Matteo Acclavio is an Assistant Professor in Computer Science at the School of Engineering and Informatics, University of Sussex, affiliated with the Foundations of Software Systems (FoSS) research group. A logician specializing in proof theory and its applications to computer science, his work bridges mathematical logic with concurrency theory and process calculi. Education: PhD in Mathematics, Aix-Marseille University, France Master in Discrete Mathematics and Foundations of Theoretical Computer Science, Aix-Marseille University Master in Mathematics, Roma Tre University, Italy Bachelor in Mathematics, Roma Tre University His research focuses on graphical proof systems, linear logic, modal logic, and concurrency theory. Publications highlight contributions to deep inference, sequent calculus, and the intersection of logic with distributed systems. Recent work explores logical frameworks for concurrency, such as choreographic programming, and graphical models for proof systems. He teaches courses like Operating Systems and maintains active collaborations in theoretical computer science.
Khalil Esper is a Researcher at the Department of Computer Science, Faculty of Engineering, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), where he works at the Chair of Computer Science 12 (Hardware-Software Co-Design). His research focuses on verification, energy optimization, and runtime requirement enforcement in embedded systems and MPSoCs. His educational background includes: Informatics Engineering from Aleppo University, Syria (2010-2015) European Master in Embedded Computing Systems (EMECS) from Rhineland-Palatinate University of Technology Kaiserslautern-Landau (Germany) and Norwegian University of Science and Technology (Norway) (2017-2019) Esper's research interests center around verification and model checking, energy optimization on MPSoC, real-time systems and embedded systems, and autonomic computing. His work particularly focuses on runtime requirement enforcement mechanisms for non-functional properties in multi-processor systems-on-chip, with applications extending to medical devices and human-robot interaction systems. He has developed approaches using finite state machines, reinforcement learning, and evolutionary algorithms to ensure system properties are maintained during execution. His publication record shows a strong trend toward applying formal methods and runtime enforcement techniques to increasingly complex systems, with recent work expanding into safety-critical applications like orthoses and human-robot interaction. The interdisciplinary nature of his research bridges computer science, embedded systems engineering, and biomedical applications. Esper has supervised multiple theses including: Sascha H.: Runtime Requirement Enforcement of Non-Functional Requirements on MPSoCs Using Fuzzy Logic (2022) Iana S.: Feedback-Based Control of Non-functional Program Execution Properties on Linux (2023) Philipp L.: Runtime Requirement Enforcement of Functional and Non-Functional Requirements of a Knee Orthosis Based on a Digital Twin (2024) Avinash N.: Runtime Requirement Enforcement of Safety Properties of an Ankle Orthosis Based on a Digital Twin (2024) Zhiyi T.: Generation of Environment FSMs Using Machine Learning Techniques (2025) Moustafa A.: Runtime Requirement Enforcement of Safety Properties of Human-Robot Interaction Based on a Digital Twin (2025) Florian K.: Runtime Requirement Enforcement of Safety Properties of Human-Robot Interaction (2025) He has been actively teaching courses on Approximate Computing and Embedded Systems since the 2021/2022 academic year, demonstrating his commitment to academic instruction alongside his research activities. Esper is involved in the InvasIC research project, part of the DFG Transregional Collaborative Research Center 89 on Invasive Computing, which explores novel approaches to resource management in parallel computing systems.
Henning Basold is affiliated with ENS Lyon , where he contributes as a Researcher . His work centers on theoretical computer science, particularly coinductive logic and corecursive proof search in programming languages and formal methods. In 2019, he authored two pivotal publications at ETAPS 2019 conferences: Coinduction in Uniform: Foundations for Corecursive Proof Search with Horn Clauses (ESOP 2019) Coinduction in Uniform: what's next? (HCVS 2019) These works explore coinductive techniques, Horn clauses, and future directions in formal verification and proof theory.
