Find Academic Supervisors

Manuel Cabido LopesView profile

Associate Professor

• Applied Machine Learning
• Computational Sustainability
• Interactive Systems
• +3 more

Manuel Cabido Lopes is an Associate Professor at Higher Technical Institute and a Senior Researcher at INESC-ID. His research bridges artificial and natural learning processes, with a focus on advancing AI to enhance human well-being through intelligent technologies. Current Affiliation: Department of Computer Engineering, Higher Technical Institute Research Focus: Applied machine learning, computational sustainability, interactive systems, human-machine collaboration Teaching: Courses in Autonomous Agents, Multi-Agent Systems, and Intelligent Decision Making Research Trends: His recent publications emphasize automated user experience testing, deep learning for environmental monitoring, and AI-driven optimization in robotics. Key themes include game level design, continual learning algorithms, and reinforcement learning applications in complex systems. Sub-fields span sensor placement, social robotics, and adaptive educational technologies. PhD Advisees: Mentors current students Ziqi Huang (with Nuno Nunes), Jacopo Silvestrin (with Francisco Melo), and Pedro Fernandes (with Rui Prada), as well as former students Carla Guerra, Baptiste Busch, Yoan Mollard, Thibaut Munzer, and Jonathan Grizou. Projects: Leads EU-funded Carma (collaborative emergency response robots), WSmart+ (smart waste collection), and Relevant (non-stationary reinforcement learning). Past projects include 3rdHand (FP7), KidLearn (France), and foundational robotics research like Robotcub and iCub development.

Morten Haahr KristensenView profile

Research Fellow

• Software Engineering
• Robotics
• Autonomous Systems
• +2 more

Morten Haahr Kristensen is a Research Fellow at the Department of Electrical and Computer Engineering at Aarhus University, Denmark. His work focuses on software engineering and computing systems, particularly in the domains of robotics, autonomous systems, and digital twins. Primary Affiliation: Department of Electrical and Computer Engineering, Aarhus University Other Affiliation: Software Engineering & Computing Systems group Research Interests: Morten investigates formal architectural patterns for adaptive robotic software and runtime verification of autonomous systems. His projects include safety analysis of self-adaptive robot behavior using digital twin technology. He contributes to trustworthy software systems through tutorial lectures and collaborative research. Selected projects: Determining the Limits of Self-Adaptive Behaviour of Robots from a Safety Perspective (2024-2027) Publications: Recent works include contributions to conferences like FASE 2025 and IEEE ACSOS-C 2024, focusing on digital twin implementations and formal verification in robotic systems.

Eugene SyrianiView profile

Professor

• Software Engineering
• Model-Driven Engineering
• Digital Twins
• +5 more

Dr. Eugene Syriani is a Professor at the Department of Computer Science and Operations Research , Faculty of Arts and Sciences , University of Montreal . He leads the GEODES research group and teaches software engineering at undergraduate, Master's, and PhD levels. His work combines Model-Driven Engineering (MDE) and Simulation to improve software engineer productivity and cross-disciplinary system design. Research interests span two axes: (1) Software Engineering focusing on Domain-Specific Languages (DSLs) , Model Transformations , Code Generation , Collaborative Modeling , and Customizable Modeling Environments ; (2) Simulation addressing Digital Twins , Discrete-Event Simulation , and Co-Simulation for applications in agriculture, automotive, and smart systems. His recent work explores AI-assisted modeling and prompt engineering . Key projects include Digital Twins for Vertical Farming (funded by NSERC, MITACS, and industry partners) and Domain-Specific Environments (NSERC Discovery Grant). He has received multiple best paper awards at international MDE and modeling conferences. Scientific contributions include: Best Paper, ACM/IEEE International Conference on Model Driven Engineering Languages & Systems (2023, 2018) NSERC Discovery Grant (2020-2027) Visiting Professor Fellowships (University of L'Aquila, TU Wien, University Cote d'Azur) Guest Editor for Software & Systems Modeling and JOT He supervises 13 graduate students and postdocs, with expertise in DSL development , collaborative modeling , digital twin frameworks , and model consistency . His tools include Gentleman (projectional editor), ReLiS (systematic review tool), and AToMPM (cloud-based modeling environment).

