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Sagiv ShmuelView profile

Professor

• Software verification
• Shape analysis
• Smart contracts
• +7 more

Prof. Sagiv Shmuel is a Full Professor at Tel-Aviv University's Department of Computer Science. He has held various academic roles, including Associate Professor (2004–2005), Senior Lecturer (2000–2004), and visiting positions at institutions such as the University of Chicago and University of Copenhagen. His research focuses on software verification, shape analysis, smart contracts, and programming languages. Education: Ph.D. in Computer Science, Technion (1986–1990) B.A. in Computer Science, Technion (1982–1985), cum laude Research Interests: His work addresses challenges in static analysis, formal verification, and program analysis. Notable areas include invariant inference, smart contract security, and parametric shape analysis. These contributions have led to practical tools like Ivy and the foundation of Certora, a company specializing in smart contract verification. Awards: ACM Fellow (2016) Friedrich Wilhelm Bessel Research Award (2002) Microsoft Outstanding Collaborator Award (2016) Grants & Leadership: Principal Investigator (PI) of a Senior ERC Grant (1.57M Euros) for software composition verification Editor of Foundations and Trends in Programming Languages Chair of program committees for POPL, SAS, and other leading conferences His research has been applied to real-world systems, such as improving the Java concurrent library and ensuring kernel extension security in Linux.

Anthony Widjaja LinView profile

Professor

• Automated Reasoning
• String Constraint Solving
• Formal Language Theory
• +5 more

Anthony Widjaja Lin is a Full Professor (W3) in Theoretical Computer Science (Automated Reasoning) and Max-Planck Fellow at University of Kaiserslautern-Landau, Germany. Previously, he was an Associate Professor in Programming Languages at Oxford University Department of Computer Science and Governing Body Fellow at Kellogg College (2016-2019), and an Assistant Professor at Yale-NUS, Singapore (2014-2016). He completed his PhD in Informatics at University of Edinburgh in 2010 under Leonid Libkin (supervisor) and Richard Mayr (co-advisor). Dr. Lin's educational background includes: PhD in Informatics, University of Edinburgh (2010) MSc, University of Toronto BSc (Honours), Melbourne University Dr. Lin's research focuses on automated reasoning, particularly over strings, formal language theory, learning/synthesis, and foundations of machine learning. His work has significant applications in software verification, program synthesis, querying graph databases, and computer security. He leads the development of the OSTRICH string solver, which won the QF_S (Single Query Track) in SMT-COMP 2023. His research has evolved from foundational work on string constraint solving to applications in verification of string-manipulating programs and more recently to connections with machine learning models like transformers. Dr. Lin has received numerous prestigious awards including an ERC Consolidator Grant (2023), Amazon Research Award (2021), ERC Starting Grant (2017), Google Faculty Award (2017), and the LICS Kleene Award (2010). Dr. Lin has advised several PhD students to completion, including Pascal Bergsträßer, Chih-Duo Hong, and Xuan-Bach Le, who have gone on to become Assistant Professors at institutions like National Chingchi University and Nanyang Technical University. He currently supervises multiple PhD students and postdocs working on string solving, automated reasoning, and verification. Dr. Lin leads the AV-SMP project (Algorithmic Verification of String-Manipulating Programs), which was supported by an ERC Starting Grant (2017-2022) and an Amazon Research Award (2021). His research group develops tools like OSTRICH, SLOTH, and CertiStr for string constraint solving and verification.

