François Trahay is an Associate Professor at Telecom SudParis, affiliated with the SAMOVAR research laboratory. His research focuses on high-performance computing systems, storage optimization, and performance analysis tools for parallel and distributed environments. He completed his PhD at Université Bordeaux I (2009) and Habilitation (HDR) at Institut Polytechnique de Paris (2021). Research Interests: Trahay specializes in optimizing storage systems (SSDs, RAID configurations), developing performance analysis frameworks (e.g., EZTrace, NumaMMA), and enhancing energy efficiency in HPC. Key areas include I/O performance, parallel runtime systems, and adaptive computing for machine learning workloads. Publication Trends: His recent work (2018–2025) demonstrates strong focus on: (1) SSD/RAID management techniques for modern storage hardware, (2) HPC performance tools for tracing and analysis, and (3) optimization strategies for distributed deep learning systems. Laboratory Affiliation: Member of SAMOVAR Laboratory (UMR CNRS), conducting research in distributed systems, networks, and computational efficiency.
Bestoun S. Ahmed Al-Beywanee is a Professor in AI and Software Engineering at the Department of Mathematics and Computer Science, Karlstad University, Sweden. He joined the university as a Senior Lecturer in 2019, was promoted to Associate Professor in 2020, and to Professor in 2023. His roles include teaching advanced courses such as AI Engineering, Automated Software Engineering, and Software Testing Fundamentals. His research focuses on software quality assurance, trustworthy AI systems, and MLOps, with a strong emphasis on combinatorial testing, IoT systems, and applied optimization techniques. Education: BSc (Electrical and Electronic Engineering, University of Salahaddin-Erbil, 2004); MSc (University Putra Malaysia, 2009); PhD (Software Engineering, University Sains Malaysia, 2012). Postdoctoral research at the Swiss AI Lab IDSIA (2015) and positions at Salahaddin University and Czech Technical University further enriched his expertise. Research interests span Quality Assurance of machine learning systems, software testing methodologies, trustworthy AI, IoT system reliability, and optimization algorithms. He has pioneered frameworks like PatrIoT for IoT testing and contributed to MLOps robustness. His work integrates machine learning with anomaly detection, adaptive systems, and industrial applications. Recent articles highlight advancements in data-driven heat pump management, MLOps robustness, and edge-cloud AR/VR optimization. Collaborations include projects on digital twins, smart manufacturing, and industrial IoT. His contributions bridge theoretical research with practical industrial solutions, emphasizing system reliability and AI ethics.
David Palma is an Associate Professor at the Department of Information Security and Communication Technology , Faculty of Information Technology and Electrical Engineering , Norwegian University of Science and Technology (NTNU). His research focuses on next-generation networking paradigms, including intent-based networking , knowledge-driven management , and IoT device automation . Key research interests include: Human-centric Internet of Things (IoT) Ontology-based network management Cloud/Edge/Fog computing for IoT Arctic and satellite communication 5G integration in smart grids His recent publications (2024-2019) highlight trends in knowledge graphs for network compliance, XR applications in critical sectors, UAV-based emergency networks , and 5G-enabled smart grid protection . Articles also explore Arctic connectivity via satellite swarms and energy-efficient IoT management.