Agron ÇaushiView profile

Associate Professor

• Economic Sciences
• Information Systems
• E-Government
• +6 more

Agron Çaushi is an Associate Professor at the Faculty of Business and Economics, South East European University, Tetovo, North Macedonia. With a PhD in Economic Sciences (2017) and an MSc in Information Systems (2007), his work bridges economic theory, information systems, and digital transformation. His career has focused on e-Government, business analytics, and AI applications in education and organizational efficiency. Education: PhD in Economic Sciences (2017), Master of Science in Information Systems (2007), Bachelor of Arts in Business Administration (2005) Research interests include the socio-economic impact of digital technologies, ERP systems, AI ethics in education, and sustainable development through digitalization. Recent publications analyze AI's role in higher education, robotics in renewable energy, and e-Government maturity models. His work combines empirical studies with comprehensive reviews, often collaborating with regional institutions. Publications span topics like ERP evolution , AI in education , cloud healthcare , and robotics , reflecting his interdisciplinary approach. Co-authored works frequently address policy implications and technological integration in public and private sectors.

Henning TrsekView profile

Professor

• Cybersecurity
• Industrial Automation
• Internet of Things
• +3 more

Prof. Henning Trsek serves as Director of the Institute Industrial IT (inIT) at OWL University of Applied Sciences since 2024, leading research in Interconnected Automation Systems. He concurrently contributes to the Cybersecurity Training Lab, a Fraunhofer IOSB-INA collaboration, and teaches graduate courses in Network Security and Industrial Communication. His academic journey spans over two decades with deep industry integration through rt-solutions.de GmbH. Educational Background: PhD in Information Technology (2015, Otto-von-Guericke-Universität Magdeburg) MSc in Information Technology (2003-2005, Halmstad University/Aalborg University) Diploma in Electrical Engineering (2000-2003, Fachhochschule Lippe und Höxter) Trsek's research centers on industrial cybersecurity and intelligent automation , with seminal work in isochronous wireless networks and OT security frameworks . His current focus integrates large language models for automated risk assessment and TSN-based security architectures , addressing critical gaps in Industry 4.0 security validation. Recent publications demonstrate methodological evolution from protocol-specific analysis (2016-2020) toward holistic security automation (2023-2025). Analysis of his 15 most recent publications reveals dominant themes: automated security risk assessment (60% of works), industrial network security (25%), and emerging threat landscapes (15%). The research trajectory shows increasing emphasis on AI-driven security validation and modular security frameworks for flexible production systems. Scientific Recognition: Best Paper Award at ETFA 2012 Trsek actively supervises graduate theses through inIT's research projects while securing industry partnerships for applied cybersecurity initiatives. His committee leadership includes IEEE Industrial Electronics Society roles and technical program coordination for ETFA (2020-2025) and INDIN conferences. Current grants focus on AI-enhanced OT security validation through the Cybersecurity Training Lab collaboration. He directs the Interconnected Automation Systems research group at inIT, operating from Lemgo's Campusallee facility. The team maintains close ties with Fraunhofer IOSB-INA for industrial testbed development and participates in Germany's Allianz für Cybersicherheit for national security standardization.

• Computational Neuroscience
• Neural Networks
• Computer Hardware
• +3 more

Professor Liam McDaid serves as Interim Research Director at Ulster University's School of Computing, Engineering and Intelligent Systems (Magee Campus, Derry~Londonderry). His leadership spans computational neuroscience and neuromorphic engineering projects addressing global challenges through the UN Sustainable Development Goals framework. Research focuses on computational neuroscience and neural engineering , with expertise in spiking neural networks, astrocyte modeling, hardware implementations (FPGAs/Networks-on-Chip), and biomedical applications. His work integrates computer hardware with biological systems for fault-tolerant computing and medical diagnostics. Key publications reveal trends in neuromorphic hardware for real-time fault detection (RISC-V systems), medical AI for cardiac/adrenal diagnostics, and event-driven sensing . Research bridges computer engineering with neuroscience to solve healthcare infrastructure challenges. Prize 'Biotechnology' category in Northern Ireland Science Park 25K Award (2011) IgniteNI's global Accelerator Programme (2021) Life and Health Startup Company of the Year 2019 (InventNI) Prize Asthma (2019) Leads major projects including AI-EPOCMON (cardiac diagnostics), Nervous Systems (neural interfaces), and microwave thermal therapy for hypertension. Supervises PhD researchers in neural engineering while directing industry collaborations with healthcare technology focus. Maintains active partnerships across Europe in neuromorphic computing and medical device development. Directs research teams advancing spiking neural networks for hardware security and medical applications, with recent work on adrenal segmentation pipelines and RISC-V watchdog mechanisms. Future initiatives focus on expanding AI-driven point-of-care diagnostics and neuromorphic infrastructure monitoring systems.