Ekkart KindlerView profile

Associate Professor

• Model-Based Software Engineering
• Process Mining
• Petri Nets
• +4 more

Ekkart Kindler is an Associate Professor in the Department of Applied Mathematics and Computer Science at DTU Compute, Technical University of Denmark. His research focuses on model-based software engineering, process mining, and road condition assessment using vehicle sensor data. He leads the Competence Centre for Model-Based Software Engineering, supporting industry adoption of advanced software development methodologies. Education: M.Sc. (1990), Ph.D. (1995) from Technische Universität München; Habilitation in Computer Science (2001) from Humboldt-Universität zu Berlin. He held visiting professorships at German universities (2000–2007) and has extensive experience in formal methods, business process modeling, and Petri nets. Research interests include declarative process modeling, complexity metrics for cognitive load assessment, and the integration of formal methods into industrial software development. His work contributes to UN Sustainable Development Goals related to sustainable infrastructure (SDG 9) and innovation (SDG 9). Notable collaborations include road condition assessment projects using vehicle sensor data (LiRA-CD dataset) and contributions to Petri net standards (PNML). He has supervised PhD students such as K. I. Simonsen (protocol software) and A. Skar (road assessment). Grants and projects: Live Road Assessment with Vehicle Sensors (2019–2022), Model Transformation Tools (2013–2016), and waste management modeling (2012–2016). Active in open-source datasets and tool development for indoor climate control (climify.org).

• Asset Management
• Fixed Income
• Bank Regulation
• +4 more

Philippe Oster is a Lecturer at the Institute of Financial Services Zug (IFZ) within the Lucerne School of Business. His academic roles include teaching courses on Fixed Income (CFA-linked), Derivatives and Structured Products, and CAS Asset Management programs. He holds a PhD in Empirical Capital Market Research and Econometrics from Zeppelin University, along with advanced qualifications in banking and finance. His research focuses on fixed income instruments, bank capitalization, and regulatory impacts on financial markets. Education highlights include: PhD in Empirical Capital Market Research (2017–2021) MSc Banking & Finance (2008–2010) BSc in Business Administration (2006–2008) Eidg. Dipl. Betriebsökonom FH (2002–2005) Research interests span hybrid capital instruments, bank regulation, and ESG investing. His publications analyze topics like CoCo bonds, regulatory effects on wealth managers, and fixed-income strategies. Notable works include Hybridkapital – Finanzierungsinstrument und Kapitalanlage Praxishandbuch and contributions to the European Financial Management journal. Professional experience includes roles as Senior Portfolio Manager at Baloise Asset Management and leadership positions in portfolio management at Zugerberg Finanz and Capra Ibex Investment Partners. He has conducted over 30 presentations on topics like risk management, emerging markets, and compliance in wealth management. Key projects include the IFZ Vermögensverwalter Guide series, studies on sustainable investments, and collaborations with financial technology providers. His work bridges academic research and industry practice, emphasizing practical applications of financial theory.

Alan G. SutherlandView profile

Professor

• Medicinal Chemistry
• Organic Chemistry
• Biochemistry
• +5 more

Dr. Alan G. Sutherland is a Practitioner in Residence in the Chemistry and Chemical & Biomedical Engineering Department at the University of New Haven since 2011. He also works as a Medicinal Chemist at L2 Diagnostics in New Haven. Prior to joining UNH, he held research roles at Wyeth Research (1995–2010), where he advanced from Senior to Principal Research Scientist, and earlier faculty positions at the University of Exeter and University of North London in the UK. B.Sc. in Chemistry , University of Edinburgh Ph.D. in Chemistry , University of East Anglia Dr. Sutherland's research focuses on developing anti-inflammatory, antibacterial, antiviral, and antitumor agents . He leads a NEI-supported program on macular degeneration treatments and contributes to NIH and DoD-funded projects as a Co-Investigator. His work integrates medicinal chemistry , biocatalysis , and structure-based drug design to target diseases like AIDS , Gram-positive bacterial infections , and cancer . Key publication trends include anti-inflammatory agents , glycopeptide antibiotics , asymmetric synthesis methods , enzymatic resolutions , and inhibitors of bacterial cell division proteins (FtsZ/ZipA) . His studies span organic chemistry , pharmacology , and biocatalysis , emphasizing practical applications in drug discovery.

