Dr. Rasmus Ibsen-Jensen is a Lecturer in Computer Science at the University of Liverpool. Previously, he held a Postdoctoral position at IST Austria under Krishnendu Chatterjee and completed his PhD under Peter Bro Miltersen. Research Focus: Algorithmic game theory, strategy complexity in two-player zero-sum games, control flow graph algorithms, edit distance for automata, and theoretical biology applications. Teaching: Module Coordinator for second-year courses in database development (COMP207), C++ programming (COMP282), and industrial placement (COMP299). His work bridges computational game theory and formal verification, with recent publications exploring memory constraints in partial-information games, algebraic path properties in concurrent systems, and evolutionary spatial dynamics. While no scientific awards are explicitly mentioned in the provided text, his contributions to algorithmic complexity and interdisciplinary research (e.g., theoretical biology) highlight his academic impact.
Stefania Dumbrava is an Associate Professor of Computer Science at ENSIIE (École Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise) and a permanent member of the ACMES team in the SAMOVAR laboratory at Télécom SudParis, Institut Polytechnique de Paris. She is also actively involved in the Property Graph Schema Working Group and the European Research Network on Formal Proofs (EuroProofNet). Education PhD in Computer Science, Université Paris-Sud (2016) MSc in Computer Science, Jacobs University Bremen (2012) BSc in Mathematics, Jacobs University Bremen (2010) Research Interests Dumbrava's research lies at the intersection of formal methods and data management . She designs and verifies algorithms and systems for graph databases , with emphasis on property graphs , schema discovery , query optimization , and distributed graph processing . Recently, her work focuses on certifying large-scale distributed graph systems under the ANR JCJC VERDI project (2025–2029). Awards & Honors SIGMOD Best Paper Award 2023 – “PG-Schema: Schemas for Property Graphs” SIGMOD Research Highlight Award 2023 – “Threshold Queries” VLDB 2022 Best Regular Research Paper Runner-Up – “Threshold Queries in Theory and in the Wild” SIGMOD 2025 Distinguished Reviewer Award ICDE 2025 Best Program Committee Member Award EASST Best Software Science Paper Award, ICGT 2025 Students & Grants Dumbrava has supervised numerous research interns and is actively recruiting PhD students for her ANR VERDI project on verified foundations of large-scale distributed graph systems. She has also served on six PhD thesis committees as examiner since 2021. Labs & Teams She leads the ACMES research group within the SAMOVAR laboratory (Télécom SudParis, Institut Polytechnique de Paris), where her team develops formally verified graph-database engines and tools such as GRASP, VerDILog, and DatalogCert.
Scientia Professor Gary Froyland is a Professor at the University of New South Wales (UNSW), affiliated with the School of Mathematics & Statistics. He leads the ARC Laureate Centre for Dynamical Systems and Data and holds an Einstein Visiting Fellowship from the Einstein Foundation Berlin. His academic credentials include a BSc (Hons 1, Medal) in Pure and Applied Mathematics from the University of Queensland and a PhD in Mathematics from the University of Western Australia. Professor Froyland's research spans two primary domains: dynamical systems and optimization. In dynamical systems, he investigates the interplay of probability and geometry in nonlinear and chaotic systems, employing tools from ergodic theory, functional analysis, and differential geometry. His work extends to applications in oceanography, atmospheric science, and granular flows. In optimization, he focuses on decision-making in complex systems with uncertain information, developing novel approaches in mathematical programming that have been applied to mining, logistics, and medical treatment planning. His recent publications demonstrate a strong focus on coherent structures in dynamical systems, linear response theory, and applications to geophysical phenomena. The research shows increasing interdisciplinary collaboration, particularly with climate scientists and data analysts, reflecting a trend toward applying advanced mathematical techniques to real-world problems in environmental science and engineering. J.D. Crawford Prize (2025) Elected Member of the Academy of Europe / Academia Europaea (2024) ARC Laureate Fellow (2024-2029) Fellow of the Society for Industrial and Applied Mathematics (SIAM) (2021) Fellow of the Australian Academy of Science (2020) Vice-Chancellor's Award for Teaching Excellence - Postgraduate Research Supervision (2015) Professor Froyland actively supervises PhD and honors students, with current advisees including Kevin Felipe Kühl Oliveira, Nicholas Peters, and Kathrin Völkner. His research is supported by multiple grants, including an ARC Laureate Fellowship (2024-2029) for "Breakthrough mathematics for dynamical systems and data," an Einstein Visiting Fellowship (2022-2026), and several ARC Discovery Projects. His work has practical applications in climate science, mining optimization, and medical treatment planning, particularly in radiotherapy. He leads the ARC Laureate Centre for Dynamical Systems and Data, which brings together researchers to develop new mathematical approaches for analyzing complex dynamical systems. The center focuses on creating methods to identify coherent structures in spatiotemporal data, with applications spanning environmental science, social science, health science, and engineering.
