Find Academic Supervisors

• Computational Neuroscience
• Robotics
• Machine Learning
• +3 more

Florentin Wörgötter is a faculty member at the Department for Computational Neuroscience , Georg August University of Göttingen, Germany. His research bridges robotics , computational neuroscience , and machine learning , focusing on action prediction, neural networks, and human-robot interaction. Key Research Areas : Action segmentation, semantic decomposition of manipulation sequences, 3D object reconstruction, and sensor fusion for infant movement classification. Recent Trends : Combining task-dependent learning with optimal path search, using foundation models for graph-based action recognition, and improving CNN interpretability through influence functions. He collaborates extensively with researchers like Minija Tamosiunaite , Tomas Kulvicius , and Poramate Manoonpong , contributing to journals such as NeuroImage , Robotics and Autonomous Systems , and IEEE Transactions on Neural Networks . His work often integrates deep learning , semantic reasoning , and biologically inspired models for robotic applications.

Tzu-Wei HungView profile

Professor

• Philosophy of Cognitive Science
• Philosophy of Language
• Philosophy of Artificial Intelligence
• +2 more

Tzu-Wei Hung is a Professor at the Institute of European and American Studies, Academia Sinica, Taiwan, since 2023. He serves as President of the Taiwan Philosophical Association (2024–2026) and has held roles as Assistant Research Fellow (2012–2017) and Associate Research Fellow (2017–2023) at the same institution. Education: PhD (2011) and MPhilStud (2007) in Philosophy from King’s College London; BA (1999) in Philosophy from National Taiwan University Academic Service: Editor-in-Chief for the Centennial Anthology of Taiwanese Philosophy Series (2018–present); Executive Editor of EurAmerica (2021–2022) Research Interests span: Philosophy of Cognitive Science Philosophy of Artificial Intelligence Taiwanese Philosophy Social Philosophy Philosophy of Language His article trends focus on predictive coding models, algorithmic fairness, cognitive warfare, and AI ethics. Collaborative works with Chun-ping Yen and others address equity, bias mitigation, and the intersection of technology with social policy. Scientific Awards include: Outstanding Research Award (2022–2023), National Science and Technology Council, Taiwan Special Outstanding Talent Award (2017–2023), Ministry of Science and Technology, Taiwan Taiwan Merit Scholarship (2005–2008), National Science Council, Taiwan

• RNA Processing
• Alternative Splicing
• Gene Expression Regulation
• +5 more

Sherif Abou Elela is a researcher affiliated with the University of Sherbrooke and its Centre de recherche du CHUS . His work focuses on RNA processing, stability, and alternative splicing, with implications in cancer biology and gene expression regulation. Education: Postdoctorate, University of California, Santa Cruz (1997) PhD in Biology, University of Guelph (1994) BSc, University of Qatar (1987) Research Interests: RNA processing and stability in gene expression, splicing program modulation in cancer and stress, snoRNA biology, yeast RNA metabolism, and RNA-binding proteins. He explores how RNA decay and splicing mechanisms can inform mammalian models and human disease diagnostics. Article Trends: Recent work emphasizes snoRNA annotation tools (e.g., SnoBIRD), stress-induced splicing adaptations (cells resist starvation), yeast RNase III roles in gene regulation, and cancer-specific non-coding RNA interactions (e.g., H/ACA snoRNAs). Computational approaches (snoDB, SAPFIR, snoGloBe) and yeast as a model organism are recurring themes. Patents & Contributions: He holds patents for methods to reprogram splice site selection and cancer biomarker discovery. He organized the Ribo Club conference, indicating leadership in RNA research.

• Philosophy of Artificial Intelligence
• Cognitive Science
• Neuroscience
• +3 more