Robert HeskethView profile

Professor

• Sustainability
• Environmental Engineering
• Green Engineering
• +6 more

Robert Hesketh is a Full Professor of Chemical Engineering at Rowan University's Henry M. Rowan College of Engineering. He holds a Ph.D. and B.S. in Chemical Engineering from the University of Delaware and the University of Illinois, respectively. His research focuses on sustainability, green engineering, process optimization, and computational methods. Key areas include novel separations (crystallization, adsorption), reaction engineering (green chemistry, combustion kinetics), and fluid dynamics (agitation, multiphase flow). Recent work emphasizes machine learning applications in sustainability, such as predicting environmental impacts and optimizing industrial processes like pipeline flushing. He has collaborated with industry partners like Johnson Matthey on projects involving PGM recovery and green engineering design. Hesketh is also active in advancing pedagogical innovation, including student-industry collaboration programs and integrating computational tools (Python/MATLAB) into curricula. His work has been recognized through over 120 publications and grants totaling $1.3M in funding. Education: Ph.D., Chemical Engineering, University of Delaware; B.S., Chemical Engineering, University of Illinois. Research Interests: Sustainability engineering, green chemical processes, fluid dynamics, and AI-driven process design. His projects address environmental challenges through interdisciplinary approaches, combining experimental and computational methods. Grants & Awards: Led three industry-funded grants (2013–2016) focusing on green engineering and PGM recovery. His work bridges academia and industry, fostering innovation in sustainable manufacturing and pollution prevention.

Matthew CampbellView profile

Professor

• Engineering Design
• Computer-Aided Design
• Computational Methods
• +4 more

Matthew Campbell is a Professor at the School of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University. He holds the title of Hans Fischer Senior Fellow at the Technical University of Munich (TUM) Institute for Advanced Study (TUM-IAS). His academic journey includes a PhD from Carnegie Mellon University (2000) and prior roles as an Associate Professor at the University of Texas at Austin. Education: BSc and MSc in Mechanical Engineering from Carnegie Mellon (1995-1997), PhD in Mechanical Engineering (2000). He founded the Automated Design Lab at UT Austin and specializes in computational design tools that integrate engineering, computer science, and cognitive psychology to enhance design efficiency and quality. Research focuses on automated design synthesis, topology optimization, and human-computer collaborative systems. His work bridges algorithmic innovation with practical engineering applications, emphasizing multi-physics computational platforms and generative design methods. Awards include the NSF CAREER Award (2005) and multiple best paper awards in engineering design and computational methods. His publications span design automation, optimization, and interdisciplinary methodologies. Key contributions include the CDS platform for multi-physics design synthesis and foundational work on automated concept generation. Current projects involve integrating qualitative/quantitative data in experimental design and advancing fluid channel topology optimization.

Ravi ChughView profile

Associate Professor

• Functional Programming
• Program Synthesis
• Graphical User Interface
• +3 more

Ravi Chugh is an Associate Professor of Computer Science at the University of Chicago, serving as Director of Undergraduate Studies since July 2023. He holds a Ph.D. from the University of California, San Diego (2013). His research focuses on programming languages and human-computer interaction, with a particular emphasis on direct manipulation programming systems, structured editors, and functional programming. Chugh has received the NSF CAREER Award (2017) and the Neubauer Faculty Fellowship (2015) for his contributions to undergraduate education and innovative research. Research Interests: Ravi’s work bridges programming language theory and interactive systems design. He develops tools like Deuce and Sketch-n-Sketch to create more user-friendly IDEs and GUI-driven programming environments. His research spans program synthesis, type systems, bidirectional evaluation, and live coding interfaces. Awards: - 2017 NSF CAREER Award - 2015 Neubauer Faculty Fellowship Advising & Grants: Chugh has advised numerous students (listed in detail below) and contributed to grants focused on HCI and programming language tooling. He is actively involved in organizing conferences like POPL, PLDI, and CHI, holding roles such as PC member and program chair. Labs & Groups: He leads the Programming Languages Group at UChicago, emphasizing practical applications of language design and theoretical foundations. His team explores topics like declarative UIs, live bidirectional systems, and creative coding education.

