Find Academic Supervisors

• Custom Hardware Design
• FPGA Acceleration
• Edge Computing
• +4 more

John McAllister is a Professor and Deputy Head of School at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science. His research focuses on custom hardware design for FPGA-based embedded/edge computing, signal processing, and machine learning applications, with a particular emphasis on neuromorphic computing, quantum computing, and dataflow architectures. He leads projects such as FPGA Acceleration of SDR Algorithms and picoStream Streaming Multiprocessors, and has supervised work in embedded systems and wearables. Research Interests: Custom FPGA Hardware and High-Level Synthesis Edge Computing and Cyber-Physical Systems Signal Processing Systems Dataflow Computing Neuromorphic Computing Quantum Computing Notable Awards: Best Paper Prize (2011, 2007) Certificate of Merit (2017) Higher Education Academy Fellowship (2007) Grants & Collaborations: R3500ECS: Arm Morello UAV Security (2023–) R8848CSC: FPGA SDR Acceleration (2017–) R3797CSC: Exascale picoStream (2016–2018) Labs/Teams: Active in the Institute of Electronics, Communications & Information Technology, leading interdisciplinary projects in quantum circuit optimization and FPGA-based signal processing.

Giles RegerView profile

Senior Lecturer

• Automated Theorem Proving
• Runtime Verification
• Formal Methods
• +3 more

Giles Reger is a Senior Lecturer in the School of Computer Science at the University of Manchester, where he leads research in the Formal Methods Group. His academic background includes a BA in Computer Science from the University of Cambridge (2009), an MSc in Advanced Computer Science from the University of Manchester (2010, Highest Achiever Award), and a PhD from Manchester (2014) on Automata-based monitoring and mining of execution traces . Research interests focus on: Theorem Proving : Core developer of the Vampire first-order ATP system, working on performance extensions and collaborative proving techniques Runtime Verification : Creator of the MarQ monitoring tool and organizer of the International Runtime Verification Competition Formal Methods : Applications in program verification, specification mining, and temporal logic Publications emphasize automated reasoning, verification tools, and temporal specification languages, with recent work exploring neural-guided theorem proving and higher-order unification. His group consistently publishes at top venues like CADE, TACAS, and RV. Awards include: Multiple division wins in SMTCOMP/CASC theorem proving competitions (2016-2020) FLoC Olympic Games medals for Vampire contributions (2018) Advises PhD students including Michael Rawson (neural-guided proving) and Joshua Dawes (runtime verification). Leads the £1.3M EPSRC-funded SCorCH project (Secure Code for Capability Hardware) with Oxford/ARM/AWS. Coordinates the COST Action on Runtime Verification Beyond Monitoring.

• Formal Methods
• Safety-Critical Systems
• Hybrid Systems
• +7 more

Zhenya Zhang is an Assistant Professor at the Intelligent Software Engineering Laboratory, Faculty of Information Science and Electrical Engineering, Kyushu University, Japan. He also serves as a Project Researcher at the National Institute of Informatics, Tokyo. His research focuses on formal methods for safety-critical complex systems , including hybrid systems (cyber-physical systems) and AI-based systems like autonomous vehicles. PhD in Informatics (2020), National Institute of Informatics/SOKENDAI Master in Computer Science (2017), Institute of Software Chinese Academy of Sciences/University of Chinese Academy of Sciences Bachelor in Software Engineering (2014), Northwestern Polytechnical University Research Interests : Quality assurance of safety-critical systems through formal methods. Specializes in verification, testing, and monitoring of hybrid systems and AI-controlled cyber-physical systems, with applications in autonomous driving validation. Key contributions include optimization-based falsification techniques and confidence measures for robustness analysis. Article Trends : Recent work emphasizes neural network verification, Monte Carlo Tree Search for falsification, and signal temporal logic monitoring. Collaborations span institutions in Japan, Singapore, and Italy, with tools like FalStar and Tumb developed for CPS testing. Scientific Awards : ACM SIGSOFT Distinguished Paper Award (ASE'24) 2nd rank in UAV Testing Competition (SBFT'24@ICSE'24) Best Paper Award nominee (EMSOFT 2018) National Scholarship, China (2011, 2012) Grants : Principal Investigator for JST BOOST (2025-2030) and multiple JSPS/Japan Society for the Promotion of Science grants. Current projects focus on neural network verification and fine-grained monitoring of temporal logic specifications. Labs & Collaborations : Works with the ERATO Metamathematics for Systems Design Project and contributes to ARCH-COMP competitions. Tools under development include FalStar-MCTS and ForeSee for hybrid system falsification.