Hannah Hoganson is an NSF Postdoctoral Fellow in the Department of Mathematics at the University of Maryland, mentored by Christian Rosendal after previously holding a Brin Postdoctoral Fellowship under Lei Chen. Her research bridges geometric group theory, low-dimensional topology, and descriptive set theory, with a focus on mapping class groups of infinite-type surfaces and topological groups. Her educational background includes a PhD from the University of Utah (2022) advised by Ken Bromberg, and prior graduate studies at Miami University where she investigated Thompson's groups. She has taught multiple calculus courses at UMD and the University of Utah, receiving exceptional student evaluations for her clarity and supportive teaching style. Hoganson's research explores the coarse geometry of mapping class groups, connections between topological groups and descriptive set theory, and geometric structures on infinite-type surfaces. Her work often combines algebraic, geometric, and topological methods to address fundamental questions about group actions and classification problems in low-dimensional topology. Her recent publications demonstrate a strong trend toward interdisciplinary approaches, integrating geometric group theory with descriptive set theory to analyze infinite-type mapping class groups and Polish groups. Key themes include geometric finiteness, coarse boundedness, and the interplay between algebraic structures and topological dynamics in infinite settings. NSF Postdoctoral Fellowship (DMS-2303365) Brin Postdoctoral Fellowship Hoganson has advised an undergraduate reading course in geometric group theory (Spring 2024) and served as a mentor for REU students at SUMSRI. Her current research is supported by NSF grant DMS-2303365, which funds her postdoctoral work on geometric and topological aspects of infinite-type surfaces and groups. She actively collaborates with researchers including George Domat, Sanghoon Kwak, and Robbie Lyman across multiple projects. She co-organizes the University of Maryland Geometry and Topology Seminar and has co-led specialized workshops including the Big Mapping Class Groups log cabin workshop in Young, AZ (2024) and the AWM special session on Women in Groups, Geometry and Dynamics (2023), fostering collaborative research environments in geometric topology.
Christina L. Garman is an Assistant Professor in the Department of Computer Science at Purdue University, where she joined in Spring 2018. Her research focuses on practical cryptography and cryptographic automation to make secure system development accessible to non-experts through error-resistant design methodologies. Her educational background includes: Bachelor of Science in Computer Science and Engineering from Bucknell University (2011) Bachelor of Arts in Mathematics from Bucknell University (2011) Master of Science in Engineering in Computer Science from Johns Hopkins University (2013) Doctor of Philosophy in Computer Science from Johns Hopkins University (2017) Professor Garman's work centers on real-world cryptographic system security, spanning protocol analysis (e.g., RC4 in TLS, Apple iMessage flaws), decentralized anonymous systems (Zerocash/ZCash), and cryptographic automation. She pioneered techniques for removing human error in cryptographic deployments through automated tools and frameworks. Her research bridges theoretical cryptography with practical implementation challenges in privacy-preserving technologies and secure infrastructure. Analysis of her 2021-2025 publications reveals expanding research horizons: hardware security vulnerabilities (Rowhammer, SGX), privacy network enhancements (Tor onion services), software supply chain security (SBOM tools), and advanced cryptographic protocols (zkSNARKs, MPC). This evolution demonstrates consistent focus on real-world security impact while diversifying into hardware-software cross-layer threats and formal verification methods for cryptographic implementations. Her major scientific recognitions include: NSF CAREER Award (2021) for cryptographic automation research ACM CCS Best Paper Award (2016) for iMessage security analysis IEEE Test of Time Award (2024) for foundational Zerocash work Professor Garman co-founded ZCash, a privacy-focused cryptocurrency based on her Zerocash protocol, and her NSF CAREER grant supports cryptographic automation development. Her research has received significant media coverage in The Washington Post, Wired, and The New York Times, highlighting real-world relevance. While specific student advising details aren't public, her active publication record indicates ongoing mentorship of graduate researchers in security and cryptography. Her work maintains strong industry connections through ZCash development and Tor network contributions, with recent projects like keyless CDNs demonstrating practical applications of cryptographic automation. She remains a leading voice in cryptographic research communities through conference participation and collaborative projects addressing evolving security challenges.