Christoph SeidlView profile

Associate Professor

• Software Engineering
• Virtual Reality
• Software Visualization
• +5 more

Christoph Seidl is an Associate Professor in the Department of Software Engineering at the IT University of Copenhagen. His research focuses on software visualization, software archaeology, and the application of virtual reality in software engineering tasks. He leads the Immersive Software Archaeology project, exploring collaborative systems and legacy system analysis in virtual environments. Key research areas include software product lines, feature modeling, and model-driven development. Seidl has received awards such as the SoSyM Best Reviewer Award (2018) and SPLC'19 Distinguished Reviewer Award (2019). His work emphasizes innovative tools for software exploration, including immersive 3D visualization and collaborative note-taking systems in VR. He has published extensively on topics like variability management, configuration testing, and domain-specific languages. Research trends in his articles highlight advancements in using VR for software archaeology, collaborative software exploration, and methodologies for managing software evolution. His projects address challenges in legacy system understanding, feature model synthesis, and automated testing for configurable systems. Seidl collaborates internationally, with projects funded by the Independent Research Fund Denmark. His contributions span academic publications, datasets (e.g., VaMoS 2022 artifacts), and tool development for software product line engineering.

• Software Engineering
• Formal Methods
• Automatic Test Generation
• +5 more

Prof. Maria Christakis is a full professor at TU Wien's Faculty of Informatics, leading the Rigorous Software Engineering Group and the Software Engineering Research Unit. Her research focuses on developing reliable software tools and improving developer productivity through formal methods, automatic test generation, and program analysis. She holds a PhD from ETH Zurich and a diploma from the National Technical University of Athens. Her work bridges verification and systematic testing, with notable contributions to fuzzing, static analysis, and neural network certification. Key projects include tools like Harvey (smart contract fuzzer), DeepSearch (neural network attack framework), and Nomos (specification language for machine learning models). Her research has received awards including the Best Presentation Award at FSE'20 and a Distinguished Paper Award at ICSE'16. She advises multiple PhD and master's students and teaches courses in advanced software engineering and formal methods. Current projects explore green fuzzer benchmarking, compositional smart contract verification, and testing code translation models. Grants: Austrian Science Fund (FWF) doctoral school on Automated Reasoning Labs/Teams: Rigorous Software Engineering Group, Software Engineering Research Unit

Reinhard BernsteinerView profile

Adjunct Professor

• Internet of Things
• Augmented Reality
• Knowledge Management
• +5 more

Reinhard Bernsteiner is an Adjunct Professor at the University of Nebraska at Omaha (Department of Information Systems & Quantitative Analysis) and a long-standing lecturer at Management Center Innsbruck, where he teaches in programs including Industrial Engineering & Management (Master), Management, Communication & IT (Bachelor/Master), and Mechatronics (Bachelor). His academic career spans over two decades, with additional roles such as Lecturer at the Higher Technical Vocational School for Industrial Engineering since 1995. He holds a Dr. from the University for Health and Life Sciences (2004–2008) and a Mag. from Johannes Kepler University (1985–1989). Bernsteiner's research centers on emerging technologies and their societal impacts. Primary interests include: Internet of Things (IoT) : Applications in education and industry Augmented Reality (AR) : Industrial training and educational tools Knowledge Management : Frameworks for open innovation AI & Digital Transformation : Ethical implications and business integration Educational Technology : Enhancing learning through VR, gamification, and data analytics His 15 most recent publications (2024–2025) reveal a strong focus on IoT/AR in vocational education, AI-driven project management, blockchain in healthcare, and digital transformation challenges. Common themes include empirical studies on technology adoption, systematic literature reviews, and interdisciplinary approaches bridging engineering, business, and pedagogy. Awards & Recognition: Best Paper Award at EDULEARN for Motivating Students to Acquire Digital Skills (2021) Bernsteiner has supervised 100+ bachelor, diploma, and master theses, primarily exploring IoT, AR, data science, and business process optimization. Students investigated topics ranging from AI ethics to sustainable supply chains, reflecting his interdisciplinary mentorship. No grant or lab affiliations were documented.

