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Jan PeleskaView profile

Professor

• Formal Methods
• Dependable Systems
• Distributed Systems
• +8 more

Jan Peleska is a Professor at the Department of Computer Science, Faculty of Mathematics and Computer Science, University of Bremen. He is a member of the Bremen Institute of Safe Systems (BISS) and co-editor of the BISS Monographs series. His research focuses on the application of formal methods and model-based testing to safety-critical embedded systems in domains such as avionics, railways, and automotive engineering. Affiliation: University of Bremen, TZI (Center for Computing Technology), BISS (Bremen Institute of Safe Systems) Academic Role: Professor of Computer Science Research Interests Peleska’s work emphasizes formal methods for dependable systems, particularly distributed and reactive real-time systems. Key areas include: Formal methods (safety, reliability, availability, security) Development of fault-tolerant systems Test automation for reactive systems Tools development for formal methods Integration with software development standards His research is applied to industrial projects involving safety-critical embedded systems, such as avionic systems and railway control systems. A comprehensive overview is provided in his Habilitation Thesis: Formal Methods and the Development of Dependable Systems . Publication Trends Peleska’s recent publications (2012–2022) focus on model-based testing (e.g., symbolic finite state machines, CSP refinement), standardisation of autonomous train control, and tools for automated testing. His work addresses challenges in railway interlocking systems, avionic software verification, and hybrid system validation, often combining formal methods with practical industrial applications. Scientific Awards Best Paper Award at FORMS/FORMAT 2014 Best Paper Award at QA+Test 2007 Other Responsibilities Peleska co-manages the Post Graduate Programme Embedded Systems GESy and serves as a shareholder/consultant for Verified Systems International GmbH. He has delivered invited lectures on industrial verification, model-based testing, and formal methods at institutions like the University of Tunghai (2016) and workshops including CyPhyAssure Spring School (2019).

Stephen SiegelView profile

Associate Professor

• Formal methods for software verification
• Verification of parallel and scientific software
• Concurrency in software systems
• +3 more

Stephen Siegel is an Associate Professor at the University of Delaware with a joint appointment in the Department of Computer and Information Sciences and the Department of Mathematical Sciences . Holding a PhD in Mathematics from the University of Chicago (1993), he transitioned from finite group theory research to formal methods in computer science, focusing on verification of parallel and scientific software. His research centers on the Verified Software Laboratory (VSL) and the CIVL Model Checker for HPC program verification. Recent work includes formal verification of PETSc components at CAV 2025 and collective contract frameworks for message-passing programs. Research Interests Formal methods for software verification Parallel and HPC software reliability Model checking techniques Application of mathematical logic to computing Academic Service Highlights Program Committee & Publication Chair, CAV 2025 Co-organizer, International Workshop on Verification of Scientific Software (VSS 2025) Chair, VerifyThis competition (2023) Editorial service at IEEE Transactions on Software Engineering (2015-2019) Teaching Portfolio CISC 404/604: Logic in Computer Science CISC 414/614: Formal Methods in Software Engineering CISC 372: Parallel Computing (MPI/OpenMP/CUDA instruction) Advanced Topics courses: Model Checking, Abstract Interpretation

Nathanaël FijalkowView profile

Researcher

• Games
• Machine Learning
• Automata Theory
• +9 more

Nathanaël Fijalkow is a Researcher at CNRS in LaBRI (Bordeaux) and a Research Fellow at The Alan Turing Institute in London. His primary research fields include games , machine learning , automata theory , and dynamical systems , with a focus on synthesizing programs from logical specifications and probabilistic models. Research Interests span program synthesis (programming by example), controller synthesis (temporal logic specifications), games on graphs (parity/mean payoff games), probabilistic automata (bounded ambiguity), and invariants for linear dynamical systems. He bridges formal methods with machine learning through projects like DeepSynth . Scientific Contributions include: Undecidability results for probabilistic automata Advances in parity game algorithms (quasi-polynomial lower bounds) Foundations of probabilistic modal logics Efficient synthesis techniques using SMT solvers and distributional learning Supervision involves guiding postdocs and PhD students such as Guillaume Lagarde, Antonio Casares, and Pierre Ohlmann. He has secured grants like the Momentum DeepSynth project (2019-2021) , aiming to merge formal methods with ML for program synthesis.