Vera Tripodi is an Associate Professor at the Department of Electronics and Telecommunications (DET) at Politecnico di Torino. Her academic career spans multiple institutions including the University of Milan 'La Statale,' University of Turin, University of Barcelona, University of Oslo, and Columbia University. She serves on the Single Guarantee Committee and is actively involved in gender equality initiatives. Dr. Tripodi earned her PhD in Logic and Epistemology from Sapienza University of Rome. Her academic journey includes postdoctoral research positions at prestigious international institutions and a research position at the University of Milan from July 2021 to March 2022. Her research focuses on the intersection of philosophy, technology, and gender. She specializes in bioethics, ethics of technology, feminist philosophy and ethics, and social ontology. Her work addresses critical contemporary issues including climate change ethics, reproductive technologies, AI ethics, and gender equality in philosophy and academia. She has made significant contributions to understanding the ethical dimensions of emerging technologies and their social implications. Dr. Tripodi's publication record demonstrates a consistent focus on ethical frameworks for technological development, gender issues in philosophy and society, and the philosophical implications of medical and technological innovations. Her work bridges theoretical philosophy with practical ethical concerns in rapidly evolving technological landscapes. Vice President of SWIP Italia (Society for Women in Philosophy) for two terms (2018-2021, 2021-2024) Member of the Bioethics Committee since 2019 Member of SIFA (Italian Society of Analytical Philosophy) since 2008 Associate Editor of AESTHETICS MAGAZINE since 2022 Member of the APHEX editorial board since 2010 Dr. Tripodi advises PhD students in philosophy programs at the University of Pavia and University of Eastern Piedmont. She teaches courses on Research Ethics in Dual-Use Technology, Gender and Diversity in Research, Ethics of Technology, and Bio- and Nanotechnologies in Medicine across various engineering programs at Politecnico di Torino. She also serves on course committees for Biomedical Engineering and Electronic, Telecommunications and Physics Engineering programs. She leads the NOW research project (2023-2025) titled 'Understanding Natural History: Nature, Evolution and Human Beings. A New Philosophical Framework' funded through the National Research PRIN program.
Ross Horne is a Senior Lecturer in the Department of Computer & Information Sciences at the University of Strathclyde, Glasgow, United Kingdom. He is a member of the StrathCyber and Mathematically Structured Programming research groups. Education: PhD (University of Southampton, 2012), BA (Oxford University, 2005) Prior Appointments: Research Fellow at University of Luxembourg (2018-2023), Senior Research Fellow at Nanyang Technological University (2015-2018), Associate Professor at Kazakh-British Technical University (2012-2015) Research Interests: Dr. Horne's work focuses on security and privacy protocols for digital systems, particularly addressing threats in payment technologies, ePassports, and decentralized identity management (e.g., Solid protocol). His theoretical contributions bridge concurrency theory, proof theory, and logic through applications to security verification and process calculi. Developed formal models for unlinkability in EMV payment protocols Created intuitionistic logical frameworks for process equivalence Explored graphical proof systems beyond formulaic representations Investigated legal-compliant AI for space systems (CubeSat anomaly detection) Scientific Contributions: He has published extensively in top venues including ACM CCS, IEEE CSF, LICS, and CONCUR. His 2017 CONCUR best paper introduced intuitionistic characterizations of bisimilarity. Principal Investigator for EU COST Action on Distributed Knowledge Graphs Co-developed privacy models adopted in Luxembourg parliamentary responses Advising: Currently accepting PhD students with strong mathematical and computer science skills for research in security/privacy of emerging systems. Former student Semen Yurkov completed a thesis on privacy-preserving smart card payments. Interdisciplinary Work: Collaborates with space lawyers through the Interdisciplinary Master Program in Space Resources. Projects include AI for CubeSat reliability and legal-compliant software certification frameworks.
Jens Michaelis is a Professor at the Faculty of Linguistics and Literary Studies, Bielefeld University, specializing in Computational Linguistics, Text Technology, and Linguistic Creativity. He serves as Deputy Head of the Department of Linguistics, Clinical Linguistics, Text Technology and Computational Linguistics, and provides academic advising for Computational Linguistics programs. His office is located at UHG U5-231, with contact details including telephone +49 521 106-6915 and email jens.michaelis@uni-bielefeld.de . Maintaining active research roles, he leads project B01 'Coercion as a creative mechanism in compositional interpretation' within the SFB 1646: Linguistic Creativity in Communication. His teaching responsibilities span modules like 23-CL-BaCL2.1 Selected methodological aspects 23-CL-BaCL5 Advanced Module 23-CL-BaCL6 Project Module 23-LIN-Ma3.1 Basics of Computational Linguistics 23-MeWi-HM3a_a Mathematical-linguistic language modeling across both undergraduate and graduate programs. His scholarly work focuses on formal grammar properties, syntactic mechanisms, and computational modeling of language. As an ordinary member of the Faculty Conference and Habilitation Committee, he contributes to academic governance while maintaining an extensive publication record in mathematical linguistics, minimalist grammars, and formal language theory.