• Formal Methods
• Model-Based Testing
• Cyber-Physical Systems
• +5 more

Paolo Arcaini is a Project Associate Professor at the National Institute of Informatics (2019–present) and previously held academic positions at Charles University (Assistant Professor, 2015–2018) and the University of Bergamo (Postdoctoral Fellow). His research spans formal methods, model-based testing, and quantum software engineering, with a focus on cyber-physical systems, autonomous vehicles, and machine learning validation. He has received multiple best paper awards, including at SSBSE (2021), AITest (2020), and Mutation (2017). Educational Background: PhD in Computer Science, University of Milan (2010–2012, advisor: Elvinia Riccobene) Postdoctoral Fellow, CNR-IDPA (2013, advisor: Gloria Bordogna) Research Interests: Dr. Arcaini's work bridges abstract state machine modeling, hybrid system falsification, and quantum program testing. His recent projects address robustness in neural networks, search-based scenario generation for autonomous systems, and quantum annealing applications to test case optimization. Article Trends: His publications demonstrate expertise in hybrid system falsification using Monte Carlo tree search mutation analysis for regular expressions and neural networks quantum software testing via combinatorial and search-based methods tool development for NuSMV/Yices integration and quantum noise mitigation multi-objective optimization for autonomous delivery systems formal methods in medical software validation Scientific Recognition: Distinguished Paper Award, SSBSE 2021 Best Paper Award, AITest 2020 Best Paper Award, Mutation 2017 Teaching: He has taught courses on Formal Methods for Cyber-Physical Systems (NII 2019) Model-Based Testing (Charles University 2015–2018) Java programming labs and advanced topics Tool Development: Dr. Arcaini has created several tools including MutRex/TearRex for regular expression testing NuSeen (Eclipse-based NuSMV environment) ATGT Boolean for SAT-based testing CRAG for combinatorial road geometry generation QUIET for quantum noise mitigation BQTmizer for quantum test case optimization

• Academic Integrity
• Research Integrity
• Academic Writing
• +2 more

Rubén Lluc Comas Forgas is a Full Professor at the University of the Balearic Islands (UIB) within the Department of Applied Pedagogy and Educational Psychology . He holds a European PhD in Science Education (2009) and has served as a visiting researcher at institutions including the University of East Anglia (UK), Liverpool John Moores University (UK), and Stockholm University (Sweden). His research focuses on academic integrity , research integrity , and educational technology , with significant contributions to understanding plagiarism, predatory journals, and AI's impact on scholarly communication. Research Leadership : Principal Investigator for EU-funded projects like CHARLIE (Bias in Big Data) and AI-UpskillED, alongside national initiatives on academic integrity. Key Publications : 15+ peer-reviewed articles (2023–2025) addressing AI-generated content, predatory publishing, and plagiarism trends. International Collaboration : Co-led studies with researchers from Spain, Portugal, Mexico, and Greece, analyzing academic misconduct across educational contexts. Teaching Portfolio : Coordinates courses on scientific documentation, systematic reviews, and academic integrity for Pedagogy, Social Education, and Sport Sciences master's programs.

