Find Academic Supervisors

• Learning Analytics
• Educational Technology
• Computer-Supported Collaborative Learning
• +4 more

Dr. Matthias Ehlenz is a Researcher at RWTH Aachen University's Informatik 9 – Learning Technologies group, where he coordinates and develops concepts for the MediaLab in teacher training. He holds a Dr. rer. nat. (PhD) earned in 2023 for his work on sustainable ecosystems for computer-supported collaborative learning. His research focuses on: Learning analytics infrastructures (xAPI, multimodal data) Collaborative learning technologies (multi-touch tables, VR/XR environments) Serious game design and assessment Human-centered approaches in educational technology Open science and sustainable EdTech development Ehlenz's recent publications (2021-2025) demonstrate strong interdisciplinary trends: 40% focus on learning analytics infrastructures, 30% examine collaborative interfaces (tabletops/XR), 20% address teacher training/digital pedagogy, and 10% explore open science practices. The work shows increasing emphasis on immersive technologies and scalable systems. He actively advises graduate researchers, supervising at least six master's/bachelor's candidates on topics including: XR learning environments AI in education Learning analytics interfaces Collaborative game design Ehlenz co-leads the Learning Technologies Innovation Lab, developing open-source tools for educational research. He contributes significantly to the DELFI conference organization and promotes open science in learning technology research.

• Computer Science
• Language Technology
• Computer Didactics
• +4 more

Viggo Kann is a Professor of Computer Science at the Royal Institute of Technology (KTH) in Stockholm, Sweden, holding this position since 2000. He serves as Director of Studies in the Theoretical Computer Science department at KTH's School of Electrical Engineering and Computer Science, a role he has maintained since 1998 with a brief interruption from 2012-2015. One-fifth of his time is dedicated to the Department of Learning, where he teaches courses on examinership and developing learning with grading criteria. He also chairs KTH's Language Committee and coordinates the director of studies network, PA network, PriU groups, and major institutional events. Professor Kann's research spans language technology and computer didactics, with current projects focusing on examination quality and diversity, cheating prevention, examiner training, and program-coordinating courses. His work bridges theoretical computer science with practical educational applications, particularly in assessment methodologies and educational technology. His recent publications reveal a strong emphasis on educational aspects of computer science, examining student behavior, programming fluency, and the impact of emerging technologies like ChatGPT on academic integrity. He has also published extensively on language technology, including grammar checking systems and natural language processing tools for Swedish language processing. As examiner and course coordinator, Professor Kann oversees multiple courses including Algorithms, Data Structures and Complexity (DD2350), Ethics in Introduction to Computer Science (DD1348), and various specialized degree projects across industrial economics, machine learning, systems engineering, robotics, and communication systems. His leadership in educational development initiatives at KTH demonstrates significant institutional influence in shaping educational policies and practices.

• Discrete Optimization
• Graph Theory
• Fuzzy Logic Systems
• +4 more

Elina Valentynivna Tereshchenko serves as Associate Professor and Head of the Department of Systems Analysis and Computational Mathematics at Zaporizhzhia Polytechnic National University's Faculty of Computer Science and Technologies. Holding a Candidate of Physical and Mathematical Sciences degree (equivalent to PhD), she graduated from Dnipropetrovsk State University in 1992 with specialization in 'automatics and control in technical systems'. Her research spans discrete optimization , graph theory , and fuzzy logic systems , with recent publications focusing on ontology engineering, team formation algorithms, and agricultural data analysis. Current projects include ontology control systems in Neo4j (2025), competition-based team optimization models (2024), and sunflower cultivation ontologies for Ukrainian agricultural contexts. Her 15 most recent publications (2022-2025) reveal strong interdisciplinary work connecting computer science with agricultural informatics, cybersecurity, and economic modeling. Key trends include graph-theoretic formulations for team formation, fuzzy logic applications in access control, and optimization under resource uncertainty. Professional affiliations include: ORCID: 0000-0001-6207-8071 Scopus: 57202151469 Google Scholar: https://scholar.google.com/citations?user=DwEYAVcAAAAJ&hl=uk She teaches core subjects including discrete mathematics , optimization methods , algorithm theory , and decision-making theory . Her departmental leadership involves developing educational programs such as the bachelor's curriculum 'Intelligent Technologies and Decision Making in Complex Systems' (2021). Research infrastructure includes work on the HELIANTHUS ontology for sunflower cultivation and analytics modules for war damage assessment systems. Current projects integrate graph theory with competitive dynamics for high-performance team design.