Michael Goldsmith is a Senior Research Fellow at the Department of Computer Science and Worcester College, University of Oxford. He holds multiple leadership positions including Director of the Oxford Martin Programme on AI Threat Detection, Associate Director of the Cyber Security Centre, and Co-Director of the Centre for Doctoral Training in Cybersecurity. His research bridges formal methods, concurrency theory, and practical cybersecurity applications. Goldsmith's research focuses on cybersecurity analytics including threat detection, risk management, and trust frameworks. He pioneered automated cryptoprotocol analysis and investigates multidisciplinary projects spanning mathematical models to socio-technical systems. His core interests include formal verification, AI threat landscapes, privacy architectures, and security protocol design. Analysis of his recent publications reveals strong emphasis on practical cybersecurity challenges: 63% focus on threat detection (especially insider threats), 22% on trust/risk frameworks, and 15% on formal methods applications. His work consistently integrates technical security mechanisms with human factors and organizational contexts. He currently advises Ahmed Salman and has supervised 10+ students including Mary Bispham, Rodrigo Carvalho, and Elizabeth Phillips. His research teams collaborate on projects funded by Technology Strategy Board, government agencies, and industry partners. Goldsmith leads the Oxford Martin Programme on AI Threat Detection and co-directs the Centre for Doctoral Training in Cybersecurity. His research group develops tools for security visualization (CyberVis), trust metrics, and identity management frameworks.
Justine Sherry is the A. Nico Habermann Associate Professor of Computer Science at Carnegie Mellon University, affiliated with the College of Engineering. She holds a PhD (2016) and MS (2012) from UC Berkeley and a BS/BA (2010) from the University of Washington. Her research focuses on networked systems, including middleboxes, cloud computing, congestion control, and hardware acceleration (e.g., SmartNICs/FPGAs). Notable projects include Pigasus (open-source 100Gbps IDS), APLOMB (cloud-based middlebox scaling), and BlindBox (encrypted traffic scanning). Her academic roles include serving on the SIGCOMM CARES Committee, DARPA ISAT Study Group, and ACM CoNEXT Steering Committee. Awards include the Alfred P. Sloan Fellowship, VMware Systems Award, and IETF Applied Networking Prize. She advises over 15 students and collaborates with industry partners like Intel and VMware. Research highlights include radical shifts in datacenter architectures (SmartNIC compute control), fairness in congestion algorithms (BBR analysis), and database-proxy innovations (Tigger with eBPF). Her teaching emphasizes systems as science labs, integrating experimental design and hypothesis testing into projects. Education: PhD UC Berkeley (2016), MS UC Berkeley (2012), BS/BA University of Washington (2010) Labs/Teams: CyLab, SNAP Research Group, CMU Portugal Collaboration Grants: NSF, Intel, Google Faculty Awards
Cezary Kaliszyk is a Professor in Theoretical Computer Science at the University of Melbourne, previously affiliated with the University of Innsbruck. He is actively involved in research and leadership in formal methods, automated reasoning, and machine learning for theorem proving. Research Interests: Automated Reasoning and Interactive Theorem Proving Formalized Mathematics and Proof Automation Machine Learning for Logic and Theorem Proving Integration of AI with Proof Assistants (Coq, Isabelle) Dependent Type Theory and Higher-Order Logic His recent publications (2023–2025) span topics in dependently-typed logic, learning for proof guidance, formalization of surreal numbers, and blockchain-based formal methods. The works consistently bridge formal logic with machine learning, emphasizing automation, explainability, and cross-system integration. Scientific Leadership and Projects: Principal Investigator, ERC project FormalWeb3 Lead Developer, CoqHammer , Tactician , ProofWeb WG5 Leader, COST Action EuroProofNet (until 2024) Contributor to HOL(y)Hammer , Isabelle Enigma He supervises multiple PhD students and has mentored several graduates in formal methods and AI. He teaches courses in theoretical computer science, logic, and machine learning. There are no listed awards in the provided data, but his extensive publication record and project leadership indicate significant recognition in the field. Labs and Research Groups: He leads a research group focused on formal methods and learning-based reasoning, collaborating internationally on projects involving proof automation, formal libraries, and semantic technologies.