• Computer Architecture
• Programming Models
• Parallel Computing
• +4 more

Daniel Jimenez Gonzalez is a faculty member at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture within the School of Informatics (FIB). He is an active researcher in programming models and high-performance computing, contributing extensively to the field through publications, projects, and academic supervision. Research Interests: His work focuses on Computer Architecture , Programming Models , and Parallel Computing . He investigates task-based programming, runtime systems, compiler optimizations, and performance modeling for multi-core and heterogeneous architectures. His research addresses challenges in scalability, energy efficiency, and resilience in modern computing environments. His recent publications show a consistent trend in task-based programming models , runtime scheduling , and performance optimization across diverse architectures, including NUMA and GPU-accelerated systems. The work spans from theoretical modeling to practical implementation, often targeting real-world HPC applications. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: While specific students are not listed, his involvement in doctoral theses and R&D projects suggests an active role in mentoring graduate students. He has participated in both competitive and non-competitive R&D+i projects, indicating grant acquisition and project leadership experience in areas related to programming models and computer architecture. Labs and Teams: He is a member of the UPC PM - Programming Models research group, which focuses on the design, analysis, and optimization of modern programming paradigms for high-performance systems.

David GazzeView profile

Assistant Clinical Professor

• Psychopharmacology
• Schizophrenia Research
• Bipolar Disorder Research
• +4 more

David Gazze is a Clinical Assistant Professor in the Department of Pharmaceutical Sciences at the Barry and Judy Silverman College of Pharmacy, Nova Southeastern University. He has served as faculty since the institution's inception (originally Southeastern College of Pharmacy) and taught every pharmacy graduating class at the Fort Lauderdale/Davie campus, with contact details including email dgazze@nova.edu and phone (954) 262-1356. Education Ph.D. in Medicinal Chemistry, University of Pittsburgh, 1987 Research Interests His primary research focuses on psychopharmacology , specifically elucidating mechanisms of action for schizophrenia and bipolar disorder treatments. Concurrently, he applies molecular graphics in drug development to visualize molecular interactions and optimize pharmaceutical agents. These interests bridge medicinal chemistry foundations with clinical mental health applications, emphasizing computational approaches to neuropharmacological challenges. Scientific Awards Teacher of the Year (awarded 10 times by students) Advising and Grants Dr. Gazze has directly educated all pharmacy students throughout the college's history since joining at inception, reflecting deep institutional commitment. While the text confirms his research activities in psychopharmacology and molecular graphics-based drug design, it contains no details regarding graduate student advisees, grant funding, or sponsored research projects beyond his instructional and scholarly contributions.

J. David RielView profile

Professor

• Educational Technology
• Active Learning Methodologies
• Digital Transformation
• +3 more

J. David Riel serves as a Professor at Carnegie Mellon University's Heinz College of Information Systems and Public Policy, appointed Distinguished Service Professor in 2018 after joining CMU in 2006. He concurrently holds a teaching appointment with the Institute of Software Research in the School of Computer Science for the eBusiness Technology Master’s Program. His research spans: Educational Technology: Application of Web 2.0, LMS, synchronous platforms, automation, and AI/ML in education Active Learning Methodologies: Learning by doing, blended learning, flipped classrooms, and team-based learning Digital Transformation: IoT, ePayment, Intelligent Automation, Blockchain, and Quantum Computing in academic/business disruption Recent publications analyze Intelligent Automation's business-academia bridge, online flipped learning efficacy, and educational psychology research productivity. His work consistently examines technology-pedagogy integration to address digital disruption across education and business sectors.