• systems thinking
• artificial intelligence
• cyber-physical systems
• +6 more

Maria Yurievna Tyagunova is an Associate Professor and Dean at the Faculty of Computer Science and Technology, Zaporizhia National Technical University. She holds a PhD in Computer Systems and has been active at the university since 2006, specializing in cyber-physical systems, artificial intelligence, and neural networks. Education: Master's in Specialized Computer Systems (ZNTU, 2006), PhD in Task Dispatching Methods (2010) Research: Systems thinking, complex systems theory, distributed computing, and AI-driven optimization Teaching: Courses in cyber-physical systems, Industry 4.0, and intelligent systems Her recent publications focus on AI integration in education, decentralized mesh networks, smart infrastructure, and wireless communication challenges. These works reflect trends in scalable systems, real-time data processing, and cybersecurity for critical applications. Contact details include her office at Zhukovsky St., 64, Zaporizhia, Ukraine, with phone +38(061)7642506 and fax +38(061)7642141.

• Artificial Intelligence
• Machine Learning
• Probabilistic Inferencing
• +5 more

Barry Drake serves as an Adjunct Professor in the School of Computer Science at the University of Technology Sydney (UTS), where he is also affiliated with the Faculty of Engineering and Information Technology and the Data Science Institute. Additionally, he holds the position of Co-Chief Scientist at the Digital Health Cooperative Research Centre and participates in government advisory committees. His career bridges academic research and industry application, with significant experience in translating research into practical technology solutions for business and government sectors. Drake earned his PhD in Computer Science from UNSW Australia (1998-2003) and a BSc with First Class Honors in Computer Science from UTS (1991-1996). His educational background is complemented by a Certificate of Proficiency for Radio Fitter/Mechanic Electronic Systems from the Royal Australian Navy. His research focuses on algorithms and software for practical smart systems, with particular expertise in applications of AI and machine learning, probabilistic inferencing and knowledge compilation, learning probabilistic models, and fast-efficient near-neighbor searching in ultra-high dimensional spaces. His work demonstrates a clear trajectory toward health informatics applications , especially in health systems and delivery of health services, where he has made significant contributions through projects like the Lumos statewide linkage programme. The analysis of his publication record reveals a consistent pattern of research bridging theoretical computer science with practical healthcare applications. His recent work shows increasing focus on health data integration, patient journey modeling, and privacy-preserving synthetic data generation for healthcare applications, while maintaining his foundational expertise in probabilistic models and efficient search algorithms. Inventor on 20 filed patents ORCID identifier: 0000-0003-0572-9936 Drake actively supervises Masters and PhD students according to his profile, and his funded research portfolio includes multiple grants from the Digital Health CRC and NSW Health. His industry experience, particularly his 13 years at Canon Information Systems Research Australia where he served as Senior Principal Engineer and lead researcher for machine learning, informs his approach to technology research methods from a commercial perspective. His current projects focus on the impact of integrated care in New South Wales, synthetic data generation, and patient journey modeling. As Co-Chief Scientist at the Digital Health CRC, Drake contributes to a major national initiative focused on digital health innovation. His work with the Lumos programme has created Australia's first statewide linked data asset across primary care and other health settings, providing unique insights about cross-setting healthcare utilization. This initiative represents a significant contribution to health data infrastructure in Australia.

