Find Academic Supervisors

Alisha PradhanView profile

Assistant Professor

• Assistive Technology
• Human-Computer Interaction (HCI)
• Aging in Place
• +5 more

Alisha Pradhan is an Assistant Professor in the Informatics department at the New Jersey Institute of Technology (NJIT). Her research focuses on human-centered design of technologies for older adults and people with disabilities, emphasizing accessibility, inclusivity, and ethical considerations. She holds a Ph.D. in Information Studies from the University of Maryland-College Park (2022), an M.S. in Human-Computer Interaction (2018), and a B.Tech. in Industrial Design from National Institute of Technology (2015). Research Interests: Dr. Pradhan's work spans assistive technologies, voice interaction design for aging populations, inclusive AI systems, and participatory design methodologies with marginalized communities. Her current projects investigate the use of smart objects and voice assistants to support cognitive aging, while addressing challenges in technology adoption and ethical implications. She also explores sustainable makerspace models for older adults and co-design approaches with people living with dementia. Publications: Her recent work addresses voice assistant personalization for seniors, accessibility of smart home technologies, and frameworks for equitable AI development. Key topics include: ontological categorization of voice agents, multimodal interaction for memory support, and posthumanist perspectives in technology design. Grants & Awards: Active research funding includes NSF-supported projects exploring future-proofing smart technologies for age-related cognitive changes. She has developed curriculum modules integrating accessibility principles into design education. Labs & Collaborations: Maintains an active research website (https://www.alishapradhan.net/) documenting her work. Her lab collaborates with geriatric care organizations and technology firms to translate research into practical solutions for aging-in-place scenarios.

Nikos SpanoudakisView profile

Assistant Professor

• Multi-Agent Systems
• Artificial Intelligence
• Agent-Oriented Software Engineering
• +11 more

Nikos Spanoudakis is an Assistant Professor at the Department of Electronic Engineering of Hellenic Mediterranean University , with concurrent research collaboration at Technical University of Crete . He holds a PhD in Computer Science (Artificial Intelligence) from Paris Descartes University (2009, "Très Honorable"), an MSc in Organization and Administration from Technical University of Crete, and a Diploma in Computer Engineering and Informatics from University of Patras. Research Focus: Multi-Agent Systems (AOSE, Computational Argumentation), Model-Driven Engineering , Smart Buildings , IoT , and Artificial Intelligence Applications in Ambient Intelligence, Finance, and Education Key Contributions: Created ASEME Methodology and AMOLA Language for agent modeling, developed Gorgias-B argumentation framework, and designed Kouretes Statechart Editor for robotic behavior specification His recent publications reveal a strong trend in Explainable AI (2023: Explainable Argumentation as a Service ), Smart Energy Systems (2025: Engineering IoT-Based Open MAS for Large-Scale V2G/G2V ), and EdTech Innovations (2024: Role Assignment in Programming Courses ). He has received prestigious ACM Senior Member (2023) and IEEE Senior Member (2012) distinctions, along with teaching recognition (2021) from Technical University of Crete. Academic Leadership: Serves as Editor for Springer Nature's Computer Science journal and has reviewed for 15+ top-tier publications including IEEE Intelligent Systems and Journal of Web Semantics Conference Involvement: Program Committee Member for 20+ international conferences (IJCAI, ECAI, AAMAS, AAAI) and organizer of multiple European Agent Systems Summer Schools

Donciu CodrinView profile

Professor

• Signal Processing
• Image Processing
• Earthquake Early Warning Systems
• +3 more