Maurizio Leotta is an Assistant Professor in Computer Science at the University of Genova, Italy, where he has been employed since 2018. He is a member of the Department of Computer Science, Bioengineering, Robotics, and Systems Engineering (DIBRIS) within the School of Mathematical, Physical and Natural Sciences. Additionally, he serves on the School Council and the Department Board of DIBRIS. Dr. Leotta received his PhD in Computer Science from the University of Genova in 2015, with a thesis on Automated Web Testing under the supervision of Prof. Filippo Ricca. His doctoral work was revised by Prof. Massimiliano di Penta (Università del Sannio, Italy) and Prof. Ali Mesbah (University of British Columbia, Canada). Before his academic career, he worked as an IT Technician in various companies and participated in research and industrial projects funded by organizations such as Finmeccanica S.p.A. and the Italian Space Agency. Dr. Leotta's primary research focuses on Software Engineering, with particular emphasis on Test Automation, which is his main research topic. He collaborates with Prof. Paolo Tonella from USI, Switzerland on this area. His other significant research interests include Empirical Software Engineering, Requirements Engineering, Business Process Modelling, and Model-Driven Software Engineering. His work often addresses practical challenges in web and mobile application testing, with a growing interest in applying AI and gamification techniques to improve software testing processes. His recent publications demonstrate a strong trend toward integrating artificial intelligence with traditional software testing methodologies, particularly in end-to-end web testing. He has made significant contributions to improving test robustness, addressing flakiness in test execution, and developing tools for better test maintenance. His work also shows increasing interest in gamification approaches to engage developers and students in software testing activities, as well as applications of large language models to enhance test automation. Dr. Leotta has received multiple prestigious awards for his research, including: Best Paper Award at ICST 2025 (Short Papers, Vision and Emerging Results) Distinguished Paper Award at ICST 2023 (Industry Papers) Best Paper Award at QUATIC 2022 (Full Papers) Best Paper Award at ICST 2022 (Demo and Testing Tool Papers) Best Paper Award at QUATIC 2020 (Full Papers) Best Student Paper Award at ICWE 2016 (Full Papers) Dr. Leotta has advised numerous graduate students, including three PhD candidates who have completed their degrees (Andrea Fasciglione in 2024, Dario Olianas in 2023, and Diego Clerissi in 2020). He currently supervises multiple Master's students working on topics related to software testing, web accessibility, and AI applications in software engineering. He has also served as a postdoctoral advisor for researchers including Diego Clerissi and Dario Olianas. Beyond advising, Dr. Leotta has secured research funding through collaborations with industry partners and has been involved in multiple research projects focused on software testing and verification. He co-directs the Software Engineering for Healthcare (SEH) Laboratory, which has been partially supported by Janssen Italia (previously by Actelion Pharmaceuticals Italia). The lab focuses on applying software engineering techniques to healthcare applications, particularly in the areas of wearable technology for patient monitoring and medical data analysis. Dr. Leotta is also active in the Gamify research community, organizing workshops on gamification in software development, verification, and validation.
Kihong Heo is an Associate Professor at the School of Computing and Graduate School of Information Security, KAIST, Republic of Korea. He leads the Programming Systems Laboratory and has held academic positions since 2017, including Assistant Professor (2017-2020) and Associate Professor (2020-2024). His research focuses on developing program reasoning systems for safe and reliable software, with key contributions in AI-based program analysis, program simplification, and scalable synthesis systems. His educational background includes a Ph.D. and B.S. in Computer Science & Engineering from Seoul National University (2009 and 2005 respectively). He has served as a post-doctoral researcher at the University of Pennsylvania (2009-2017) before transitioning to KAIST. Research interests span AI-driven program analysis for deep semantic bug detection, program debloating systems for security optimization, and synthesis frameworks using probabilistic models. His work bridges undecidability in static analysis with external information integration. Recent publications analyze logic-based verification for mobile agents, compiler fuzzing , and data dependency guided fuzzing . Trends show a focus on security-critical systems, reinforcement learning for code reduction, and probabilistic models. Scientific awards include the ACM SIGSOFT Distinguished Paper Award (FSE 2025) , Amazon Research Award (2024) , and multiple KAIST teaching honors . He has also received ACM SIGPLAN Distinguished Paper (PLDI 2019) and Best Artifact Awards. He has mentored numerous Ph.D. and Master’s students and contributes to program committees for leading conferences like SOAP (PC Co-Chair) , ICSE , and SAS . His work is supported by grants and collaborations with institutions including Facebook and Seoul National University.