• Deep Learning
• Natural Language Processing (NLP)
• Internet of Things (IoT) Systems
• +4 more

Dr. Tazar Hussain is a Lecturer in Computing Science at the School of Computing, Ulster University , where he teaches deep learning and IoT. He completed his PhD at Ulster University on IoT management frameworks for decision-making under unreliability and worked as a part-time Research Associate on the BTIIC 'Data to Action' project. Previously, he served as a Lecturer at King Saud University (9 years) , securing research funding from NPST and DSU. Education: PhD (Ulster University), MSc in Data Telecommunication and Networks (Salford University), Bachelor of Information Technology (Sarhad University) Research Focus: Deep Learning, NLP, IoT Security, Explainable AI, and Human Activity Recognition (HAR) Projects: Active member of the PwC Advanced Engineering and Research Centre (2021-2026), specializing in Few-Shot Learning and Smart Cities His work bridges IoT systems and cybersecurity , with a focus on intrusion response mechanisms. Publications span machine learning applications in security, risk-based decision frameworks , and C4I systems . He is a certified IBM Security Specialist and trained in smart cities and cloud technologies. Key Trends: 1) Application of Explainable AI in pathology LIS systems, 2) Cognitive modeling for IoT cyberattack responses, 3) Risk-based decision-making in IoT environments, 4) Cost-sensitive intrusion response systems, 5) Formal methods (e.g., Situation Calculus) in cybersecurity Collaborations include Invest Northern Ireland and BTIIC , with expertise aligning to UN Sustainable Development Goals in digital security and smart infrastructure.

• Machine Learning
• Artificial Intelligence
• Computational Biology
• +7 more

Andreas Karwath is an Associate Professor at the University of Birmingham, affiliated with the Cancer and Genomic Sciences Institute, Institute for Interdisciplinary Data Science and AI, and The Centre for Computational Biology. His research spans computational biology, artificial intelligence, and data science applications in healthcare and cancer genomics. His research interests include: Machine Learning and Artificial Intelligence Computational Biology and Bioinformatics Phenotype Analysis and Ontology Cancer Genomics and Radiomics Differential Diagnosis Systems Dr. Karwath's research fingerprint reveals significant contributions to Inductive Logic Programming (100%), Semantic Similarity (89%), Phenotype Profiles (80%), Machine Learning (74%), Learning Systems (74%), Ontology (71%), Differential Diagnosis (66%), and Neural Networks (63%). His work consistently applies computational approaches to biomedical challenges, with recent focus on cancer outcomes prediction, cardiovascular monitoring through wearables, and phenotype library development for health data research. His scientific contributions include 73 research outputs spanning two decades, with notable recent publications in high-impact journals including Nature Medicine, Machine Learning, and Frontiers in Oncology. His work has been cited across multiple platforms with significant attention from news outlets and academic readers. Dr. Karwath serves as Co-Investigator on several major research projects: PETNECK2 - Radiomics in Outcome Predictive Models for Head and Neck Cancer (2025-2027, NIHR) ACORN: Assessment of Chronic Opioid Risk using Neurobiology (2024-2027, Wellcome Leap Inc.) PINK - Provision of Integrated Computational Approaches for Safe-and-Sustainable-by-Design Chemicals and Materials (2024-2027, UKRI) NIHR BRC Theme - Data, Diagnostics & Decision Tools (2022-2027, NIHR) His collaborative network spans multiple UK institutions and international partners, with frequent collaboration with Gkoutos, G.V. across multiple projects. His research has practical clinical applications, particularly in cancer treatment outcomes prediction and digital health monitoring systems.

• Building Information Modeling
• Digital Twinning
• Information Management
• +5 more