Prof. Donciu Codrin is a full professor at the Department of Electric Power Engineering, Technical University of Iasi. His research spans interdisciplinary fields including signal processing, image processing, earthquake early warning systems, and textile engineering. He leads projects on seismic response analysis using uniaxial shaking tables, non-invasive eye safety systems (e.g., Opto-Guard), and ESD-protective textiles. His work integrates hardware design (e.g., electrodynamic actuators) with advanced algorithm development for applications like video-based distance measurement and apparel sizing estimation. Research projects include: Signal Processing : OFDM modulation, DFT/FFT algorithms, and seismic waveform analysis Computer Vision : Pattern recognition, 3D reconstruction, and human-centric interface design Structural Engineering : Earthquake simulation platforms and early warning system validation Textile Innovation : Conductive fabric development for ESD protection and functional garments Recent publications focus on seismic wave analysis (2023–2025), optoelectronic safety systems (2022), and ultrasonic sensing technologies (2020–2021). His work bridges theoretical signal processing with real-world applications in disaster preparedness and ergonomic design.

Markos KonstantakisView profile

Research Fellow

• Augmented Reality
• Virtual Reality
• Digital Culture
• +7 more

Markos Konstantakis is a PhD candidate at the Department of Cultural Technology and Communication, University of the Aegean, focusing on Augmented Reality (ACUX thesis). He holds a Master’s in Information Systems from the Hellenic Open University and degrees in Marine Mechanical Engineering from NTUA. As a Research Fellow-Lecturer at the University of Athens, he teaches courses like Network Engineering, MATLAB, and Digital Culture under the e-learning program. He also works as a Research Assistant at Panteion University under the ELKE research fund. His research spans Virtual/Augmented Reality, Digital Culture, Cultural Heritage Management, and Human-Computer Interaction. Key research interests include: Development of digital twins for cultural spaces using photogrammetry and laser scanning Augmented Reality applications for cultural tourism and education Personalized visitor experiences through frameworks like ACUX and AI-driven recommendation systems Integration of IoT and serious games in cultural heritage preservation His recent work emphasizes: Smart Glasses for cultural heritage navigation OpenLab initiatives for archaeological conservation (e.g., Ancient Tiryns) Recommender systems leveraging LLMs like ChatGPT for museums Design of mobile interfaces for cultural tourism optimization Collaborations include projects like TRACCE (content personalization), CHATS (tangible interfaces), and TRIPMENTOR (gamification in tourism). His contributions bridge technological innovation with cultural preservation, emphasizing user-centric design approaches.

• Cloud Computing
• 3D Video Processing
• Mobile Computing
• +3 more

Katerina Papanikolaou is an Associate Professor in the Department of Computer Science and Engineering at the European University Cyprus, located in Nicosia. She holds a PhD in Electronic and Electrical Engineering from University College London (2001) and a Bachelor of Science in Physics from Imperial College of Science, Technology and Medicine (1993). Her academic roles include program coordination for the Computer Science program (2008-2019) and membership in faculty selection committees. Her research focuses on cloud computing, mobile networks, and ambient assisted living technologies. Notable projects include EU-funded initiatives like ICT Cost Action CA16226 (2017-2021) for elderly care environments and ICT COST Action IC1303 (2014-2017) for enhanced living environments. She has contributed to over 20 peer-reviewed publications, emphasizing optimization of resource migration in 3D video processing and energy-efficient mobile cloud systems. Prof. Papanikolaou actively participates in IEEE committees, serving as Cyprus Section Vice Chair (2018-2019) and Secretary (2016-2018). Her work integrates interdisciplinary approaches combining machine learning, wireless networks, and healthcare applications to address modern computational challenges.

Frits de NijsView profile

Research Fellow

• Artificial Intelligence
• Renewable Energy Systems
• Reinforcement Learning
• +3 more

Frits de Nijs is a Research Fellow in the Department of Data Science & AI at Monash University. His work focuses on advancing artificial intelligence techniques for energy systems optimization, multi-agent decision-making, and sustainable infrastructure. He has contributed to projects such as the Human-in-the-loop Microgrid Project and RACE for 2030 CRC, addressing challenges in renewable energy integration and smart grid management. Key research areas include reinforcement learning applications for energy curtailment, HVAC control systems, and resource-constrained multi-agent planning. His projects often bridge AI methodologies with real-world energy challenges, aiming to enhance grid reliability, carbon efficiency, and fair resource allocation. Notable collaborations involve researchers in machine learning, sustainable energy, and building automation. He has actively participated in 6 major research projects since 2020, including initiatives on AI-ready buildings and probabilistic multi-agent learning environments. His publications span conferences like AAAI, NeurIPS, and IEEE Power & Energy Society events, emphasizing peer-reviewed contributions to energy-AI intersections.

