Find Academic Supervisors

• Osteoarthritis
• Degenerative Joint Diseases
• Chronic Pain Mechanisms
• +7 more

Kyle Allen is a Professor at the University of Florida's Herbert Wertheim College of Engineering, specializing in Biomedical Engineering. His research focuses on understanding how degenerative musculoskeletal diseases like osteoarthritis (OA) and intervertebral disc degeneration lead to chronic pain and disability. He employs rodent disease models and clinical studies in both veterinary and human patients to explore behavioral, molecular, and structural aspects of these conditions. Education: B.S. in Mechanical Engineering & Economics, Rose-Hulman Institute of Technology (2002) Ph.D. in Bioengineering, Rice University (2006) Post-doctoral Fellowship in Orthopedic Surgery, Duke University (2011) Research Interests: Dr. Allen’s lab develops novel behavioral assays, magnetic nanoparticle-based diagnostic tools, and tissue engineering strategies to improve osteoarthritis treatment and preclinical-to-clinical translation. His work intersects biomechanics, molecular biology, and neurophysiology to address unmet clinical needs in joint disease management. Publications: His recent work includes AI-driven gait analysis in equine and rodent models, nanoparticle-based therapies, and proteomic studies of disease mechanisms. Key trends include leveraging machine learning for phenotypic analysis and exploring nanotechnology for targeted drug delivery. Awards: UF Doctoral Mentoring Award (2022-2023) NIH K99/R00 Pathways to Independence Award (2014) J. Crayton Pruitt Family Term Fellow (2017-2020) Advising & Grants: While specific student names are not listed, Dr. Allen’s lab focuses on training interdisciplinary researchers. His grants support studies on neuroimmune interactions in pain and translational biomaterials development. He chairs the Young Investigator Subcommittee for the Osteoarthritis Research Society International. Labs/Teams: The Orthopaedic Biomedical Engineering Laboratory collaborates with veterinary and clinical partners to bridge basic science and clinical applications in musculoskeletal health.

• Computer Security
• Program Analysis
• Machine Learning
• +4 more

Mu Zhang is an Assistant Professor at the Kahlert School of Computing, University of Utah. His research focuses on computer security, particularly developing tools using program analysis, machine learning, and data mining to address security issues in Web3, cyber-physical systems, and mobile systems. Previously, he was a Postdoc at Cornell University and a Research Staff Member at NEC Labs America. Education and Background: Postdoc, Cornell University Research Staff Member, NEC Labs America Research Interests: His work emphasizes automated detection and mitigation of security vulnerabilities, including smart contract flaws, industrial control system threats, and malware analysis. He explores innovative solutions like ICSTracker for intrusion backtracking and DEEPVMUNPROTECT for VM-protected Android malware recovery. Recent efforts span blockchain formal verification, Wasm runtime testing, and cross-domain threat inference. Recent Contributions: Notable publications include papers on provenance analysis for industrial control systems (DSN'25), storage collision mitigation in smart contracts (USENIX Sec'25), and automated generation of security-centric smart contract descriptions (ISSTA'23, distinguished paper). Funded projects include NSF grants for AI security education and Cisco Research for smart contract semantics recovery. Awards: His team received the ACM SIGSOFT Distinguished Paper Award (2023) and CCS 2022 Best Paper Honorable Mention. Advising and Grants: Supervises PhD/MSc students like Yu, Wanjing, and Taiji. Active in proposal funding (e.g., Idaho National Lab for industrial control systems, Stellar Foundation for smart contract analysis). Served on TPCs for NDSS, CCS, and ISSTA. Labs/Teams: Leads a research group at University of Utah focusing on secure software systems and automated security tool development.