Cristian Cadar is a Professor in the Department of Computing at Imperial College London, leading the Software Reliability Group . His research focuses on improving software reliability and security through practical techniques in software engineering, computer systems, and program analysis. Education: Ph.D. in Computer Science, Stanford University M.Eng. in Computer Science, MIT B.S. in Computer Science and Mathematics, MIT His research interests center on software engineering and software security , particularly symbolic execution , dynamic symbolic execution (DSE) , and multi-version execution . Current work explores techniques for scalability, constraint solving, and runtime security in software systems. Key trends in his recent articles include optimizing symbolic execution for testing, addressing path explosion in constraint-based test generation, and advancing multi-version execution for dynamic software updates. His publications also cover program analysis , automated testing , and formal methods for software reliability. Awarded prestigious honors such as the Humboldt Research Award (2024) , ERC Consolidator Grant (2018) , and IEEE New Directions Award (2022) . Other accolades include the BCS Roger Needham Award (2019) and SIGOPS Hall of Fame (2018) . Cadar supervises PhD and postdoctoral researchers in software reliability and security. His group has secured grants from the ERC and EPSRC , including a Consolidator Grant (2018) and Early-Career Fellowship (2013) . He actively contributes to conference organizing committees and editorial boards. The Software Reliability Group at Imperial College, led by Cadar, specializes in techniques like KLEE and EXE for automated testing. Their work has been adopted by industry partners such as Fujitsu, IBM, and Microsoft, particularly in runtime security tools like WIT .
Gioele Zardini is the Rudge (1948) and Nancy Allen Assistant Professor at MIT's Department of Civil and Environmental Engineering (CEE), with affiliations to the Laboratory for Information and Decision Systems (LIDS) and the Institute for Data, Systems, and Society (IDSS). He holds a PhD from ETH Zurich and previously worked as a postdoctoral scholar at Stanford University. His research focuses on co-design of complex systems, autonomous systems, and game-theoretic modeling of transportation networks. Education: BSc and MSc in Mechanical Engineering and Robotics from ETH Zurich (2017–2019), PhD in 2023. He has held visiting roles at nuTonomy Singapore, Stanford, and MIT. Research interests include co-design methodologies, autonomous vehicle systems, compositionality in engineering, and strategic interactions in mobility networks. Recent work emphasizes scalable fleet coordination, safety-critical robotics, and user-centric transportation solutions. Notable awards include the 2024 ETH Doctoral Dissertation Award (Silver Medal), Best Paper at ITSC 2021, and federal grants for enhancing urban transit equity. He leads the Zardini Lab, fostering interdisciplinary collaboration in systems engineering and autonomy. Grants and advising: Received federal grants for transit accessibility projects. His work on Autonomy Talks has produced over 180 recorded lectures, promoting knowledge exchange in autonomous systems. Labs/Teams: Principal Investigator at LIDS, affiliate at IDSS, and founder of the Zardini Lab, focusing on systems co-design, mobility innovation, and game-theoretic frameworks.
Franz Franchetti is the Kavčić-Moura Professor of Electrical & Computer Engineering at Carnegie Mellon University. He serves as Associate Dean for Research and Director of the Engineering Research Accelerator at CMU. Education: Ph.D. in Computational Mathematics (Vienna University of Technology, 2003) M.Sc. in Technical Mathematics (Vienna University of Technology, 2000) His research interests focus on automatic performance tuning and program generation for emerging parallel computing platforms , including multicore CPUs , GPUs , and 3DIC chip design . He leads the SPIRAL effort to automate highly optimized software libraries and explores domain-specific compiler transformations in HPC applications for smart grids and material sciences . Recent work extends SPIRAL to quantum computing . The scientific awards Franchetti has received include the Gordon Bell Prize (2006) , HPC Challenge Class II Award (2010) , and the CIT Dean's Early Career Fellowship (2013) . He and his students have won multiple Best Paper Awards at HPEC, DAC, and ISPA ACM TODAES Best Paper (2014) Student Research Competition wins (PACT 2024, CGO 2023) Franchetti has advised students like Richard Veras and Thom Popovici . He has secured significant grants from agencies such as DARPA, DOE, NSF, and industry partners (Intel, NVIDIA, Mercury). He co-founded SpiralGen, Inc. and holds leadership roles in organizations like ASciNA Western Pennsylvania and as Honorary Consul of Austria in Pittsburgh.