Mika MäntyläView profile

Professor

• Software Engineering
• Software Testing
• Software Log Analysis
• +3 more

Mika Mäntylä is a Professor at the Department of Computer Science, University of Helsinki, affiliated with the Faculty of Science. His research focuses on software engineering, testing, log analysis, and systematic literature reviews. He leads projects such as CRITICAL (cultivating critical reading in the internet era) and a microservice anomaly detection initiative funded by the Academy of Finland. His work spans technical domains like software log anomaly detection, meta-learning applications, and social media credibility evaluation. Notable tools include Credtwi (a browser plugin for credibility assessment) and LogLead (a log analysis system). Key grants include SRC Strategic Research Council funding (2023–2026) and Academy Project funding (2023–2026). Mika’s research bridges technical and societal challenges, addressing software quality, automated anomaly detection, and user-centric credibility evaluation. His publications often emphasize empirical methods, tool development, and interdisciplinary approaches.

Carlo MenonView profile

Professor

• Wearable Technology
• Electronic Textiles (E-textiles)
• Bio-signal Processing
• +4 more

Prof. Carlo Menon is a Full Professor and Head of the Biomedical and Mobile Health Technology Lab at ETH Zürich. His expertise spans wearable technology, e-textiles, and bio-signal processing for healthcare and sports applications. He holds a Laurea in Mechanical Engineering and a PhD in Space Sciences from the University of Padua, with prior roles at Carnegie Mellon University and Simon Fraser University. His lab focuses on next-generation wearables for personalized medicine and neuromuscular rehabilitation. Prof. Menon has secured over 80 grants and published 400+ works, co-founding two startups to commercialize his research. Education: Laurea in Mechanical Engineering, University of Padua PhD in Space Sciences and Technologies, University of Padua Research Interests: His lab develops innovative materials for e-textiles, computational methods for bio-signal analysis, and wearables for sports and medical monitoring. Key projects include motion tracking via triboelectric textiles, privacy-preserving health sensors, and stroke rehabilitation technologies. His work bridges engineering and clinical needs, emphasizing translational research. Awards & Recognition: Tier I Canada Research Chair CIHR and MSFHR Career Awards Advising & Grants: As lab head, he oversees 40+ researchers in the Menrva Group. His funding portfolio includes competitive grants totaling over CHF 8 million, supporting projects in wearable energy harvesting and clinical validation. Labs & Collaborations: Leads the ETH Zurich Biomedical and Mobile Health Tech Lab, collaborating with ESA and industry partners. His Menrva Research Group focuses on multi-disciplinary wearable tech solutions.

• Artificial Intelligence
• Smart Grids
• Machine Learning
• +5 more

Carlos Ramos is a researcher affiliated with the University of Porto's Faculty of Engineering and the Polytechnic Institute of Porto's GECAD Research Group. He holds a PhD in Electrical Engineering and Computers from the University of Porto (1993). His work focuses on AI applications in energy systems, ambient intelligence, and agent-based systems. Ramos has collaborated extensively with researchers like Zita A. Vale and Sabah Mohammed on projects involving smart grids, manufacturing optimization, and cyber-physical systems. Research Interests : His primary areas include artificial intelligence, smart grids, machine learning, agent-based systems, and ambient intelligence. Recent work emphasizes explainable AI models in building energy management and genetic algorithms for industrial scheduling. Publications : Ramos has over 138 publications spanning journals like Engineering Applications of Artificial Intelligence and IEEE Transactions on Intelligent Systems . Key themes include AI-driven energy optimization, IoT applications in smart cities, and multi-agent systems for market simulation. His work often bridges theoretical AI with practical industrial and healthcare applications. Labs/Teams : Active in the GECAD Research Group, focusing on intelligent engineering solutions. Collaborates with international partners on projects like the Mascem electricity market simulator and the ISEM agent-based marketplace.