Mirco TribastoneView profile

Professor

• Stochastic Processes
• Dynamical Systems
• Performance Engineering
• +4 more

Dr. Mirco Tribastone is Full Professor of Computer Science at IMT School for Advanced Studies in Lucca, Italy, where he leads the SySMA research unit and serves as Deputy Rector. His research focuses on quantitative modeling of concurrent and distributed systems using stochastic processes and differential equations. Primary research streams: Algorithms for aggregation of dynamical systems Performance self-adaption of software systems Inference methods for probabilistic programs Formal methods for biological systems Professor Tribastone has supervised numerous PhD students and leads research projects on cyber-physical systems and adaptive software. His tool development includes ERODE for differential equation analysis and DiffLQN for layered queuing networks. Recent publications demonstrate advanced work in model reduction techniques for chemical reaction networks, optimal autoscaling for microservices, and novel approaches to quantum circuit verification.

• Formal Methods
• Cyber-Physical Systems
• Temporal Logic
• +3 more

Eleonora Nesterini is a PreDoc Researcher at TU Wien's Faculty of Informatics, specializing in Cyber-Physical Systems. She is affiliated with the E191-01 department and involved in the ProbInG project (2020–2025). Her research focuses on formal methods for system verification, particularly mining temporal logic specifications and applying them to safety-critical systems. She holds an ORCID identifier: 0000-0002-1229-5331 . Her work bridges theoretical computer science with practical applications in predictive safety monitoring and multi-class classification systems. Recent projects include developing tools like ShapeIt for automated specification generation and analyzing hyperproperties in cyber-physical systems. Eleonora's research has been published in venues such as ACM Transactions on Embedded Computing Systems and Runtime Verification conferences. She actively contributes to advancing formal methods through interdisciplinary approaches combining machine learning and temporal logic frameworks.

• Formal Methods
• Program Synthesis
• Recursive Programming
• +3 more

Eva Maria Wagner is a PreDoc Researcher in the Department of Formal Methods in Systems Engineering at Vienna University of Technology (E192-04). Her contact email is eva.maria.wagner@tuwien.ac.at, and she works in Room HA0305 at Favoritenstrasse 9, Vienna. Education: Diploma Thesis (2024): Program synthesis of provable recursive functions, Technische Universität Wien Research Focus: Eva specializes in formal methods, program synthesis, and recursive programming. Her work bridges theoretical computer science with practical systems engineering, particularly in automated reasoning and software verification. Recent Publications: Her research explores the synthesis of recursive programs using saturation techniques and the development of provable recursive functions. These contributions align with advancements in automated deduction and formal verification.

Ernest TenienteView profile

Professor

• Software Engineering
• Database Systems
• Conceptual Modeling
• +4 more

Ernest Teniente is a full professor at the Universitat Politècnica de Catalunya — BarcelonaTech and director of the inLab FIB . He specializes in software engineering, databases, and IoT systems, with a focus on conceptual modeling, data integration, and automated reasoning. His research spans 20 years, yielding over 60 peer-reviewed publications and leading roles in national/international projects like SUDOQU and DAGIA. He has supervised numerous students across BSc, MSc, and PhD levels, contributing to projects such as an AI-based police patrol tool and semantic IoT infrastructure monitoring. Teaching experience includes undergraduate/postgraduate courses on software analysis, requirements engineering, and advanced databases. He has collaborated with institutions like Mossos d’Esquadra and Barcelona City Council on projects like the Artificial Intelligence-assisted police patrol manager and LinDaFIX for social welfare data analysis. His work bridges academia and industry, emphasizing practical applications in transportation optimization (SORT project) and cybersecurity. Research Highlights : Conceptual modeling and automated reasoning for database schemas IoT semantic integration and critical infrastructure monitoring Artifact-centric business process modeling in UML Projects : SUDOQU (data quality via ontologies) DAGIA (threat detection in ICT infrastructures) REMEDiAL (ontology-based software development) He regularly serves on program committees for top conferences and has coordinated projects funded by Spain’s Ministry of Science. His labs and teams, notably inLab FIB, drive innovation in AI applications, DevOps benchmarking, and IoT ecosystems.