Andrej Bogdanov is a Professor at the University of Ottawa in the School of Electrical Engineering and Computer Science . He earned his B.S. and M.Eng. from MIT and Ph.D. from UC Berkeley . Before joining Ottawa, he held positions at the Chinese University of Hong Kong , ITCS (Tsinghua) , DIMACS (Rutgers) , and the Institute for Advanced Study . He has served as a Visiting Professor at the Tokyo Institute of Technology (2013) and the Simons Institute (2017, 2021). Research Interests : Computational complexity, cryptography foundations, pseudorandomness, one-way functions, property testing, quantum algorithms, and sublinear-time algorithms. Teaching : Courses on Discrete Mathematics, Great Algorithms, Computational Complexity, and Cryptography at University of Ottawa, Chinese University of Hong Kong, and Rutgers University. Publications : 15+ recent works in TCC , CRYPTO , ICALP , RANDOM , and journals like Journal of Cryptology and Theory of Computing . Service : Program co-chair for SAC 2026 , and committee member for major conferences including CRYPTO , TCC , Eurocrypt , and FOCS . Advising : 12 current and former Ph.D./M.Phil. students, with postdoctoral advisees at institutions like IIT Palakkad and Academia Sinica . His work bridges theoretical computer science with applications in cryptography, quantum computing, and network security.
Cole A. DeForest is a Weyerhaeuser Endowed Professor and Associate Professor in the Department of Chemical Engineering at the University of Washington, where he also serves as Associate Chair for Graduate Studies. Additionally, he holds appointments as Associate Professor in Bioengineering and Adjunct Associate Professor in Chemistry, and is the Director of Education at the Molecular Engineering & Sciences Institute and a Core Faculty member at the Institute for Stem Cell & Regenerative Medicine. Dr. DeForest earned his Ph.D. in Chemical and Biological Engineering from the University of Colorado, Boulder in 2011 and completed postdoctoral training at Caltech before joining the UW faculty in 2014. His research focuses on developing user-programmable hydrogels with tunable biochemical and biophysical properties, utilizing cytocompatible bioorthogonal chemistries, particularly those initiated with light. His work spans several key areas including User-Programmable Biomaterials for Directing Dynamic Stem Cell Fate, Biomolecular and Tissue Engineering, Controlled Delivery of Therapeutics to Treat Disease, and Tool Development for Enhanced Proteomic Studies. His publication record demonstrates consistent high-impact contributions to biomaterials science, with numerous papers in Nature family journals, JACS, and Advanced Materials. His research approach integrates principles of rational design with fundamental concepts from material science, synthetic chemistry, and stem cell biology to create next-generation materials addressing health-related problems. UW College of Engineering Junior Faculty Award (2020) Society for Biomaterials Young Investigator Award (2020) Society for Biomaterials Mid-Career Award (2025) NSF CAREER Award (2017) UW Presidential Distinguished Teaching Award (2016) 35 Under 35 Award, AIChE Bioengineering Category (2017) Dr. DeForest has mentored numerous graduate students, postdocs, and undergraduates, many of whom have received prestigious fellowships including NSF GRFP, NIH F30, and HHMI Gilliam Fellowships. His lab has secured significant funding including collaborative grants from the Institute for Translational Health Sciences, the Institute for Stem Cells & Regenerative Medicine, and the Allen Institute for Brain Science. His educational leadership extends to directing the MolES Education program and teaching courses including Biological Frameworks for Engineers and Biomaterials Seminar.
Brigitte Pientka is a Professor at McGill University's School of Computer Science , where she leads the Computation and Logic group . She earned her PhD from Carnegie Mellon University in 2003 and previously studied at the University of Edinburgh and Technical University of Darmstadt. Education PhD in Computer Science, Carnegie Mellon University (2003) University of Edinburgh Technical University of Darmstadt Research Interests Her work focuses on the theoretical and practical foundations for building reliable software systems, combining logic, type theory, and verification with system-building. Key areas include: Type Theory and Dependent Types Logical Frameworks and Mechanized Metatheory Session-Typed Concurrency and Linear Logic Metaprogramming and Contextual Type Systems Theorem Proving and Formal Verification Functional Programming and Language-Based Security Professional Roles She has served as: PC Chair for ICFP'24 and CPP'24 General Chair for POPL'20 Executive Editor of Logical Methods in Computer Science Steering Committee Member for LICS, POPL, and ESOP Scientific Awards Dr. Pientka has received: Test of Time Award at PPDP'18 Humboldt Fellowship for research at MPI-SWS, Germany Labs & Teams She actively develops the Beluga programming language , a tool for mechanizing meta-theory proofs and type-driven program manipulation.
