, D.C., North Carolina, and the U.S. Supreme Court, with extensive prior experience in legal aid organizations, including roles as Managing Attorney at Tidewater Legal Aid Society and Executive Director of Lumbee River Legal Services. She is also a Certified General and Family Mediator in Virginia.
Filippos Vokolos is an Associate Teaching Professor in the Department of Computer Science at Drexel University's College of Computing and Informatics, where he contributes to teaching and research in software engineering and related disciplines. Education: PhD in Computer Science, Polytechnic University MS in Computer Science, New Jersey Institute of Technology BS in Computer Science, New Jersey Institute of Technology Dr. Vokolos' research and teaching focus on the development of high-quality, dependable software systems. His expertise spans system architecture, principles of software design and construction, and verification and validation methods for large-scale software systems. He has taught foundational courses in software engineering, software design, programming languages, and dependable systems. His professional experience includes serving as Assistant Professor and Director of Software Engineering programs at Drexel University from 2002 to 2006, followed by a role as Technical Manager at SRI International starting in 2006. His return to Drexel in a senior teaching faculty role underscores his commitment to academic education in computing. Scientific Awards: No awards listed in available text. Dr. Vokolos has advised students and contributed to curriculum development, particularly in software engineering programs, though specific advisees and grants are not mentioned in the provided information. There is no mention of active labs or research teams in the current text.
Deepak Garg is a researcher at the Max Planck Institute for Software Systems (MPI-SWS) in Germany. His work primarily focuses on secure compilation , type theory , and formal verification of software systems. Conference Roles: He has served as an author and committee member in premier programming language conferences such as POPL , PLDI , ICFP , and ESOP since 2015. Research Interests include: Secure compilation techniques for hyperproperty preservation. Modal and refined type theories for cost analysis and concurrency. Formal verification of C code and probabilistic programs. Compiler correctness and decentralized multi-language verification. Contributions span foundational research in programming languages, with a focus on security, complexity, and concurrency. His work has been published in tracks like PriSC , OOPSLA , and ESOP , addressing topics such as data-flow back-translation and robust property preservation.
Maryam Mehri Dehnavi is an Associate Professor in the Department of Computer Science at the University of Toronto and a Principal Research Scientist at NVIDIA. She holds the Canada Research Chair in Parallel and Distributed Computing and leads the ParaMathics research group. Research focuses on high-performance computing , machine learning , sparse matrix optimizations , and compiler design for heterogeneous systems. Her work develops domain-specific languages , scalable numerical libraries , and auto-vectorization techniques for cloud and GPU platforms. Recent publications address LLM compression , sparse code translation , GPU kernel synchronization , and control flow optimization . Scientific recognition: Ontario Early Researcher Award (2021), NSF CRII Grant, NSERC New Frontiers in Research Fund. Current students: Mushegh Shahinyan , Martin Phan , Maryam Haghifam , and others. Former advisees: Kazem Cheshmi (NJIT), Zachary Blanco (MIT Lincoln Lab), Yuanxi Li (Amazon).
Dr. Liang (Leon) Dong is an Associate Professor in the Department of Electrical and Computer Engineering at Baylor University, where he conducts research and teaches in the areas of signal processing, wireless communications, and artificial intelligence. He leads the Laboratory of Signal Processing, Communications, and Artificial Intelligence, fostering innovation in next-generation communication systems, IoT, and AI-driven applications. PhD, Electrical & Computer Engineering, The University of Texas at Austin (2002) MS, Electrical & Computer Engineering, The University of Texas at Austin (1998) BS, Applied Physics with Minor in Computer Engineering, Shanghai Jiao Tong University (1996) Dr. Dong's research focuses on advancing digital signal processing and wireless communications, with strong emphasis on artificial intelligence applications. His work spans NextG wireless systems , IoT and smart cities , cyber-physical system security , and AI in healthcare and industrial automation . He applies deep learning to domains such as autonomous driving and drug discovery, and investigates energy-efficient, secure, and reliable communication protocols. The recent publications highlight a strong trend toward integrating AI into traditional signal processing and communications. Topics include mRNA vaccine stability prediction , smart city infrastructures , secure cyber-physical systems , and deep learning for biomedical and industrial applications . His work bridges theoretical innovation with real-world impact in defense, transportation, and public health. Dr. Dong has earned recognition as a Senior Member of IEEE and a Member of the American Physical Society. He has also served as Faculty Advisor for Baylor University's InterVarsity chapter. Senior Member, Institute of Electrical and Electronics Engineers (IEEE) Member, American Physical Society (APS) He has successfully advised numerous graduate and undergraduate students, many of whom now hold academic and industry positions at institutions like Stanford, Intel, NASA, L3Harris, and Cummins. His research is generously supported by Baylor's VP for Research, the National Science Foundation, NASA, the Department of Defense (TARDEC), the Michigan Department of Transportation, and industry leaders including Intel, L3Harris, ExxonMobil, and Denso. He actively mentors students through research assistantships and senior design projects. Dr. Dong leads the Laboratory of Signal Processing, Communications, and Artificial Intelligence, which provides a collaborative environment for advancing research in signal processing, communications, and AI. The lab supports graduate and post-doctoral researchers and offers opportunities for undergraduate involvement in AI programming, circuit design, and embedded systems.
Adrian Francalanza is a Professor in the Department of Computer Science at the Faculty of Information and Communication Technology, University of Malta. His research is centered on formal methods, runtime verification, and concurrency, with a focus on monitorability and distributed systems. His research interests include: Runtime Verification and Monitor Synthesis Session Types and Protocol Safety Concurrency and Actor-Based Systems Branching and Linear-Time Temporal Logics Probabilistic and Decentralized Monitoring Formal Tools for Cyber-Physical and Distributed Systems The recent publications highlight a strong trend in theoretical and practical advances in monitorability, especially for branching-time and probabilistic systems. His work bridges theory with implementation, often resulting in tools like STMonitor and DetectEr. There is a clear emphasis on session types, runtime enforcement, and the verification of communication protocols in real-world systems such as REST APIs and SMTP. Scientific awards include: Distinguished Paper Award at ECOOP 2025 Best Paper Award at DisCoTec 2022 He has been actively involved in advising and organizing major academic events. He served as Program Chair for GandALF 2024 and 2025, FORTE 2024, and VORTEX workshops. He led a three-year project funded by Rannis on Theoretical Foundations for Monitorability in collaboration with Reykjavik University. He has received grants and recognition for developing practical tools such as DetectEr and STMonitor, which support runtime monitoring of Erlang and session-typed systems. He is associated with several research teams and labs, including: Runtime Verification and Monitorability Research Group at University of Malta Collaborators on the DetectEr project Developers of STMonitor and polyLarva tools International collaborators at Reykjavik University and beyond
Roel Bloo is a University Lecturer in the Department of Mathematics and Computer Science at Eindhoven University of Technology. His research group focuses on Algorithms and Logics for Verification. His research spans theoretical computer science with emphasis on: Formal methods and verification techniques Lambda calculus and type systems Computational logic and term rewriting Explicit substitution models Publications (2001-2012) demonstrate consistent specialization in foundational aspects of computer science, particularly formal semantics of programming languages, type theory implementations, and equivalence proofs in computational systems. Teaching responsibilities include courses in Discrete Mathematics, Logic and Set Theory, and Automata Theory.