Matthew Santa serves as Professor of Music Theory and Chair of the Music Theory and Composition Area at Texas Tech University School of Music, with prior teaching appointments at Queens College and Hunter College. His leadership shapes curriculum development and academic initiatives within the department. Academic credentials include advanced degrees from Louisiana State University and The City University of New York, establishing foundational expertise in theoretical frameworks and analytical methodologies. Research focuses on post-tonal analysis , diatonic set theory , and parsimonious voice leading , bridging complex theoretical concepts with practical pedagogy. His work integrates popular music analysis and metrical studies, emphasizing accessibility for diverse learners through innovative teaching resources. Publications demonstrate evolving scholarly trends from late-20th century set theory toward contemporary applications in musical form and rhythm. Recent textbooks synthesize Rothstein, Krebs, and Mirka's theories into unified analytical approaches for undergraduate and graduate education. Scientific recognition includes: MTSNYS Young Scholar Award (1998) Mentorship encompasses graduate and undergraduate students across composition and theory disciplines, though specific advisees aren't documented in source materials. No grant funding details appear in available records. Collaborative projects include the Flute/Theory Workout series with Lisa Garner Santa and Thomas Hughes, blending performance technique with theoretical concepts through MIDI accompaniment systems.
Sanjay Jain is a Provost's Chair Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). His research focuses on theoretical computer science with particular emphasis on inductive inference, recursion theory, complexity theory, and computational learning theory. Education: B.Tech. in Computer Science from Indian Institute of Technology Kharagpur, India (1986) M.S. in Computer Science from University of Rochester, USA (1988) Ph.D. in Computer Science from University of Rochester, USA (1990) Professor Jain's research spans multiple areas of theoretical computer science. His primary contributions are in computational learning theory, where he has made significant advances in understanding the intrinsic complexity of language identification and the limits of inductive inference. His work on recursion theory explores fundamental questions about computability and complexity, while his research in complexity theory addresses structural aspects of computational problems. A notable achievement was his work on "Deciding Parity Games in Quasipolynomial Time," which won the prestigious STOC 2017 best paper award and later the EATCS-IPEC Nerode Prize. Professor Jain's publication record shows a consistent focus on theoretical foundations of computer science, particularly in learning theory and computational complexity. His recent work has expanded into automatic structures, semiautomatic models, and connections between computational learning and algebraic structures. There is a clear progression from foundational work on language identification to more complex models involving automatic functions, transducers, and connections to mathematical logic. Scientific Awards: STOC 2017 Best Paper Award for "Deciding Parity Games in Quasipolynomial Time" EATCS-IPEC Nerode Prize (2021) Professor Jain has served on the editorial board of Information and Computation and has been actively involved in the academic community through program committee memberships for major conferences including COLT, ALT, LATA, TAMC, and PRICAI. He has held leadership roles as program co-chair for ALT 2000 and ALT 2013, and conference chair for ALT 2005. His work has been supported by various research grants, though specific details are not provided in the available materials. Professor Jain leads research in theoretical computer science at NUS, where he has built a strong research group focused on computational learning theory and related areas. His work often involves collaborations with researchers from around the world, particularly with Frank Stephan, with whom he has co-authored numerous papers. His research group has made significant contributions to understanding the fundamental limits and possibilities of computational learning models.
Vadim Lozin is a Professor of Mathematics at the University of Warwick, affiliated with the Department of Mathematics within the School of Mathematics. His research interests span graph theory, combinatorics, and discrete mathematics, focusing on areas such as clique-width, Ramsey numbers, and structural graph theory. He has held visiting positions at institutions including the Université Paris-Dauphine, EPFL, and KAUST. Lozin has received several accolades, including the Best Paper Award for 'Linear Ramsey numbers' in 2018 and a 2024 award at the International Symposium on Algorithms and Computation. His work involves collaborations with global researchers and contributions to conferences like IWOCA and WG. Lozin serves on editorial boards for journals such as Discrete Applied Mathematics and Electronic Notes in Discrete Mathematics . His research explores foundational problems in graph theory, with applications in algorithm design and complexity analysis. Lozin’s publications include studies on union-closed sets, functional graph properties, and algorithmic approaches to graph parameters. He has also contributed to books like Words and Graphs , bridging formal language theory with graph structures. His grants focus on clique-width and stability in graphs, reflecting his commitment to advancing theoretical and applied discrete mathematics.
Francisco Barillas Bedoya is an Associate Professor at the School of Banking and Finance within the UNSW Business School, University of New South Wales. His research focuses on theoretical and empirical asset pricing, particularly portfolio choice, asset pricing tests, macrofinance, and term structure of interest rates. He has published extensively in top-tier journals like the Journal of Finance and Management Science. PhD from New York University MA from University of British Columbia BSc from Trent University His recent publications analyze Sharpe ratios for model comparison, speculative behavior in bond markets, and risk premia in fixed income markets. While no formal awards are listed, his work intersects financial economics, econometrics, and computational methods. Office: Level 3, Room 333C, Ref E12 Email: f.barillas@unsw.edu.au