Dr. José Luis Calvo Rolle serves as a Professor in the Department of Industrial Engineering at the School of Engineering, Universidade da Coruña (UDC), specializing in Systems Engineering and Automation. His research focuses on intelligent control systems, fault detection, and virtual instrumentation within the Cybernetic Science and Technology Research Group. Teaches across multiple programs including Master's in Industrial Computing and Robotics, Textile Technology, and Occupational Risk Prevention Coordinates thesis supervision across Industrial Engineering and related disciplines His research spans intelligent control systems and optimization, with significant contributions in virtual sensors, fault detection, and AI-driven modeling for industrial applications. Current projects integrate machine learning with industrial processes for naval construction, wastewater treatment, and precision livestock farming, demonstrating cross-disciplinary impact from energy systems to agricultural technology. Recent publications reveal strong trends in applying deep learning to industrial metaverse frameworks, wastewater optimization, and livestock monitoring systems. His work bridges theoretical control engineering with practical implementations in energy management, naval manufacturing, and sustainable agriculture, frequently utilizing dimensionality reduction and one-class classification techniques. Dr. Calvo Rolle actively mentors students through thesis supervision across multiple engineering disciplines and coordinates research projects with diverse funding sources including the European Commission, Spanish National Research Agency, and industrial partners like Navantia and Telefónica. His laboratory work centers on the Cybernetic Science and Technology Research Group, developing testbeds for industrial automation, virtual instrumentation, and AI-driven monitoring systems. Current initiatives include digital twin implementations for naval manufacturing and smart energy management systems.
Achilleas Boukis is an Associate Professor in Marketing at the University of Birmingham's Birmingham Business School. With a PhD from Strathclyde University (2014) and a PGCert in Higher Education (2015), he focuses on branding, technology-enabled service interactions, and employee-customer dynamics in hospitality and sharing economy contexts. His work appears in top journals like Tourism Management , Journal of Business Research , and British Journal of Management . PhD: Strathclyde Business School (2014) PGCert: University of Sussex (2015) MSc: Athens University of Economics and Business (2008) BSc: Athens University of Economics and Business (2005) His research examines value creation in service interactions and branding strategies for blockchain technologies. Recent work includes NFT classification frameworks, employee social media impact on service performance, and customer threat dynamics in hospitality. He collaborates with institutions in the UK, Australia, and the US. Scientific achievements include: Highly Commended Award (Emerald/EFMD 2014) BAFTA 2014 Honourable Mention Active in curriculum development and online education, he supervises PhD/DBA students while integrating service-dominant logic into teaching methodologies to foster critical thinking and global collaboration.
Dr. Ayan Mukhopadhyay serves as a Senior Research Scientist in the Department of Electrical Engineering and Computer Science at Vanderbilt University's School of Engineering. Previously, he was a Post-Doctoral Research Fellow at Stanford Intelligent Systems Lab where he received the 2019 CARS post-doctoral fellowship. His academic journey includes a Ph.D. from Vanderbilt University's Computational Economics Research Lab with a doctoral thesis nominated for the Victor Lesser Distinguished Dissertation Award 2020. His research spans critical domains in smart infrastructure systems with particular focus on: Developing robust decision-making frameworks for cyber-physical systems under uncertainty Creating multi-agent solutions for emergency response optimization Designing machine learning approaches for urban mobility and energy management Building proactive incident detection pipelines using heterogeneous data sources Analysis of his recent publications reveals strong thematic continuity in applying artificial intelligence to real-world infrastructure challenges, particularly in transportation systems, emergency response, and energy management. His work consistently bridges theoretical AI advances with practical implementation in smart city contexts, demonstrating expertise in both algorithmic innovation and systems integration. Award highlights include: CARS Post-Doctoral Fellowship (2019) Best Paper Award at ICLR's AI for Social Good Workshop Victor Lesser Distinguished Dissertation Award Nomination (2020) Dr. Mukhopadhyay leads significant research initiatives through ScopeLab, focusing on creating deployable solutions for public transit, emergency response, and energy systems. His work on vehicle-to-building charging, traffic incident localization, and equitable transit network design demonstrates commitment to solving high-impact urban challenges through rigorous computational methods. Current projects involve developing simulation environments for non-stationary environments (NS-Gym) and explainable planning frameworks integrating formal logic with large language models.