• Software Performance Engineering
• Microservice Architectures
• Cyber-Physical Systems
• +3 more

Catia Trubiani is a faculty member at the Gran Sasso Science Institute in L'Aquila, Italy, specializing in software performance engineering, architectural analysis, and cyber-physical systems. Her work bridges theoretical modeling with practical applications, focusing on performance antipatterns, uncertainty quantification, and DevOps practices. In research , she explores performance modeling of microservices, federated learning systems, and cyber-physical systems, with a strong emphasis on architectural decision-making under uncertainty. Her recent articles analyze performance regression testing, aging detection in networks, and anti-pattern correlation in distributed systems, reflecting her interest in robust, scalable software solutions. She collaborates extensively with researchers like Raffaela Mirandola , Alberto Avritzer , and Riccardo Pinciroli , contributing to tools and frameworks such as PLUS (Performance Learning for Uncertainty of Software) and VisArch (Visualisation of Performance-Based Architectural Refactorings). Her work has been published in journals including IEEE Transactions on Software Engineering and Future Generation Computer Systems , as well as conferences like ICSE, ECSA, and ICPE.

• Computer Science
• Information Security
• Cloud Computing
• +6 more

Radu Sion is a Professor at the Department of Computer Science, Stony Brook University, specializing in Computer Science , Information Security , Cloud Computing , Data Privacy , and Cryptography . His research focuses on secure data outsourcing, trusted hardware applications, and privacy-preserving systems. Recent work includes Wink: Deniable Secure Messaging (2023) and A Study of China's Censorship Evasion (2023), both exploring plausibly deniable communication. Earlier contributions like PEARL (2021) and ConcurDB (2014) address secure storage and database integrity. His 2024 paper INVISILINE introduces invisible plausibly deniable storage solutions. His research spans Oblivious RAM , History-Independent Data Structures , Trusted Execution Environments , and Flash Memory Security . Key collaboration networks include Bogdan Carbunar, Anrin Chakraborti, and Chen Chen.

Adrian SpătaruView profile

Lecturer

• Cloud Computing
• Distributed Systems
• Edge Computing
• +4 more

Adrian Spătaru serves as a Lecturer at the Faculty of Mathematics and Computer Science, West University of Timisoara, Romania, with his office located in room 058. He maintains active academic engagement through direct contact channels including email (adrian.spataru@e-uvt.ro) and phone ((0256) 592 157), reflecting ongoing institutional affiliation and research activities within computer science. His research centers on the integration of edge, cloud, and high-performance computing resources within the cloud continuum framework. Key focus areas include service orchestration, resource management, blockchain applications for decentralized systems, and AI-driven optimization of cloud infrastructures. His work addresses critical challenges in heterogeneous platform integration, fault tolerance, and predictive maintenance across large-scale distributed environments, with notable contributions to container deployment and accelerator-aware application specification. Analysis of his publication trends reveals sustained emphasis on the edge-cloud-HPC continuum since 2018, evolving toward intent-based AI orchestration and heterogeneous hardware integration in recent works. His research bridges theoretical distributed systems concepts with practical applications in environmental monitoring (solar forecasting, freshwater quality assessment) and industrial cloud reliability, demonstrating both academic rigor and real-world impact. No scientific awards are documented in the provided institutional information. Details regarding student supervision, research grants, or laboratory affiliations are not specified in the available materials. Current research directions appear focused on advancing the edge-cloud-HPC continuum through heterogeneous platform integration, with 2025 publications indicating active development in this domain.

Enes AyanView profile

Lecturer

• Artificial Intelligence
• Deep Learning
• Medical Image Analysis
• +3 more

Enes Ayan serves as a Doctor Lecturer in the Department of Computer Engineering at Kirikkale University's Faculty of Engineering and Natural Sciences, where he has maintained continuous academic affiliation since his 2014 appointment as Research Assistant. His career trajectory includes completing both master's (2015) and doctoral degrees (2019) in Computer Engineering at the same institution following his 2013 bachelor's graduation from Süleyman Demirel University. Education Bachelor's: Computer Engineering, Süleyman Demirel University (Isparta), 2013 Master's: Computer Engineering, Kirikkale University, 2015 Doctorate: Computer Engineering, Kirikkale University, 2019 Research Focus Dr. Ayan's work centers on deep learning applications across three primary domains: medical imaging (specializing in dental diagnostics, radiology, and endoscopy), security systems (weapon detection and traffic monitoring), and agricultural technology (crop pest classification). His research bridges theoretical AI advancements with practical healthcare solutions, particularly through explainable AI frameworks for dental caries detection and pneumonia diagnosis. Publication Trends Analysis of his 15 most recent publications (2020-2025) reveals intensifying specialization in dental AI applications (60% of 2024-2025 output), with significant contributions to caries detection under prostheses and tooth numbering systems. Concurrently, his work maintains strong threads in security-focused computer vision (UAV-based traffic analysis, weapon detection) and agricultural AI, demonstrating methodological versatility through genetic algorithm optimizations and ensemble CNN architectures. Professional Context No information regarding student supervision, research grants, laboratory facilities, or scientific awards appears in the source materials. His academic progression from Research Assistant to Doctor Lecturer indicates standard career advancement within Kirikkale University's engineering faculty without notable interruptions.