Sylvio Barbon JuniorView profile

Associate Professor

• Machine Learning
• Meta-Learning
• Process Mining
• +7 more

Sylvio Barbon Junior is an Associate Professor at the Department of Engineering and Architecture, University of Trieste, Italy. He leads the Machine Learning Lab and previously held roles including Research Group Leader at the State University of Londrina (Brazil) and visiting positions at Università di Modena e Reggio Emilia and Università degli Studi di Milano (Italy). His academic journey includes a Ph.D. in Computational Physics (University of São Paulo, 2011) and multiple postdoctoral and research fellowships. Research interests span Meta-Learning, Process Mining, Stream Mining, Data Mining, and Computer Vision. He focuses on applications such as fraud detection in agrifood systems, cybersecurity in IoT networks, and real-time anomaly detection in business processes. His work integrates machine learning with spectroscopic techniques for quality assessment in agriculture and medical diagnostics. Publications highlight contributions to meta-learning frameworks for graph-based search, adaptive ensemble methods for multi-label streams, and computer vision systems for cocoa classification. Awards include Best Paper recognitions at SBSI and BRACIS conferences for innovations in process mining and anomaly detection. Award highlights include Honorable Mentions for work on fake news classification (SBSI 2019) and Best Paper awards for leveraging anomaly detection in business processes (SBSI 2018). He serves as a reviewer for journals like Elsevier Information Processing in Agriculture and as an editor for Springer’s Data Semantics series. His teaching spans postgraduate and graduate programs in Applied Data Science, Machine Learning Operations, and Computer Graphics. He advises on Ph.D. and Master’s theses focusing on AutoML, Process Mining, and Machine Learning Applications.

Arnaldo PereiraView profile

Assistant Professor

• Artificial Intelligence
• Intelligent Systems
• Semantic Data
• +3 more

Arnaldo Pereira is an Invited Assistant Professor at the Instituto Politécnico de Bragança. He holds a Ph.D. in Informatics from a collaborative program between the University of Aveiro, University of Porto, and University of Minho (MAPi), focusing on semantic data querying and visualization. His research interests include Artificial Intelligence, Intelligent Systems, and their applications in biomedical informatics and FAIR data practices. He has contributed to European research projects advancing data integration and control systems. Education: Ph.D. in Informatics (Collaborative Program: University of Aveiro, University of Porto, University of Minho) Research Interests: Dr. Pereira specializes in semantic data technologies, FAIR data principles, and their application to biomedical database systems. His work emphasizes query optimization, visualization tools for complex data, and the development of interoperable systems in healthcare and industrial contexts. Recent efforts focus on collaborative workshops (BYOD) to enhance data management practices and knowledge sharing in interdisciplinary environments. Key Research Trends (2020–2024): His publications highlight advancements in FAIR-compliant tools, semantic querying of biomedical databases, and the integration of AI-driven approaches for data accessibility and system monitoring. Earlier work includes contributions to industrial cyber-physical systems, KPI optimization, and agent-based enterprise architectures. Grants & Collaborations: Active participant in EU-funded research projects focusing on data integration and intelligent systems. No specific grant details provided in the text. Labs/Teams: Affiliated with computational and biomedical informatics groups at his institution, though specific lab names are not mentioned.

Björn LisperView profile

Professor

• Computer Science
• Software Engineering
• Real-Time Systems
• +5 more

Björn Lisper is a Professor at Mälardalen University, Sweden, affiliated with the School of Innovation, Design and Engineering and the Division of Computer Science and Software Engineering. His research focuses on formal methods, real-time systems, embedded software, static analysis, and high-level synthesis. He has contributed to advancements in WCET analysis, machine learning applications in testing, and compiler optimization techniques. His work emphasizes practical industrial applications, particularly in automotive and multi-core systems. Research Interests: Real-Time Systems & WCET Analysis Static Program Analysis High-Level Synthesis for FPGAs Machine Learning in Software Testing Formal Methods & Verification Embedded Systems Design Publications span topics like neural network accelerators, automated testing frameworks, and compiler optimizations, reflecting a blend of theoretical and applied computer science. His work is characterized by collaboration between academia and industry to bridge gaps in embedded software predictability and performance.

Kester CleggView profile

Research Fellow

• Air Traffic Simulation
• Safety-Critical Systems
• Avionics Safety
• +4 more

Dr. Kester Clegg is a Research Fellow in the Department of Computer Science at the University of York, affiliated with the High Integrity Systems group. He holds a PhD in non-standard computation and has extensive experience in safety-critical systems, including work on air traffic simulation, UAV safety, and carbon nanotube-based computation. His research focuses on automated hazard identification, avionics safety, and evolutionary algorithms applied to engineering challenges. Education PhD in Non-Standard Computation (University of York, 2007) Postgraduate Degrees in Linguistics and Computer Science Research Interests Automated risk discovery in complex systems Safety analysis for aviation and autonomous systems Material-based computing using carbon nanotubes Integration of safety models with system design Key Projects NASCENT project: Evolutionary computation for nanotube configurations (2015) SESAR project: Air traffic risk modeling using RAMS Plus software (2013) Rolls-Royce UTC: Safety-critical jet engine controller software (2002-2005) His work bridges theoretical computer science with practical safety engineering, emphasizing automated tools for identifying worst-case scenarios in high-risk environments. Current activities include teaching safety courses under the HISE initiative.