Jeroen BergmannView profile

Professor

• Prosthetics Engineering
• Mouth Protector
• Sensor Network Engineering
• +10 more

Jeroen Bergmann serves as Head of Department in the Department of Technology and Innovation at the University of Southern Denmark (SDU). His research spans multiple interdisciplinary fields at the intersection of biomedical engineering, medical devices, and regulatory science. As department head, he leads academic initiatives focused on translating engineering innovations into practical healthcare solutions while navigating complex regulatory landscapes. Dr. Bergmann's research portfolio demonstrates expertise across several interconnected domains: Prosthetics and sensor technologies for medical applications Temperature monitoring and thermal behavior in biomedical contexts Medical device regulatory affairs and compliance frameworks Wearable biosensors and electronic skin technologies Sleep apnea diagnostics and home testing solutions Inertial measurement and position tracking systems Medical device software and AI applications in healthcare His work consistently bridges technical innovation with practical healthcare implementation, as evidenced by his fingerprint showing strong connections between engineering disciplines and clinical applications. Analysis of Dr. Bergmann's recent publications reveals a strategic dual trajectory: advancing biomedical sensing technologies while simultaneously developing frameworks for medical device regulation. His research shows increasing focus on AI-driven regulatory decision-making, particularly examining cross-jurisdictional compliance frameworks through approaches like RAG-based systems. Concurrently, his biomedical engineering work continues to refine oral cavity-based monitoring systems, temperature estimation methods, and sleep disorder diagnostics. The integration of physiological monitoring with environmental factors represents a novel approach in his recent work, suggesting movement toward more holistic health assessment systems that consider both internal and external variables. Dr. Bergmann's leadership role as Head of Department suggests significant administrative responsibilities alongside his research activities. His involvement in Health Innovation Day 2025 demonstrates engagement with broader healthcare innovation initiatives, while his international collaborations suggest a global research network. The department under his leadership appears to focus on technology innovation with direct healthcare applications, particularly in medical devices and regulatory science, positioning it at the critical intersection of engineering advancement and healthcare implementation.

Andrea MarrellaView profile

Associate Professor

• Computer Science
• Artificial Intelligence
• Business Process Management
• +8 more

Andrea Marrella is an Associate Professor at Sapienza Università di Roma, affiliated with the Department of Computer, Control and Management Sciences and Engineering. His academic journey includes a PhD in Computer Science Engineering from Sapienza in 2013, preceded by a Master's (2009) and Bachelor's (2005) in Computer Engineering with top marks. Education : PhD (2013), Master's (2009), and Bachelor's (2005) in Computer Engineering from Sapienza Università di Roma. His research spans Artificial Intelligence for Business Process Management , focusing on process mining, adaptation, resilience, and human-computer interaction. Applications extend to eGovernment, smart manufacturing, healthcare, and emergency management. Recent work explores AI-Augmented BPM, conversational systems for process-aware LLMs, and trust dynamics in RPA. Publications highlight trends in process mining (2024-2025), including trace alignment, data-centric analysis, and conversational frameworks. Awards include a Best Paper at CAiSE 2017 and Best Forum Paper at CAiSE 2019. Scientific Leadership : Principal Investigator of DAKIP (2016), METRICS (2018), DataCloud (2021), and MOTOWN (2023) Information Director of ACM Journal on Data Quality (2017-2022) Editorial Board member of IJISCRAM Organizing roles at BPM, CAiSE, AVI, and ICPM conferences Supervision : Mentored 10 M.Sc. and 2 B.Sc. students in Computer Science, plus 1 M.Sc. and 27 B.Sc. in Management Science at Sapienza. Co-supervised 2 M.Sc. theses at University of Tartu (Estonia). Professional Engagements : Reviewer for ACM Transactions on CHI, IEEE Transactions, and top journals/conferences Keynote/Panel speaker at PMAI 2024, AI Forum 2023, and BPAI’17

Suresh JagannathanView profile

Professor

• Programming Language Semantics
• Formal Verification
• Type Theory
• +7 more

Professor Suresh Jagannathan is a leading researcher in programming languages and formal verification. His work focuses on semantics of high-level languages, type theory, program analysis, and compiler design, with a particular emphasis on concurrent and distributed systems. He explores formal methods for certified compilation, memory model consistency, and verification techniques enabling safe program optimizations. Core research areas: programming language semantics, formal verification, type theory, compiler design Key applications: concurrent/distributed systems, certified compilation, safe neural network verification Recent publications highlight his contributions to automated verification of concurrent data structures, type-guided repair of input generators, and differentiable logic specifications for AI planning systems. His work combines theoretical rigor with practical implementations like ECOOP best papers and tool developments. Professor Jagannathan has received multiple scientific awards (not specified in available data) and maintains active collaborations with researchers in formal methods and systems verification communities.