Spyros Reveliotis is a Professor at the Stewart School of Industrial & Systems Engineering within the College of Engineering at Georgia Institute of Technology. His work bridges theoretical advancements with practical applications in automation and control systems. Education : PhD in Industrial Engineering (University of Illinois at Urbana-Champaign), B.Sc. in Electrical Engineering (National Technical University of Athens), M.Sc. in Computer Systems Engineering (Northeastern University) Reveliotis focuses on discrete event systems theory , emphasizing control of flexible automation and traffic management for multi-agent systems. His research integrates machine learning and Markov decision processes to optimize scheduling and coordination in complex environments like robotics and manufacturing systems. Recent trends in his publications address deadlock avoidance , min-time coverage in constrained spaces, and liveness enforcement for transport systems. These works often leverage combinatorial optimization and graph theory for scalable solutions. Scientific Awards : IEEE Fellow As a core faculty member of the Institute for Robotics and Intelligent Machines (IRI) , Reveliotis contributes to interdisciplinary robotics research. His affiliations with professional societies like INFORMS reflect his impact on operations research and automation fields.
Madhusudan Parthasarathy is a Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign, College of Engineering. His research focuses on software verification, formal methods, and logic in computer science, with significant contributions to trustworthy AI systems, program synthesis, and security. Ph.D. in Theoretical Computer Science (2002), Institute of Mathematical Sciences, University of Madras Research interests include automating software verification, building correct-by-design systems, and exploring synergies between machine learning and program synthesis. He pioneered visibly pushdown languages , impacting XML processing and program verification. His tools like VEX and Strand advanced security and heap reasoning. Recent articles focus on blockchain verification, timed automata, and learning logics from data. His work has been widely cited, with the visibly pushdown language paper alone generating over 940 scholarly entries. Best Paper Award, 19th USENIX Security Symposium (2010) He has advised numerous students and postdocs, with former advisees now at institutions like Purdue University and Google. His outreach initiatives include the ConTraIL privacy-preserving contact tracing project and the MASSIVELY EMPOWERED CLASSROOMS MOOC platform for Indian undergraduates. He teaches courses like CS 521: Advanced Topics in Programming Systems and CS 474: Logic in Computer Science , while actively serving on program committees for top-tier conferences such as POPL and PLDI.
Michael M. Zavlanos is the Yoh Family Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science at Duke University's Pratt School of Engineering. He also holds secondary appointments in the Department of Computer Science and the Department of Electrical and Computer Engineering. Currently serving as the Director of the Healthcare Systems Optimization program with Duke AI Health and as an Amazon Scholar with Amazon Robotics, his academic career spans control theory, optimization, and artificial intelligence with applications across multiple domains. Dr. Zavlanos received his educational foundation from prestigious institutions: Diploma in Mechanical Engineering from the National Technical University of Athens (NTUA), Greece (2002) M.S.E. in Electrical and Systems Engineering from the University of Pennsylvania (2005) Ph.D. in Electrical and Systems Engineering from the University of Pennsylvania (2008) His research program spans multiple interconnected domains, with a strong foundation in control theory, optimization, and learning methodologies . This theoretical work directly enables applications in robotics and autonomous systems , where his team develops algorithms for multi-robot coordination, motion planning under complex constraints, and network connectivity maintenance. A significant portion of his work addresses networked and distributed control systems , focusing on how multiple agents can coordinate effectively with limited communication. More recently, he has expanded his research into cyber-physical systems with healthcare applications, leveraging his expertise to optimize healthcare delivery systems through the Duke AI Health initiative. Dr. Zavlanos' work demonstrates a consistent trajectory from theoretical foundations to real-world applications. His early work established fundamental principles for maintaining connectivity in mobile robot networks, which evolved into more sophisticated approaches for temporal task planning and risk-averse decision making in uncertain environments. The most recent phase of his research integrates machine learning with traditional control theory to address complex healthcare system optimization problems. His significant contributions to the field have been recognized through prestigious awards: Office of Naval Research Young Investigator Program (YIP) Award (2014) National Science Foundation Faculty Early Career Development (CAREER) Award (2012) National Science Foundation Faculty Early Career Development (CAREER) Award (2011) Duke University Distinguished Faculty Rank (2019) Duke University Distinguished Professor designation (2018) As an educator, Dr. Zavlanos has taught courses including ME 627: Linear System Theory, ME 592: Research Independent Study, ECE 391/291: Projects in Electrical and Computer Engineering, and CEE 627: Linear System Theory. His research program has been supported by multiple grants from the National Science Foundation and the Office of Naval Research, enabling him to mentor numerous graduate students and postdoctoral researchers in the development of cutting-edge control and optimization algorithms. Dr. Zavlanos leads research efforts at the intersection of control theory, optimization, and artificial intelligence, with particular focus on translating theoretical advances into practical applications. His recent work with Duke AI Health represents a strategic expansion of his research portfolio into healthcare systems optimization, where he applies his expertise in algorithmic decision making to improve patient scheduling, resource allocation, and operational efficiency in medical settings. Through his Amazon Scholar role, he also contributes to advancing robotics technologies for real-world applications.