• Quantum Software Engineering
• Cyber-Physical Systems
• Digital Twin Technologies
• +3 more

Dr. Shaukat Ali is a leading researcher at Simula Research Laboratory (Certus Software V&V Center, Norway), with a PhD from the University of Oslo . His work bridges quantum software engineering and cyber-physical systems (CPS) validation, focusing on digital twins, autonomous vehicles, and healthcare IoT applications. Collaborates with institutions like South Dakota State University, COMSATS University, and Mohammad Ali Jinnah University Co-developed tools: QuCAT (Quantum combinatorial testing), DeepScenario (autonomous driving datasets), and EvoCLINICAL (medical digital twin evolution) Research spans quantum software testing (IBM quantum computers), uncertainty-aware validation of medical devices, and search-based optimization in CPS. His 2025 work introduces quantum circuit mutants, uncertainty-wise test oracles, and foundational models for digital twin creation. Publications in journals like ACM Transactions on Software Engineering and conferences including ICSE , GECCO , and IEEE Quantum Software reflect his interdisciplinary approach. Current projects address quantum software robustness, LLM-driven scenario realism, and safe adaptation in robotics.

• Information Retrieval
• XML Search Engines
• Text Search Engines
• +8 more

Shlomo Geva is an Adjunct Professor in the School of Computer Science at Queensland University of Technology's Faculty of Science. His research focuses on information retrieval systems, particularly in specialized areas including XML search engines, text search engines, link discovery, and document computing. His academic work spans multiple disciplines within computer science, with particular emphasis on information retrieval technologies and their applications. Professor Geva's research interests include clustering algorithms, cross language information retrieval, focused information retrieval, information retrieval systems, link discovery mechanisms, search engine technologies, text indexing and retrieval methods, and XML indexing and retrieval techniques. His work demonstrates a consistent focus on improving the efficiency and effectiveness of information access systems across various data formats and domains. His recent publications reveal a trend toward applications of information retrieval techniques in diverse fields including remote sensing, bioinformatics, and data stream processing. The research shows an evolution from traditional information retrieval problems toward more specialized applications requiring advanced clustering algorithms and efficient data processing techniques for large-scale datasets. Professor Geva has successfully supervised numerous doctoral students whose research topics include indoor environment mapping by robots, cross-language information retrieval, natural language query interfaces for XML, evolvable hardware, and autonomous robot behavior systems.

• Database Systems
• Data Engineering
• Data Governance
• +4 more

Sergi Nadal Francesch is a Professor at the Universitat Politècnica de Catalunya (UPC) , affiliated with the College of Informatics of Barcelona (FIB) and the Department of Service and Information Systems Engineering . He leads research within the inSSIDE and DTIM groups, focusing on database technologies, data governance, and knowledge graph applications. Research areas: Database Systems, Data Engineering, Knowledge Graphs, Data Governance, and Automated Data Lifecycle Management Email: sergi.nadal@upc.edu His recent work explores automated data pipelines , scalable data discovery , and AI-driven medical diagnostics . He contributes to knowledge graph lifecycle development and graph-driven federated data systems , with projects funded by Horizon Europe and Spanish national programs. Scientific Awards : UPC Award for Quality in University Teaching (2021), Best Doctoral Thesis in SISTEDES (2021), EDBT 2025 Best Demo Paper