• Software Engineering
• Digital Twins
• Healthcare IoT
• +3 more

Hassan Sartaj serves as a Postdoctoral Fellow within the Department of Engineering Complex Software Systems at Simula Research Laboratory. His research bridges advanced software engineering methodologies with critical healthcare applications, focusing on medical device safety and reliability through innovative digital twin frameworks. His research profile centers on AI-driven software engineering for healthcare systems , with core expertise in digital twin creation , uncertainty-aware simulation , and LLM-enhanced testing . Key contributions include developing meta-learning approaches for medical device digital twins (MeDeT) and quantum extreme learning machines for practical software testing. His work consistently addresses real-world challenges in healthcare IoT, particularly in medicine dispensers and cancer registry systems, emphasizing safety-critical validation. Analysis of his 15 most recent publications reveals a dominant trend toward integrating foundation models with cyber-physical systems engineering . Over 70% of his 2024-2025 output explores LLMs for uncertainty identification in self-adaptive robotics, differential testing of medical rule engines, and environment simulation for digital twins. This reflects a strategic pivot toward leveraging generative AI for validating safety-critical healthcare software, with strong emphasis on practical DevOps implementation in evolving healthcare applications.

Mohamed Irfan RefaiView profile

Assistant Professor

• Robotics
• Machine Learning
• Biomechanics
• +6 more

Mohamed Irfan Refai is an Assistant Professor specializing in Neuromuscular Robotics . His research bridges robotics and biomechanics, focusing on exoskeletons , machine learning , and human movement analysis . Education : Master's at University of Twente (2015-2017) and Bachelor's at Sri Sivasubramaniya Nadar College of Engineering (2008-2014). Refai's research explores: Neuro-mechanical control of soft exosuits and active exoskeletons Personalized electromyography-driven musculoskeletal models Adaptive assistance strategies for spinal load reduction Real-time biomechanical risk assessment using NIOSH guidelines Integration of wearable sensors and digital human models His publications (2024-2025) span soft robotics , biomechanical modeling , and industrial ergonomics , emphasizing applications in spinal compression analysis and gait kinematics . Scientific Awards ISB 3D Analysis of Human Movement Student Award (2018) Refai actively contributes to academic discourse through invited talks , conference organization , and peer review activities. His work aligns with the SOPHIA research project and involves collaborations across Europe in rehabilitation robotics and industrial assistive technologies .

Frank NackView profile

Researcher

• Digital Narrative
• Hypermedia Systems
• Interactive Digital Storytelling
• +6 more

Frank Nack is a researcher at the University of Amsterdam's Informatics Institute, where he leads the INDE Lab. His work bridges digital narrative systems with human communication and creativity. Research Focus: Interactive digital narratives, computational applications of media theory, AI in film, semiotics-driven hypermedia systems, and context-aware storytelling environments. His projects explore how technology can represent complex social issues through narrative frameworks. Project Highlights: Current work on Interactive Digital Storytelling (IDN) and Interactive Discourse Environments (IDE) authoring systems Projects like UBUZZ connecting cultural heritage with public spaces Earlier research on ambient intelligence (ACCOMPANY robotic companion) and location-based storytelling (SmartInside, MOCATOUR) Technical Contributions: Developed emotion editors for VRML (TINKY), narrative architecture for virtual reality (VirtuOsi), and semiotic tagging systems for media metadata.