• Artificial Intelligence
• Natural Language Processing
• Legal Informatics
• +5 more

Tomasz Pełech-Pilichowski serves as a Lecturer at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków. He concurrently holds dual administrative leadership positions as Director of the AGH Recruitment Center and Rector's Representative for Recruitment, demonstrating significant institutional impact beyond his academic role. His research expertise spans artificial intelligence, natural language processing, and legal informatics with methodological foundations in deep learning and time series analysis. Recent work focuses on AI-driven solutions for legal text processing (text segmentation, hypertext law), educational technology (gamification, recruitment systems), and security applications (facial-age detection, anomaly identification). His interdisciplinary approach consistently bridges computer science with law, education, and environmental science through practical implementations. Analysis of his 2023-2025 publications reveals three dominant research trajectories: legal tech innovation (68% of output featuring text segmentation and regulatory automation), educational transformation (22% including gamified AI skill development), and security/environmental systems (10% covering IoT integration and pollution prediction). This progression shows increasing specialization in AI-NLP fusion techniques applied to domain-specific challenges, particularly within legal informatics where he has developed novel text recovery and visualization frameworks.

• Automata Theory
• Formal Verification
• Logic in Computer Science
• +3 more

Christof Löding , currently an Adjunct Professor at the Lehrstuhl für Logik und Theorie diskreter Systeme (Informatik 7) department of RWTH Aachen University , is a leading researcher in Automata Theory , Formal Verification , and Logic in Computer Science . His work bridges theoretical foundations with practical applications in software verification, automata minimization, and game theory. Research Interests include automata theory, formal verification, logic, tree automata, game theory, and computational models. Publications span topics like Finite-valued Streaming String Transducers , Deterministic Parity Automata , and Stochastic Game Strategies . Collaborations with researchers like Emmanuel Filiot , Sarah Winter , and León Bohn highlight his contributions to automata and verification. Email : loeding@informatik.rwth-aachen.de He has actively published in venues such as ICALP , LICS , and STACS , focusing on deterministic automata, transducers, and logic-based computational systems. His work on Hyperlogic for Strategies in Stochastic Games (2025) and Minimal History-Deterministic Automata (2025) showcases his ongoing influence in formal methods and automata theory.

Shigetoshi EdaView profile

Professor

• Infectious Disease Diagnostics
• Biosensors and Electrochemical Detection
• Veterinary Pathology
• +3 more