• Crisis Management
• Simulation-Gaming Exercises
• Critical Infrastructure Resilience
• +5 more

Joeri Van Laere is a Professor of Informatics at the University of Skövde's School of Informatics. His research focuses on crisis management, simulation games, critical infrastructure resilience, and healthcare information systems. He has led multiple projects addressing payment system disruptions, self-service business intelligence challenges, and emergency response training. He coordinates courses in informatics and collaborates with municipalities and industries to develop practical solutions for real-world crises. Research Interests: Simulation-gaming for crisis training and resilience assessment Information systems development in healthcare and critical infrastructure User-centric design of self-service business intelligence tools Decision support systems leveraging distributed cognition Recent work emphasizes leveraging simulation games to bridge the gap between training and real-world crisis response. His articles highlight strategies for enhancing learning transfer through debriefing, mitigating cascading infrastructure failures, and improving situation monitoring systems. Ongoing projects include AI-driven healthcare prediction, drone protocols for crisis management, and GPS-based elderly safety systems.

Ira AssentView profile

Professor

• Machine Learning
• Data Mining
• Clustering Algorithms
• +5 more

Professor Ira Assent is affiliated with the Department of Computer Science at Aarhus University. Their research focuses on machine learning, data mining, and visualization, with applications in climate science, medical informatics, and computer vision. Professor Assent leads projects such as Light-IoT (analytics on compressed IoT data), WallViz (interactive visualization for massive datasets), and eData (anomaly detection in e-science). Their work emphasizes scalable algorithms, explainable AI, and interdisciplinary applications. Recent publications address rainfall prediction using deep learning, entity summarization via knowledge graphs, and efficient clustering techniques. Projects like RainAI demonstrate contributions to weather modeling and satellite data analysis. Collaborative efforts span academic and industrial domains, with a strong emphasis on practical, user-centric solutions. Selected research contributions include advancements in density-based clustering (e.g., AnyDBC, DISCO), parallel algorithms optimized for GPUs (HUNIPU), and visualization frameworks (AVID). Their work bridges theoretical computer science with real-world challenges, such as improving decision-making through interactive visualizations and enhancing medical information retrieval systems. Ongoing projects aim to address computational efficiency in large-scale data analytics while maintaining interpretability. Key areas of innovation include explainable AI (e.g., InteDisUX), climate modeling (DROPP), and hardware-accelerated algorithms (GPU-FAST-PROCLUS). These efforts reflect a commitment to advancing both foundational methods and applied technologies that impact diverse fields from environmental science to healthcare.

Taewon KangView profile

Researcher

• Computer Science
• Artificial Intelligence
• Computer Vision
• +5 more

Taewon Kang is a researcher at Korea University's Department of Computer Science, specializing in artificial intelligence, computer vision, and AI's intersection with digital art. His work includes novel view synthesis, GAN-based image translation, and emotion recognition systems. Key projects: Vender (AI vending machine with emotion analysis), Text2Story (text-guided video narratives), and GLEAN-ID (identity-preserving super-resolution). Collaborated with Prof. Ming-Hsuan Yang at UC Merced (2022–2023) and participated in workshops like ICCV 2019. Research focuses on: Generative AI (diffusion models, GANs) Human-AI interaction (emotion detection, empathy-driven systems) Creative applications of AI in art and education Recent article trends include: 3D priors for single-image synthesis (2024) Score-based stochastic modeling in Hilbert spaces (2023) Interactive AI for real-time translation (2020–2021) Scientific awards: Multiple competition wins (2014–2023) Two Korean patents (2016, 2018) 2017 Intel ISEF Finalist Part of the Temporary Artists team for the Play on AI exhibition (2020–2021), creating AI-driven artworks exploring empathy and connection.