Prof. Dr.-Ing. Sebastian Esser serves as Group Lead for Information Management at the Chair of Computing in Civil and Building Engineering at Technical University of Munich. His research focuses on advancing Building Information Modeling (BIM) methodologies, particularly in infrastructure and railway applications. He contributes significantly to international standardization efforts including IFC-Road and IFC-Rail projects, and leads research initiatives such as RIMcomb and BauPuls360. Dr. Esser's research spans several critical areas in digital construction: Graph-based version control systems for BIM collaboration Digital twin development for infrastructure management Semantic modeling of built environments BIM-based regulation checking for railway infrastructure Interdisciplinary model coordination techniques Knowledge representation in civil engineering His work bridges theoretical computer science with practical civil engineering applications, focusing on improving data interoperability and workflow efficiency in construction projects. Analysis of his recent publications reveals a strong emphasis on graph-based approaches to BIM challenges. His research has evolved from foundational work on BIM programming interfaces to sophisticated implementations involving knowledge graphs, semantic reasoning, and digital twin architectures. Key trends include increasing integration of semantic web technologies with BIM standards, development of specialized query interfaces like GraphQL for construction data, and application of formal methods to infrastructure modeling problems. Dr. Esser actively supervises numerous bachelor's and master's theses annually, with recent topics covering graph-based entity alignment, BIM-GIS integration for flood assessment, incremental model updates, and digital twin implementations. His teaching portfolio includes courses such as Bau- und Umweltinformatik, BIM.fundamentals, BIM.infra, and Semantic Modeling of the Built World, demonstrating his commitment to educating the next generation of digital construction professionals. He is involved in multiple research initiatives including DFG FOR 5672 (The information backbone of robotized construction), SPP 2187 (Adaptive modularized constructions), and AM2PM (Additive to Predictive Manufacturing). His laboratory work spans the BIM-Lab and related computational infrastructure supporting his research in digital construction technologies.

• Higher Education Research
• Educational Psychology
• Information Systems
• +5 more

Dr. Justtina John serves as Lecturer and Diploma Program Leader in the Department of Computing, School of Engineering, Computing and Built Environment at University of Wollongong Malaysia KDU Penang University College. With over 14 years at the institution since 2011 and 20+ years total in Malaysian private higher education, she teaches core courses including Object Oriented System Analysis and Design, Business Information Systems, and Strategic Systems Management across diploma and bachelor programs. Her educational credentials feature a Doctorate of Business Administration (2018), MSc in Information Technology (2003), and Bachelor in Information Technology (2001), all from Universiti Utara Malaysia. The doctoral research employed PLS-SEM methodology to investigate workload pressure, person-job fit, and innovation trust effects on educator creativity in Malaysian private universities. Dr. John's research program bridges educational psychology and computing applications, with dual streams examining higher education dynamics and information systems development. Her scholarly output since 2015 demonstrates consistent publication in both educational research (focusing on faculty creativity metrics) and applied computing (including route optimization systems and environmental data visualization tools), reflecting an interdisciplinary approach to academic challenges. As Diploma Program Leader, she oversees operational management for Diploma in Information Technology and Diploma in Digital Animation programs, handling curriculum revisions, student coordination, and academic quality assurance. Her international collaboration with Gorondutse, A.H. at the 2017 Asian Academy of Management Conference indicates active engagement with global academic networks, while her quantitative research expertise provides methodological rigor to institutional improvement initiatives.

Ivan TotView profile

Associate Professor

• Information Systems
• Biometric Verification
• Mobile Applications
• +4 more

Ivan Tot is an Associate Professor at the University of Defense's Military Academy in Belgrade, with a career spanning roles as Teacher (1999-2010) and Assistant Professor (2015). His academic foundation includes a Doctorate from the Military Academy (2010), a Master's from the University of Kragujevac (2008), and an undergraduate degree from the Military Technical Academy (1999). His research bridges Information Systems , Biometric Verification , and IoT Security , with applications in defense logistics, mobile communications, and healthcare technology. Recent publications explore biometric maternity verification, encrypted SMS applications, and military data-gathering techniques. He contributed to key projects: New information technologies for analytical decision-making (Ministry of Science, 2010-2016) Performance Analysis of Tactical Telecommunications Systems (Military Academy, 2010-2015) Database models for logistics decision support (Military Academy, 2013-2015) He authored the textbook Information Systems for Decision Support (2013) and maintains a focus on practical, security-oriented solutions.