Shigetoshi Eda serves as Professor in the Department of Forestry, Wildlife & Fisheries at the University of Tennessee, Knoxville, with concurrent appointments as Co-Chair of the UT Chronic Wasting Disease Working Group, Associate Director of the Center for Wildlife Health, Adjunct Associate Professor in Microbiology, and Affiliate Faculty at the National Institute for Mathematical & Biological Synthesis. His educational background includes a Ph.D. from Tokyo University of Pharmacy and Life Science and postdoctoral research at the University of California, Riverside. He joined the University of Tennessee faculty in 2003 after completing his postdoctoral training. Dr. Eda's research program pioneers rapid diagnostic platforms for animal infectious diseases, specializing in chronic wasting disease and Johne's disease diagnostics through electrochemical biosensors and AC electrokinetic capacitance sensing. His work bridges veterinary medicine, electrical engineering, and computational biology to develop field-deployable tools that improve sensitivity, specificity, and cost-efficiency over conventional methods like ELISA and PCR. Current projects include mathematical modeling of Pseudomonas aeruginosa biofilms and IoT-based mastitis detection systems. His publication record (79 papers as of 2022) reveals a strong trajectory toward point-of-care biosensors for animal health, with recent work emphasizing capacitive immunoassays, electrochemical antibody detection, and nucleic acid analysis. These studies consistently address critical gaps in on-site disease surveillance across veterinary diagnostics, food safety, and wildlife health applications. Scientific recognition includes three patents for a Johne's disease diagnostic test licensed to a veterinary diagnostic company and commercialized in February 2015. He has secured multiple extramural grants and contracts to advance his diagnostic platform development. Dr. Eda actively mentors graduate researchers, including Ph.D. graduate Ashutosh Wadhwa (now CDC postdoc) and numerous student co-authors on publications. His laboratory maintains strategic partnerships with electrical engineering departments and veterinary diagnostic facilities to accelerate technology translation. Current grant funding supports the development of ACEK-based capacitance sensing devices for infectious disease detection in agricultural settings. The Center for Wildlife Health provides his primary research infrastructure, facilitating collaborations on wildlife disease diagnostics and serving as the operational base for the UT Chronic Wasting Disease Working Group he co-chairs.

• Physical Chemistry
• Analytical Chemistry
• Materials Science
• +6 more

Jonathan Whitmer is a Concurrent Associate Professor at the University of Notre Dame, with appointments in the Department of Chemistry & Biochemistry and Chemical & Biomolecular Engineering. His research spans computational chemistry, materials science, and machine learning applications in physical systems. Education: Ph.D. in Physics (2011), University of Illinois; B.S. in Physics and Mathematics (2005), Kansas State University Whitmer's work focuses on free energy calculations , ionic liquids , and liquid crystal dynamics , with recent studies leveraging machine learning for material discovery. His publications highlight interdisciplinary approaches combining advanced sampling methods , nanomaterials , and GPU-accelerated simulations . Scientific Awards: 2018 NSF CAREER Award 2018 Emerging Investigator in Materials Science, Materials Research Express Whitmer's collaborative projects include host-guest systems , supramolecular hydrogels , and polymer-surface interactions , supported by software development contributions like PySAGES and SSAGES.

Stefana ParaschoView profile

Assistant Professor

• Digital Fabrication
• Robotic Construction
• Sustainable Architecture
• +3 more

Stefana Parascho serves as Tenure Track Assistant Professor at the Swiss Federal Institute of Technology in Lausanne (EPFL) within the School of Architecture, Civil and Environmental Engineering (ENAC), specifically in the Institute of Architecture (IA). She leads the Laboratory for Creative Computation (CRCL) and concurrently heads the Diversity Office at ENAC, demonstrating dual commitments to technological innovation and institutional equity. Her research pioneers intersections of digital fabrication, robotics, and sustainable architecture, with particular focus on transforming construction waste into valuable resources. Through computational design and robotic assembly, she develops novel methodologies for upcycling concrete rubble and timber into structurally sound building components, directly addressing circular economy challenges in construction. Her work bridges theoretical frameworks with physical prototyping, emphasizing human-robot collaboration and material reintegration. Analysis of her recent publications reveals a cohesive trajectory toward waste valorization through digital processes, with concrete rubble masonry and timber reuse forming the core technical pillars. These investigations consistently integrate robotic fabrication, structural validation, and circular design principles across 15+ publications since 2023, establishing new paradigms for resource-efficient construction. As an academic advisor, she supervises four PhD candidates (Grangeot Maxence, Skevaki Eleni Maria, Vallat Gabriel Rémi, Wang Jingwen) while contributing to architectural education through courses like "Digital design and making: A critical introduction" that merge technical skill development with theoretical critique. Her leadership extends to the ENAC Teaching Committee and institutional diversity initiatives, reflecting comprehensive engagement with academic community development. Her operational base at CRCL (https://crcl.epfl.ch) provides the technical infrastructure for robotic experimentation, while her Diversity Office role (https://www.epfl.ch/schools/enac/about/diversity-office/) demonstrates parallel commitment to inclusive academic environments. This dual focus positions her at the forefront of both technological innovation and cultural transformation within architectural academia.