Lars-Henrik Eriksson is a Senior Lecturer in the Department of Computer Science at Uppsala University, part of the Department of Information Technology. He holds a PhD and is recognized as an Excellent Teacher and educational mentor. He currently serves as the program director for the Master's program in Computer Science and has previously held leadership roles, including Head of the Department of Computer Science from 2004 to 2018. PhD in Computer Science Excellent Teacher Award Pedagogical Mentor at Uppsala University His research focuses on the applications of logic in computer science, particularly formal methods for software development. His work spans formal specification, verification, and synthesis, with strong emphasis on logic programming, interactive theorem proving, and logical frameworks. He has made significant contributions to the use of formal methods in safety-critical domains such as railway signaling. His current research includes modeling application domains within formal methods and formalizing concurrency theory using the Isabelle proof assistant. The recent publications reflect a sustained focus on modal logics for nominal transition systems, formal verification tools (e.g., GTO), and domain-specific applications of formal methods. These works demonstrate deep integration of theoretical logic and practical software engineering, especially in distributed and safety-critical systems. The recurring themes include concurrency, verification, and the use of domain models to enhance formal reasoning. Scientific Awards and Recognitions: Excellent Teacher Pedagogical Mentor Lars-Henrik Eriksson has advised numerous students through project supervision, thesis reviews, and course mentorship, though no formal list of advisees is provided. He has been involved in significant research management, including leading the department and directing a master’s program. He has also collaborated with industry, particularly in railway signaling, contributing to safety analysis and formal verification projects with Trafikverket and through companies he co-founded. He is a board member of Formal Methods Europe and served as program committee chair for the FME Symposium 2002 (part of FLoC’02). His work bridges academia and industry, especially in the application of formal methods to real-world engineering challenges.
Chris Hartley, M.D. is a Physician Scientist at Mayo Clinic's Department of Laboratory Medicine and Pathology, specializing in gastrointestinal and liver pathology, cytopathology, and pancreatobiliary cytology. He completed his MD at Wake Forest University School of Medicine (2012) and fellowships at Washington University School of Medicine (2018) and University of Wisconsin Hospital (2017). 2018 Fellow - Liver and Gastrointestinal Pathology 2017 Fellow - Cytopathology 2016 Resident - Anatomic & Clinical Pathology Hartley's research integrates artificial intelligence with cytopathology and histopathology , focusing on improving diagnostic accuracy for pancreatic ductal adenocarcinoma, colonic graft-versus-host disease, and hepatocellular carcinoma. His work explores AI-driven tools for bile duct brushing evaluation and spatially resolved iron quantification in liver samples. Recent publications highlight his leadership in digital pathology and AI applications across gastrointestinal, hepatic, and pulmonary diseases. Key trends include: AI for histologic differentiation in cancers Cytomorphologic studies of rare neoplasms Molecular marker analysis in transplant-related pathologies Scientific recognitions include: 2019 'Good Catch' Patient Safety Award 2017 Young Investigator Award - Cancer Cytopathology 2015 USCAP Abstract Award Runner-up As a member of the Rodger C. Haggitt Gastrointestinal Pathology Society and American Society for Clinical Pathology, Hartley contributes to precision medicine initiatives and multidisciplinary cancer care teams.
João Pedro Machado Vitorino is a part-time lecturer and researcher at the Polytechnic Institute of Porto's School of Engineering, affiliated with GECAD. He is pursuing a Ph.D. in Informatics Engineering (Artificial Intelligence) at the University of Porto and holds an MSc in Artificial Intelligence Engineering. Education : Ph.D. (in progress), MSc, and BSc in Informatics/Artificial Intelligence Engineering Research : Focuses on machine learning robustness, explainability, and adversarial attack simulation for cybersecurity applications Projects : Involved in 7 EU/National R&D initiatives (2021-2025), including BEHAVIOR (2024-2025) and CYDERCO (2023-2025) His recent publications (2023-2025) span cybersecurity datasets , adversarial learning , malware detection , LLM security , and energy-efficient AI . He co-organized the 36th European Simulation & Modelling Conference (2022) and peer-reviewed for Pattern Recognition and Computers & Security . Awards : IEEE Outstanding MSc Thesis (2023), Engineers Association Innovation Award (2024), multiple merit certificates Skills : Machine Learning, AI Security, Network Analysis, and 3 professional certifications (Cisco, Microsoft, Airbus)
Sandro Bartolini serves as Associate Professor in the Department of Information Engineering and Mathematical Sciences at the University of Siena, Italy, where he teaches advanced courses in computer architecture and parallel programming while leading cutting-edge research in high-performance computing systems. His academic journey began with a cum laude Laurea in Computer Engineering followed by a PhD in Computer Science and Engineering from Università di Pisa. Education: PhD in Computer Science and Engineering, Università di Pisa Laurea in Computer Engineering (cum laude), Università di Pisa Research Focus: His work centers on photonic interconnects for chip multiprocessors , energy-efficient software optimization for multi-core/GPU architectures, and performance-portable parallel programming models . Current investigations span cryptographic acceleration, blockchain algorithms, and hardware/software co-design for emerging computing paradigms, with strong emphasis on practical implementations bridging theoretical advances and real-world applications. Publication Trends: Recent publications (2019-2023) reveal three dominant threads: (1) Photonic network innovations addressing energy bottlenecks in chip multiprocessors, (2) The PHAST library ecosystem enabling seamless CPU/GPU programming across domains from autonomous vehicles to UAV navigation, and (3) Hardware accelerator designs for convolutional networks and cryptographic workloads. These works consistently target performance-portability challenges in heterogeneous computing environments. Grants and Collaborations: As principal investigator for the Italian Ministry-funded PHOTONICA project, he established international research partnerships with Murcia University, Columbia University, and Hong Kong University of Science and Technology, while securing industry collaborations with STMicroelectronics, Intel Munich, IBM, and IMEC. He has also managed complex IT system deployments for Siemens Italy, RAI (Italian public broadcasting), and SpaceDys. Academic Leadership: Bartolini serves as Associate Editor for the Eurasip Journal of Embedded Computing and actively contributes to the European HiPEAC network. His research group at Siena maintains strong industry ties for technology transfer, particularly in photonic interconnect validation and parallel programming frameworks for next-generation computing systems.