• Concurrency Theory
• Process Algebra
• Trustworthy Systems
• +7 more

Alessandro Aldini is an Associate Professor in the Section of Informatics and Mathematics within the Department of Pure and Applied Sciences (DiSPeA) at the University of Urbino Carlo Bo. His academic work focuses on theoretical computer science with applications to security and verification of complex systems. His research interests span several key areas: Design and verification of concurrent and distributed computer, network, and software systems Trust models and trustworthy systems Concurrency theory and (nondeterministic, probabilistic, and Markovian) process algebra Exact and approximate behavioral equivalences and equivalence checking Exact and approximate noninterference approach to information flow analysis Modal logics and model checking Security, dependability, and performability analysis Professor Aldini serves as the UNIURB research unit leader for the PRIN project AsCoT-SCE (Assessing Compliance of IoT API for Security Critical Environments) and participates in other significant research initiatives including DeKLA (Developing Kleene Logics and their Applications) and NiRvAna (Noninterference and Reversibility Analysis in Private Blockchains). He is actively involved in the academic community through the Italian Chapter of the EATCS and IFIP WG 11.14 Secure Engineering. His teaching responsibilities include Programming Languages and Software Verification and Cybersecurity courses across multiple Informatics degree programs. Professor Aldini has supervised numerous PhD students and postdoctoral researchers. His academic contributions include the book "A Process Algebraic Approach to Software Architecture Design" and his PhD thesis "Security and Performance Analyses in Distributed Systems."

Apostolos AmpatzoglouView profile

Associate Professor

• Technical Debt
• Reverse Engineering
• Software Maintainability
• +5 more

Apostolos Ampatzoglou serves as Associate Professor in the Department of Applied Informatics at the University of Macedonia, where he leads research in software engineering with particular emphasis on technical debt management and software quality. Previously, he held an Assistant Professor position at the University of Groningen (2013-2016) and maintains active collaborations across European research initiatives. His academic credentials include a PhD in Software Engineering from Aristotle University of Thessaloniki (2013), MSc in Computer Systems from the University of Macedonia (2005), and BSc in Informatics from the Technological Education Institute of Thessaloniki (2003). Dr. Ampatzoglou's research program centers on technical debt quantification, reverse engineering, and software maintainability. He pioneered financial models for technical debt management and developed metrics for assessing ripple effects in software systems. His work bridges theoretical foundations with industrial applications through projects like SDK4ED and SmartCLIDE, focusing on energy-efficient development and cloud service engineering. Current investigations explore machine learning applications for vulnerability prediction and technical debt prioritization. His extensive publication record reveals strong trends in applying AI to software quality assurance, with recent work emphasizing transformer models for vulnerability detection and explainable AI for technical debt identification. He actively investigates energy-aware development practices and service-oriented architecture patterns in cloud environments. Notable recognitions include: Top-7 reviewer for Journal of Systems and Software (2022) Best paper awards at IGSCC'21, ICSR'18, and EASE'17 18th most active Consolidated Researcher in Software Engineering (2013-2020) 3rd most active Early Stage Researcher (2010-2017) Multiple personal research grants from National Scholarships Association He has successfully supervised PhD candidates including Dr. Areti Ampatzoglou (Best PhD Thesis Award, University of Groningen) and Dr. Elvira-Maria Arvanitou (VERSEN Institute award). His research is funded through major European projects such as SDK4ED, SmartCLIDE, and SKILLAB, with recent grants exceeding €2M in total funding. Current work focuses on FAIR data implementation and skills gap analysis in European labor markets. As leader of the Software Engineering Lab at the University of Macedonia, he directs a 15+ member team working on technical debt management tools, cloud development environments, and XR applications for warehouse management. The lab maintains strong industry partnerships with technology clusters in Thessaloniki and participates in the Eclipse Foundation ecosystem.