Gregory KapfhammerView profile

Associate Professor

• Software Engineering
• Software Testing
• Mutation Testing
• +13 more

Gregory M. Kapfhammer is an Associate Professor in the Department of Computer and Information Science at Allegheny College, where he contributes to teaching, research, and open-source software development. He holds a B.S. from Allegheny College and earned his M.S. and Ph.D. from the University of Pittsburgh. His academic roles include serving as an associate editor for the Journal of Software: Evolution and Process and an academic editor for PeerJ Computer Science , and he actively participates in program committees for major conferences such as ICSE and ICST. B.S., Allegheny College M.S., University of Pittsburgh Ph.D., University of Pittsburgh His research focuses on empirical software engineering, particularly in software testing, with key areas including mutation testing, flaky tests, regression testing, database testing, and responsive web page testing. He develops and evaluates automated tools and techniques to improve software reliability and test suite effectiveness. His work often involves collaboration with undergraduate students at Allegheny College and researchers from institutions worldwide. The recent publications highlight a strong trend toward using empirical and machine learning methods to detect and mitigate weaknesses in test suites, particularly flaky and pseudo-tested code. His research spans both theoretical contributions and practical tool development, such as Chasten and PseudoSweep, demonstrating a balance between academic rigor and real-world applicability in software engineering. Associate Editor, Journal of Software: Evolution and Process (2012–2025) Academic Editor, PeerJ Computer Science (2019–2025) Program Committee Member, International Flaky Tests Workshop (2024–2025) Reviewer, Transactions on Software Engineering Kapfhammer is deeply involved in academic service and mentoring, frequently collaborating with students and colleagues on research projects. He has contributed to the development of automated assessment tools like GatorGrader and GatorGrade, which support programming education. His work is supported through academic collaboration rather than explicit grant funding mentioned in the text. He leads research projects that integrate empirical methods with tool building, often resulting in open-source software that benefits both academia and industry. He is a co-host of the popular podcast Software Engineering Radio , where he interviews leading experts in the field, further amplifying his impact on the software engineering community. His lab and research team involve undergraduate researchers at Allegheny College, fostering hands-on learning and innovation in software testing and analysis.

Russ HuntView profile

Associate Professor

• Human Factors
• Systems Engineering
• Industrial Engineering
• +3 more

Russ Hunt is an Associate Professor in the Department of Systems and Industrial Engineering at Kennesaw State University (KSU). He holds a PhD in Mechanical Engineering from the University of Illinois and has a diverse career spanning academia, entrepreneurship, and administration. He co-founded Search Technology, Inc., and later led the Southern Polytechnic Applied Research Corporation before the merger with KSU. His roles at KSU include Assistant Dean of Engineering and Associate Vice President of Research. Degrees: PhD (University of Illinois, 1981), MS (University of Illinois, 1979), BS (University of Illinois, 1978). His research focuses on Human Factors , particularly in warning design, human-product interfaces, and system design. His work bridges human behavior with technical systems, emphasizing safety and usability. Publications highlight trends in aerospace and manufacturing applications, fuzzy rule-based models, and fault diagnosis methodologies. Russ Hunt actively consults through RM Hunt, Ltd., specializing in human factors analysis and product design. He oversees the Kennesaw Applied Research Center (SPARC) and has taught graduate courses like Human Factors Engineering and Systems Engineering.

Petros KatsioloudisView profile

Professor

• STEM Education
• Technology Education
• Engineering Technology
• +6 more

Petros Katsioloudis is the Associate Dean for Faculty Affairs and Research at Old Dominion University's Darden College of Education & Professional Studies, with a focus on STEM Education , Technology Education , and Engineering Technology . He holds an Ed.D. in Technology Education from North Carolina State University (2007), an M.Ed. in Technology Education (2004), a B.S. in Industrial Technology (2003), and specialized diving certifications from IANTD/PADI. Education: Ed.D., Technology Education, North Carolina State University (2007) M.Ed., Technology Education, California University of Pennsylvania (2004) B.S., Industrial Technology, California University of Pennsylvania (2003) A.S., Pennsylvania Gunsmith School (1998) His research explores the intersection of spatial visualization , pedagogical techniques , and non-conventional learning styles , often integrating virtual reality and dynamic visualizations to enhance educational outcomes. His 15 most recent publications (2004–2018) address topics like holographic modeling, music's impact on technical drawing, and game-based port logistics simulations. Scientific Awards include: Distinguished Technology and Engineering Professional (2017), New Investigator Grants Award (2010), DELOS Best Paper Award (2012), and multiple Outstanding Graduate Student Citations (2004, 2006). He has secured over $4.5 million in grants for projects such as Research Experiences for Teachers ($500,000) and VisPort port logistics visualization ($21,888). His work bridges academia and practical application through initiatives like Project SEARCH 2.0 , Maritime Mechatronics Technician Training , and Policy-Ready Citizen Science , reflecting a commitment to experiential learning and workforce development.