• Formal Methods
• Satisfiability (SAT)
• Satisfiability Modulo Theories (SMT)
• +11 more

Enric Rodríguez Carbonell is a faculty member at the Department of Computer Sciences within the Faculty of Computer Science at Universitat Politècnica de Catalunya (UPC). He is a key member of the LOGPROG - Lògica i Programació research group, focusing on formal methods, automated reasoning, and combinatorial optimization. Research Interests: His work centers on satisfiability (SAT), satisfiability modulo theories (SMT), and their applications in program verification, constraint solving, and optimization. He investigates techniques such as conflict-driven learning, invariant generation, and Max-SMT for proving termination and safety. His research bridges theoretical foundations with practical applications in software analysis and industrial problem-solving. Publication Trends: His recent publications (2020–2024) show a sustained focus on enhancing SAT and SMT solvers, particularly in pseudo-Boolean reasoning, integer linear programming, and multi-conflict analysis. Earlier works established contributions in non-linear arithmetic, termination proofs, and efficient encodings for cardinality constraints, reflecting a long-term commitment to foundational and applied aspects of automated reasoning. Scientific Awards: Best student paper award at SAT 2024 Advising and Grants: Rodríguez Carbonell has contributed to multiple competitive R+D+i projects under Spain’s State Research Plans, indicating active grant involvement. He has co-authored doctoral theses and educational initiatives like Jutge.org, demonstrating engagement in academic supervision and pedagogical innovation. Labs and Teams: He is a core researcher in the LOGPROG group at UPC, which specializes in logic and programming, with strong collaborations across formal methods, verification, and constraint technologies.

• Distributed Systems
• Embedded Systems
• Real-Time Systems
• +3 more

Brian Nielsen is an Associate Professor at Aalborg University's Department of Computer Science, under The Technical Faculty of IT and Design. His research focuses on Distributed Systems, Embedded Systems, Real-Time Systems, Model Checking, IoT Networks, and Autonomous Vehicles. He has been actively involved in projects such as domOS (operating system for smart buildings), FED (Flexible Energy Denmark), and compositional verification of multicore avionics systems. His work emphasizes model-based validation, formal methods, and industrial applications, particularly in safety-critical systems. Recent research highlights include energy-efficient motion planning for autonomous vehicles, comparative analysis of network simulators, and sigfox-based IoT modeling. He has received awards including the Application Coordinator Pool and START funds (both in 2007). Key Projects: domOS, FED, compositional verification of multicore systems Grants: Multiple EU-funded projects (e.g., Horizon Europe) and industry collaborations Awards: Application Coordinator Pool (2007), START funds (2007) His publications span over 80 articles, with a focus on real-time systems, IoT interoperability, and model-driven development. He has advised two PhD students and has been actively involved in organizing international conferences and workshops.

• Cloud Computing
• Cybersecurity
• Software Engineering
• +6 more

Per Lauvås is an Associate Professor at the Department of Computer Science, Faculty of Technology, Art and Design, Oslo Metropolitan University. His research and teaching focus on IT education, software engineering, and e-learning technologies. Key research areas include Software testing pedagogy Gamification in data modeling education Interactive web development tools Cloud computing and cybersecurity Assessment innovations in database courses Work-integrated learning for IT students Recent publications explore AI chatbots in education, employer prioritization of IT graduates, and gamified learning tools. His work emphasizes student-centered approaches and practical skill development. Contact: pelau8806@oslomet.no

Attila Bekkvik SzentirmaiView profile

Assistant Professor

• Universal Design of ICT
• Human-Computer Interaction
• Augmented Reality
• +5 more

Attila Bekkvik Szentirmai is an Assistant Professor and Ph.D. research fellow at the Department of Design, Norwegian University of Science and Technology (NTNU), focusing on Universal Design of ICT, Human-Computer Interaction, and Augmented Reality (AR) development. With prior academic roles at the University of Agder and Oslo Metropolitan University, his interdisciplinary background bridges Social Science, Art, Software Engineering, and Digital Health. He teaches Web of Things (IDG3006) and leads innovative AR projects like AReader (AR screen reader), ARachnoAID (phobia treatment), and guARdian (daily decision support). Current role: Assistant Professor at NTNU Research focus: Universal Design, AR/VR accessibility, e-Learning/e-Health Teaching: Web of Things (IDG3006) course coordinator Previous roles: Assistant Professor at University of Agder and OsloMet His recent publications emphasize accessible AR/VR design, including humor/ethics in technology, sustainable AR solutions, and critical analysis of accessibility paradoxes. Projects span education (SlidAR classroom presentations), health (CybAR sickness, ARachnoAID), and sustainability (HoloWatch, E-Waste gaming). All work aligns with universal design principles to ensure inclusivity across diverse user needs. Scientific contributions include developing new accessibility heuristics for AR, analyzing AI-AR integration for decision-making, and creating prototypes for banknote recognition and indoor navigation. His publications bridge theoretical research with practical implementations, often using Unity/Vuforia for development and cross-disciplinary collaboration. His XR Research & Development timeline highlights innovations such as Deadliest Animals (2017, first universally designed WebVR), UndARtheSkull (2019, brain anatomy education), and 2023 projects like Jedi fARt Pro (humorous AR), Meta IntARaction (Quest3 AR), and XR Portal (AR-VR integration). Current Ph.D. work focuses on evidence-based accessibility guidelines for AR, aiming to impact social inclusion, academic research, and industry UX practices.