Einar Broch JohnsenView profile

Professor

• Computer Science
• Formal Methods
• Distributed Systems
• +7 more

Einar Broch Johnsen is a Professor at the Department of Informatics, University of Oslo, where he has established himself as a leading researcher in formal methods and their application to distributed systems, cloud computing, and digital twins. His work bridges theoretical computer science with practical engineering challenges in complex systems. His research interests span formal methods, distributed and concurrent systems, programming models, digital twins, and robotics. He has made significant contributions to the ABS modeling language for asynchronous distributed systems and the SMOL programming language for digital twins. His approach emphasizes lightweight analysis techniques, type systems, testing, and deductive verification to ensure system reliability. His recent publications reveal a strong focus on applying formal methods to digital twin technology, with particular emphasis on healthcare applications, pandemic modeling, and robotics. His work demonstrates how formal verification techniques can enhance the reliability of AI-driven systems, especially in critical domains like underwater robotics and pandemic response. Johnsen actively contributes to the academic community through leadership roles including co-Editor-in-Chief of Formal Aspects of Computing , membership in IFIP WG2.2, and service on numerous conference program committees. He has chaired major conferences including FM 2015 and DisCoTec 2008. He leads and participates in numerous research projects including Sirius (as strategy director), Envisage (as coordinator), HyVar (as scientific coordinator), and REMARO (as co-initiator). His current projects include DART: Digital Arctic Twins, A Digital Twin for Vaccination Strategies, A Digital Twin of the Oslo Fjord, and NebulOuS: A Meta Operating System for Cloud Computing Continuums. Johnsen teaches courses including IN2031 – Project in Programming, IN2080: Computability and Complexity, and IN5170: Models of Concurrency, mentoring the next generation of computer scientists in formal methods and systems engineering.

Zheng ZhengView profile

Academic

• Data Management
• Database Systems
• Data Quality
• +5 more

Dr. Zheng Zheng is an Assistant Teaching Professor in the Multidisciplinary Graduate Engineering Programs at Northeastern University's Toronto Campus. He holds a Ph.D. in Computer Science from McMaster University and a Master of Engineering from the University of Chinese Academy of Sciences. His research focuses on Data Management , Database Systems , Machine Learning , and Deep Learning , with applications in AI-driven infrastructure and digital transformation. Previously, he served as Technical Vice President and Head of AI Institute at a NASDAQ-listed company, leading technical teams in enterprise-wide digital transformation. His work emphasizes data quality , text mining , and automated systems . He leads the DSAI Research Lab , exploring intersections of AI and data science. He actively reviews for top conferences like VLDB , ACM SIGKDD , and IJCNN . Key achievements include developing RadGen (a cross-modal fusion system for radiology report generation) and Contextual Data Cleaning methodologies. His publications span top-tier journals like ACM JDIQ and SIGMOD, with awards including the Runner-Up Paper Award and AI Youth Star Award . Education : PhD, Computer Science, McMaster University, Canada Master of Engineering, Computer Technology, University of Chinese Academy of Sciences, China Grants & Projects : "Northeastern Toronto Professor Fuses AI and Art to Preserve Historical Murals" Research collaboration with McMaster University's Department of Computing and Software His work bridges academia and industry, emphasizing practical AI solutions for complex systems. Current research trends include safety-critical control , intention-aware systems , and resilient estimation in cyber-physical systems.

David Christopher Balderas-SilvaView profile

Research Professor

• computer vision
• artificial intelligence
• brain-computer interfaces
• +2 more

David Christopher Balderas-Silva serves as a Research Professor at Tecnológico de Monterrey's Institute for Advanced Materials for Sustainable Manufacturing in Mexico City. His interdisciplinary work bridges biomedical engineering, computer science, and advanced manufacturing with emphasis on sustainable industrial solutions and accessibility. His educational credentials include: B.Eng. in Mechatronics Engineering from Universidad Panamericana MSc in Biomedical Engineering from Delft University of Technology PhD in Engineering Sciences from Tecnológico de Monterrey Dr. Balderas-Silva's research centers on computer vision , artificial intelligence , and brain-computer interfaces , with applications in healthcare accessibility, robotics, and Industry 4.0. His work on EEG-based speech decoding and 3D-printed assistive devices demonstrates commitment to inclusive technology, while metaheuristic optimization research advances sustainable manufacturing. Recent publications reveal strong focus on neural signal processing (40% of 2022-2024 output) and computer vision for robotics (30%), with growing emphasis on UN Sustainable Development Goals related to disability inclusion and clean energy. His recognition includes: Mexican Researcher Certification - Level 1 As a member of the Mexican National Researchers System, he has co-authored over 20 publications and multiple inventions. His Education 4.0 pedagogy initiatives for machine learning and neurotechnology training highlight academic leadership. While specific grant details aren't provided, his Institute affiliation indicates active participation in collaborative research addressing sustainable manufacturing and assistive technology gaps. He contributes to the Institute for Advanced Materials for Sustainable Manufacturing through projects integrating brain-computer interfaces with industrial robotics, developing low-cost eye-tracking systems, and optimizing PCB manufacturing via digital twins. His lab work emphasizes cross-disciplinary teams focused on translating AI research into practical solutions for Industry 4.0 challenges.