Dr. Xiaoyan Hong is an Associate Professor in the Department of Computer Science at The University of Alabama's College of Engineering. Her research focuses on mobile/wireless networks, vehicular networks, and delay-tolerant systems. Ph.D., Computer Science, University of California-Los Angeles (2003) M.S., Computer Science, Zhejiang University (2000) Research spans Internet of Things (IoT) , Connected Vehicles , and Underwater Wireless Networks . Key projects include NSF-funded underwater robot communication infrastructure and smart traffic light systems. Recent work explores Named Data Networking (NDN) in vehicular environments, Task Synchronization for autonomous vehicles, and V2I Communication for traffic optimization. NSF Research Experience for Undergraduates (REU) grant recipient $1.5M NSF grant for underwater robotics networking Her research integrates with multiple engineering centers, including the Center for Advanced Vehicle Technologies and Center for Transportation Operations .
Johannes Geier is a Researcher at the Chair of Design Automation at the Technical University of Munich (TUM). His work focuses on electronic design automation, fault injection simulations, and security countermeasures for RISC-V processors. University: Technical University of Munich Department: Chair of Design Automation Email: johannes.geier@tum.de Research Interests Electronic Design Automation (EDA) for analog and digital circuits Fault tolerance and reliability in RISC-V architectures Security analysis of post-quantum cryptographic systems Timing analysis and microfabrication techniques Optical Networks-on-Chip (NoC) and emerging technologies Compiler-assisted hardware security implementations Recent Research Trends Specializes in fault injection methodologies for hardware security validation Develops open-source tools like vRTLmod for RTL simulation acceleration Explores RISC-V vector extensions for post-quantum cryptography Investigates differential fault effect equivalence checks for efficiency Designs compiler-based security countermeasures against instruction skip attacks Works on concurrent multi-node XCP proxy server architectures
Stephanie Weirich is the ENIAC President's Distinguished Professor in the Department of Computer and Information Science at the University of Pennsylvania's School of Engineering and Applied Science. Her research focuses on programming languages, with emphasis on dependent types, formal verification, and functional programming semantics. She leads Penn's Programming Languages Group (PLClub) and teaches courses including Advanced Programming (CIS 5520) and Programming Languages and Techniques (CIS 120). Research Areas: Her work spans theoretical foundations and practical implementations, including type systems for security, mechanized program verification, cost analysis for lazy evaluation, and language-based techniques for probabilistic programming. Recent projects explore indistinguishability in dependent types and effects systems for resource-aware computation. Honors: SIGPLAN Robin Milner Young Researcher Award (2016) NSF CAREER Award (2004) Microsoft Outstanding Collaborator (2016) Most Influential Paper Award, ICFP (2016) DARPA Computer Science Study Panel (2007-2008) Advising: Mentored 15+ PhD graduates including Richard Eisenberg (2016 Reynolds Award winner) and Vilhelm Sjöberg. Current students work on stratified type theory and mechanized logical relations. Secured grants from NSF and DARPA for research in dependently typed systems. Collaborations: Leads the PLClub research group; collaborates with industry (Microsoft) on Haskell extensions and verification tools like Hs-to-Coq.