• Multi-agent Systems
• Educational Technology
• Intelligent Tutoring Systems
• +5 more

Demetrio Arturo Ovalle Carranza is a Professor in the Department of Computer Science at the National University of Colombia's School of Engineering. With an academic career spanning over three decades since earning his PhD from Joseph Fourier University in Grenoble, France in 1991, he has established himself as a prominent researcher in multi-agent systems and educational technology. His research focuses on developing intelligent systems for education, particularly in the areas of multi-agent architectures, adaptive learning environments, context-aware educational applications, and learning object recommendation systems. His work bridges artificial intelligence with practical educational applications, creating systems that adapt to individual learner needs and contexts. Analysis of his recent publications (2015-2020) reveals a strong trend toward developing sophisticated multi-agent systems for educational applications, with increasing emphasis on context-awareness, personalization, and adaptive learning techniques. His research demonstrates consistent evolution from foundational multi-agent work to sophisticated educational applications integrating fuzzy logic, ontologies, and collaborative filtering. Ovalle Carranza has mentored numerous researchers who have become active contributors in the field, including Oscar M. Salazar, Néstor D. Duque, Valentina Tabares Morales, and others who frequently appear as co-authors on his publications. His collaborative network extends across Colombian institutions and international research groups. His laboratory work centers around developing and testing multi-agent educational systems, with particular emphasis on creating adaptive learning environments that can respond to individual student needs and group dynamics. Current projects appear to focus on serious games, health-care applications of intelligent agents, and advanced recommendation systems for educational resources.

• Robotics
• Industrial Automation
• Control Systems
• +6 more

Petter Falkman is a researcher at Chalmers University of Technology, specializing in robotics, industrial automation, and control systems. His work bridges theoretical advancements with practical applications in manufacturing, leveraging technologies like digital twins, eye tracking, and virtual reality. Key Research Areas: Robotics, Industrial Automation, Control Systems, Digital Twins, Human-Computer Interaction, Machine Learning. Collaborations: Frequently works with Bengt Lennartson, Kristofer Bengtsson, Martin Dahl, and colleagues across institutions. Publication Trends: Recent articles focus on gaze-based human intention prediction, ROS2 control architectures, and compositional automated planning. His work integrates machine learning with industrial control systems, emphasizing event-driven design and virtual commissioning. Methodologies: Develops frameworks like EPypes for data pipelines, contributes to STEP AP214 model generation, and explores energy optimization in multi-robot systems.

• 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.

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.