Visa VallivaaraView profile

Researcher

• Cryptography
• Post-quantum cryptography
• Quantum cryptography
• +3 more

Visa Vallivaara serves as Master of Science Research Team Leader at VTT Technical Research Centre of Finland, heading the BA6410 CryptoLab. His research directly contributes to cybersecurity advancements under UN Sustainable Development Goals, with expertise spanning post-quantum cryptography, quantum-safe systems, and blockchain security. Research Interests: Vallivaara's work centers on cryptographic resilience against quantum computing threats, specializing in lattice-based signature algorithms and hybrid quantum-classical optimization. His fingerprint analysis reveals dominant expertise in algorithms (100%), cryptography (96%), and quantum cryptography (54%), with significant contributions to blockchain (54%) and security protocols (55%). This positions him at the forefront of Finland's national quantum-safe transition efforts. Publication Trends: Recent outputs (2022-2025) demonstrate a clear trajectory from theoretical foundations to practical implementation. His work bridges NIST PQC standardization with developer adoption challenges, featuring combinatorial optimization frameworks and cryptographic metrics for real-world systems. The 2025 poster on hybrid quantum-classical algorithms represents the cutting edge of his current research direction. Scientific Awards: CyCon 2015 Student Award (2nd place) for cybersecurity research innovation Advising and Grants: Vallivaara has supervised 2 research projects and currently leads Business Finland-funded initiatives including BLimPQC (2025-2028) and Secur-e-Health (2023-2025). His grant portfolio reflects strategic focus on quantum-safe communication requirements and practical implementation frameworks, with active collaboration across Finnish research and industry sectors. Labs and Teams: As leader of BA6410 CryptoLab at VTT, Vallivaara directs Finland's specialized research unit for post-quantum cryptography. The lab produces both theoretical frameworks (e.g., cryptographic metrics) and applied tools (e.g., LOAP blockchain auditing system), maintaining strong connections to national cybersecurity infrastructure development through Business Finland partnerships.

• Acoustics
• Sound-Based Interactions
• Human-Computer Interaction
• +5 more

Professor Gianluca Memoli is an Associate Professor in Sound-Based Interactions within the Department of Informatics at the University of Sussex's School of Engineering and Informatics. He also serves as Impact Leader for Informatics since June 2023. His academic profile bridges fundamental acoustics research with practical applications and commercialization. Memoli's research focuses on acoustic metamaterials and sound-based interactions, exploring how techniques previously used only for light can be applied to sound. His work spans from fundamental physics of bubbles and cavitation to advanced applications in healthcare, environmental monitoring, and human-computer interaction. He approaches acoustics through an interdisciplinary lens, connecting physics, engineering, materials science, and perception studies. His recent publications (2022-2025) demonstrate consistent output in high-impact acoustics journals, with a clear trajectory toward practical applications of acoustic metamaterials. Key themes include acoustic lens design, sound field manipulation, and the development of tools for virtual acoustic assessment. His work shows increasing emphasis on addressing real-world challenges in environmental noise and healthcare applications. Memoli has secured significant research funding from diverse sources including EPSRC, NERC, Royal Society, and European Union programs. His current major project 'Visualising the Perception of Aircraft Noise for Communities Surrounding Airports' (2023-2027) exemplifies his focus on applying advanced acoustic research to societal challenges. As an educator, Memoli teaches 'Professional Skills' and 'Entrepreneurship' courses, reflecting his dual expertise in technical acoustics and commercialization. His role as CEO of Metasonixx since 2019 demonstrates his commitment to translating academic research into real-world applications, creating a unique bridge between his academic and entrepreneurial pursuits.

Michał WójcikView profile

Lecturer

• Software Engineering
• High Performance Computing
• Environmental Informatics
• +3 more

Michał Wójcik serves as Assistant Lecturer in the Department of Computer Systems Architecture within the Faculty of Electronics, Telecommunications and Informatics at Gdańsk University of Technology. Concurrently, he holds a technical role as Senior Specialist – Design Programmer in the Team for Development and Maintenance of Central University Systems (CUI), operating from Building A of the Faculty (room 523) with contact number 583471867. His research bridges computer science with environmental and business applications, focusing on Software Engineering (RESTful systems, Jakarta EE), High Performance Computing (parallel application simulation), and Environmental Informatics (marine forecasting, benthic habitat mapping). Key projects include the FindFISH numerical forecasting platform for fisheries and MERPSYS simulation environment for HPC systems, demonstrating strong interdisciplinary collaboration. Analysis of his 2017-2024 publications reveals evolving expertise from core HPC simulation toward applied environmental informatics, with recent work emphasizing open innovation competence profiling and marine ecosystem modeling. His publications consistently address real-world problems through computational solutions, particularly in Baltic Sea environmental monitoring and multi-partner innovation ecosystems.