Ramadan Abdunabi is a Senior Clinical Professor in the Department of Computer Information Systems at Colorado State University's College of Business, joining in 2015. He holds a Ph.D. and MCS in Computer Science from the same university. Education: Ph.D. and MCS in Computer Science (Colorado State University) Research Interests: Primary: Software engineering, computer security, access control frameworks for mobile applications Secondary: Information systems education, pedagogy, curriculum design, and technological influences on learning Key projects: Spatiotemporal access control, secure resource access in mobile environments Article Trends: His work spans access control (15+ publications), software testing (e.g., test case prioritization), and educational research (programming self-efficacy in CIS students). Recent articles focus on body area networks, safety-critical systems, and software supply chain security, reflecting his dual emphasis on cybersecurity and pedagogical innovation. Advising: Mentored graduate and undergraduate students in thesis projects, including Rejina Basnet (M.S.) and Wisdom Senolos (BSBA).
Stephan Kessler is a researcher at the Technical University of Munich , affiliated with the Department of Mechanical Engineering and the Chair of Conveying Technology, Material Handling, and Logistics . His work focuses on construction logistics, digital twins, and IoT integration in building processes. Contact: stephan.kessler@tum.de Key research areas: Digital Twin, BIM, DEM simulations, IoT in construction Collaborates with Prof. Johannes Fottner on construction automation projects His research emphasizes digitalization of construction processes through technologies like RFID, machine learning, and simulation tools. Recent publications address tower crane planning, co-robot integration, and bulk material handling standards. Article trends show consistent focus on construction automation (IoT, digital twins, BIM), material flow optimization (DEM simulations, screw conveyor standards), and equipment lifecycle management (telematics, RFID identification). Kessler contributes to industry-university collaborations through projects like BauFlott (fleet management systems) and TEP (Tower Crane Deployment Planner). His work bridges theoretical research with practical implementations in construction site logistics.
Scott Mahlke is a Professor and Associate Chair in the Department of Electrical Engineering and Computer Science at the University of Michigan's College of Engineering. He is affiliated with both the Advanced Computer Architecture Laboratory and the Software Systems Laboratory. Dr. Mahlke joined the University of Michigan in 2001 after completing his Ph.D. at the University of Illinois and working at HP Laboratories. Ph.D., University of Illinois Former Researcher, HP Laboratories Dr. Mahlke's research spans compilers, computer architecture, and high-level synthesis, with particular focus on overcoming challenges in performance, power consumption, and reliability for next-generation computer systems. His work integrates hardware and software co-design approaches to address fundamental limitations in modern computing platforms. His research has evolved from traditional compiler and architecture topics toward increasingly incorporating machine learning acceleration, autonomous systems, and reliability engineering. Analysis of his recent publications (2021-2025) reveals a strong trend toward hardware-software co-design for emerging workloads, particularly in autonomous systems, neural network acceleration, and reliability-aware computing. His work demonstrates consistent innovation in bridging compiler technology with architectural innovations to solve real-world performance and efficiency challenges. Dr. Mahlke has received significant recognition for his contributions to the field: National Science Foundation CAREER Award (2003) for "Compiler-Directed Synthesis of Application Specific Processors" Morris Wellman Faculty Development Assistant Professor appointment (2004) ISCA Most Influential Paper Award (2006) for the 1991 paper "IMPACT: An Architectural Framework for Multiple Instruction Issue Processors" Young Alumni Award from the University of Illinois ECE Department (2007) As an educator, Dr. Mahlke has taught core computer systems courses including EECS 370 (Introduction to Computer Organization), EECS 483 (Compiler Construction), and EECS 583 (Advanced Compilers) since joining Michigan. His teaching philosophy follows Yale Patt's 10 commandments for teaching, emphasizing understanding over memorization, genuine respect for students, and taking responsibility for course content. He has received mixed but generally positive student evaluations, with students noting both his deep subject matter expertise and areas for improvement in lecture delivery. Dr. Mahlke maintains active research leadership through his affiliations with the Advanced Computer Architecture Laboratory and Software Systems Laboratory, where his team continues to explore innovative approaches to compiler and architecture challenges in modern computing systems.