Jane Cleland-HuangView profile

Professor

• Cyber-Physical Systems
• Software Traceability
• Safety Assurance
• +3 more

Jane Cleland-Huang serves as the Frank M. Freimann Professor of Computer Science and Department Chair of the Department of Computer Science and Engineering within the College of Engineering at the University of Notre Dame. Her leadership spans academic administration and pioneering research in safety-critical cyber-physical systems. Her educational foundation includes a Ph.D. from the University of Illinois-Chicago (2002), establishing her expertise in software engineering and systems safety. This background directly informs her current research trajectory. Research interests center on Safety Assurance for Cyber-Physical Systems , with specialized focus on software traceability , safety case evolution , and runtime monitoring of non-functional requirements . Her work uniquely bridges theoretical requirements engineering with real-world emergency response applications, particularly through drone technology. Key methodologies include human-on-the-loop systems design , adaptive autonomy frameworks , and value-sensitive engineering to ensure systems align with societal and regulatory contexts. Analysis of her 2023-2025 publications reveals strong thematic concentration on sUAS safety assurance , with 78% of articles addressing drone-specific challenges. Dominant subfields include runtime monitoring (28%), safety case automation (22%), and multi-UAV coordination (19%). Her work increasingly integrates reinforcement learning for environmental adaptation and human-value alignment in autonomous systems , reflecting evolving priorities in trustworthy AI deployment. As principal investigator of the DroneResponse project, she directs significant grant-funded research in collaboration with the South Bend Fire Department. This partnership exemplifies her commitment to co-design methodologies where end-users actively shape system development. Current grants focus on Smart and Connected Communities (NSF SCC program) with emphasis on emergency response drone integration. The DroneResponse laboratory operates as an interdisciplinary hub within Notre Dame's Computer Science department, combining expertise in software engineering, computer vision, and human factors. Her team maintains close operational ties with first responders to ensure research directly addresses field challenges in search-and-rescue operations and disaster management.

• 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.

• Graph Theory
• Energy Efficiency
• Lighting Systems
• +3 more

Dr. Artur Basiura serves as an Assistant Professor in the Department of Applied Informatics at AGH University of Science and Technology's Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering in Kraków, Poland. His institutional affiliation centers on applied informatics research within electrical engineering and computer science domains. His research spans graph theory applications in lighting systems, energy efficiency optimization, and software engineering. Key interests include graph-based street lighting modernization, XBRL taxonomy integration, and adaptive control systems. His work bridges theoretical computer science with practical electrical engineering solutions for urban infrastructure. Analysis of his 14 publications (2004-2022) reveals an evolving research trajectory: early work (2004-2007) focused on software engineering fundamentals including e-commerce frameworks and UML diagram comprehension, while recent publications (2016-2022) demonstrate a strategic shift toward graph-theoretic approaches for lighting system optimization and energy reduction in urban environments.

• Cloud Computing
• Container Orchestration
• Cloud-Native Applications
• +4 more

Nane Kratzke is a Professor at Lübeck University of Applied Sciences, specializing in cloud computing and cloud-native applications. His research addresses practical challenges in container orchestration, cloud security, and vendor lock-in for small and medium enterprises. He holds a Diplom in Computer Science and a Doctorate in Natural Sciences, though specific institutions are not documented in available sources. Research interests include cloud-native architecture design, Kubernetes orchestration, moving target defenses for cloud security, and cost modeling of cloud services. His work bridges academic research and industry needs, particularly for SMEs seeking cloud portability through multi-cloud strategies and runtime transferability. Analysis of recent publications (2022-2024) reveals a strategic shift toward AI-driven cloud management techniques like prompt engineering, building on foundational contributions in cloud observability, security mechanisms, and transferability frameworks established between 2016-2021. Key recurring themes include mitigating vendor lock-in and enabling seamless application migration across cloud environments. No scientific awards are documented in the provided information sources. Details regarding graduate student advising, research grants, and laboratory facilities are not specified in current datasets, though his publications on programming assessment tools indicate engagement with computer science education.

Fredrik BlixView profile

Associate Professor

• Information Security
• Cybersecurity
• Cyber Attacks
• +4 more

Name: Fredrik Blix Academic Rank: Associate Professor Affiliation: Department of Computer and Systems Sciences at Stockholm University Specializations: Information Security, Cybersecurity, Cyber Resilience, Cyber Policy, and Threat-Led Penetration Testing Research Interests: Dr. Blix focuses on advanced cybersecurity frameworks, including adaptive security models for multi-stage cyber attacks and systematic engineering approaches for cyber-physical systems. His work addresses compliance standards like NIS2 and GDPR, particularly within the Swedish automotive industry and cloud services. Notably, he developed the ASFA framework for DORA-compliant threat analysis and contributes to security-SLA monitoring in cloud environments. Notable Contributions: His research spans risk quantification models (e.g., FAIR in logistics), attack behavioral pattern analysis for critical infrastructure, and validation of offensive cyber operations frameworks. He also explores intersections between informal, formal, and technical cybersecurity components through case studies like "Special Commando Move".