• Medical Imaging Analysis
• Deep Learning
• Artificial Intelligence
• +5 more

Dr. Laith Alzubaidi is a postdoctoral researcher at the School of Mechanical, Medical and Process Engineering , Queensland University of Technology (QUT) , Australia. He earned his Ph.D. in 2022 in medical imaging analysis with deep learning from QUT and a master’s degree in computer science from the University of Missouri (2016), USA. His research interests span medical imaging analysis , deep learning , artificial intelligence , and computational mechanics . He has contributed to advancements in bone fracture detection , skin cancer classification , IoT security frameworks , and physics-informed neural networks , with a focus on data fusion , adversarial attack detection , and real-time diagnostic systems . Dr. Alzubaidi has published over 53 refereed papers, garnered more than 3,700 citations, and led two special issues in reputed journals. His work involves global collaborations and grants for deep learning in medical applications . He reviews for 53+ journals, including IEEE Transactions on Medical Imaging and Information Fusion . Scientific Awards : Scholarship during master’s degree (University of Missouri) QUT scholarship for Ph.D. His recent publications highlight trends in AI-driven medical imaging , secure IoT networks , and physics-informed computational models . He has also explored trustworthy AI , reinforcement learning in healthcare , and explainable machine learning frameworks .

Sergio Salinas MonroyView profile

Associate Professor

• Cyberphysical Systems
• Network Security
• Additive Manufacturing Security
• +6 more

Sergio Salinas Monroy is an Associate Professor at Wichita State University's College of Engineering, School of Computing. His research focuses on cyberphysical systems, network security, and privacy enhancement in critical infrastructures like additive manufacturing, power grids, and edge computing networks. He currently leads the Graduate Certificate in Information Assurance and Cybersecurity program and spearheaded the NSA/DHS CAE-CD designation for WSU. Academic Rank: Associate Professor Department: School of Computing University: Wichita State University Email: sergio.salinasmonroy@wichita.edu His research spans secure resource allocation in supply chains, cyberfraud investigation, and federated deep learning systems. Recent publications emphasize adversarial machine learning, intrusion detection, blockchain applications in manufacturing, and privacy-preserving algorithms. His work integrates deep learning, anomaly detection, and cryptographic protocols for industrial cybersecurity. Research trends in his articles include cyberphysical systems security (4 entries), privacy preservation in distributed networks (3 entries), and machine learning optimization for threat detection (5 entries). He also explores blockchain integration, edge computing economics, and energy-based attack detection in IoT-enabled systems. Professor Salinas Monroy actively contributes to academic service as an organizer and technical program committee member for IEEE conferences. His office hours are held in Jabara Hall (239) on Wednesdays from 3:30–5:00 PM.

James BernView profile

Professor

• Soft and Rigid Robotics
• Computational Design
• Numerical Simulation
• +3 more

James Bern is a Professor in the Computer Science Department at Williams College , currently on leave. He holds a PhD in Computer Science from ETH Zurich (2020), an MS in Robotics from Carnegie Mellon University (2017), and a BS in Mechanical Engineering with minors in Computer Science and Control & Dynamical Systems from Caltech (2015). His research spans soft and rigid robotics , computational design , and numerical simulation , with a focus on enabling artists, designers, and the public to utilize advanced robotics tools. Key questions include modeling unpredictable physical phenomena, optimizing design/control spaces, and democratizing robotic design. Recent publications highlight his work on soft drone grasping , virtual reality inverse kinematics , cable-driven stiffness modulation , and soft robot simulation . His collaborations include the Computational Robotics Lab at ETH Zurich and the Distributed Robotics Lab at MIT CSAIL.