Carlos Zednik is an Assistant Professor for Philosophy of Artificial Intelligence at Eindhoven University of Technology , affiliated with the Industrial Engineering and Innovation Sciences department. He leads the Eindhoven Center for Philosophy of AI and participates in the alignAI (ERC) and ROBUST AI (NWO) consortia. His work bridges philosophy with AI and neuroscience, focusing on explainable AI (XAI), mechanistic explanation, and cognitive modeling. Education: BSc in Computer Science and Philosophy, Cornell University MSc in Philosophy of Mind, University of Warwick PhD in Cognitive Science, Indiana University Bloomington Zednik’s research investigates philosophical questions about biological and artificial intelligence, emphasizing: Methodological principles in cognitive psychology and neuroscience Norms and best practices for XAI in machine learning Knowledge representation in transformer models and large neural networks His recent publications explore the integration of cognitive models into XAI, the role of Bayesian reverse-engineering in cognitive science, and the mechanistic explanation of network neuroscience. Zednik also contributes to international standardization efforts through ISO/IEC TS 6254 and DIN SPEC 92001 . Scientific Awards include fellowships from: DAAD Alexander-von-Humboldt Foundation StandICT Fellowship Zednik supervises PhD students Zeynep Kabadere , Michela Ghezzi , Céline Budding , Miriam Gorr , and Hannes Boelsen , while mentoring postdocs Manuel Barbosa de Oliveira and Philippe Verreault-Julien . His teaching spans philosophy of AI, ethics of machine learning, and decision theory, with innovation projects on generative AI in higher education.

• Audio and Speech Processing
• Signal Processing
• Image Processing
• +3 more

Serkan KESER is an Associate Professor in the Department of Electrical and Electronics Engineering at the Faculty of Engineering and Architecture, Ahi Evran University, Turkey. He has been serving as a full-time faculty member since 2018 and previously served as Head of Department from 2018-2021. His educational background includes a PhD in Electrical and Electronics Engineering from Eskişehir Osmangazi University (2009-2018), a Master's degree in the same field from the same institution (2005-2008), and a Bachelor's degree in Electrical and Electronics Engineering from Mustafa Kemal University (1999-2005). Dr. KESER's research focuses on three main areas: Audio and Speech Processing : Including speaker identification, isolated word recognition, and speech coding techniques Signal Processing : With applications in fiber optic sensor systems and acoustic positioning Image Processing : Covering face recognition, image compression, and denoising techniques His recent publications demonstrate a strong trend toward integrating machine learning and deep learning approaches with traditional signal processing methods. He has made significant contributions in applying subspace methods to various domains including speech recognition, image processing, and sensor technologies. His work often bridges theoretical signal processing concepts with practical applications in areas like smart home systems, medical imaging, and environmental monitoring. Dr. KESER has successfully supervised five Master's students to completion, with thesis topics spanning deep learning applications for class attendance systems, photovoltaic systems, speaker identification, brain tumor classification, and speech-controlled robotic arms. He has led four research projects, including development of fiber optic motion sensors, smart home models using Arduino microcontrollers, and science outreach initiatives. His teaching portfolio includes advanced courses in digital image processing, artificial neural networks, digital signal processing, and machine learning at both undergraduate and graduate levels. Dr. KESER's research impact is reflected in his publication metrics: 30 total publications with 117 citations (h-index 5) through the UNIS system, 25 publications with 180 citations (h-index 6) on Google Scholar, and strong representation in Scopus and Web of Science databases.

• Quantum Computing
• Machine Learning
• Parallel and Distributed Systems
• +1 more

Giacomo Vitali is a Ph.D. candidate in Computer and Systems Engineering at the Politecnico di Torino , Department of Control and Computer Science (DAUIN), while also serving as a Lecturer at the same institution. His research focuses on Quantum Computing , Machine Learning , and Parallel and Distributed Systems . Education: M.Sc. in Physics of Fundamental Interactions (2018) from the University of Pisa Research: Pioneering hybrid quantum-classical algorithms for industrial applications, including BBQ-mIS and DEN models for graph problems and quantum hardware optimization Teaching: Contributing to courses on Quantum Hardware Design and Quantum Computing at the M.Sc. level, as well as undergraduate courses in Computer Science

Alireza MohammadinodooshanView profile

Research Fellow

• Social Media Analysis
• User Engagement Dynamics
• Data Mining
• +3 more

Alireza Mohammadinodooshan is a Postdoctoral Fellow at Linköping University's Department of Computer Science (IDA), Sweden, working within the Database and Information Technology (ADIT) research group. He contributes to the Wallenberg AI, Autonomous Systems and Software Program (WASP) – Sweden's largest individual research initiative – focusing on data-driven analysis of social media engagement dynamics across Twitter, Facebook, and Instagram platforms. His research centers on quantifying how political bias, news reliability, and content-agnostic factors shape temporal user engagement patterns. Key interests include social media analysis, user engagement dynamics, data mining, information systems, network science, and artificial intelligence, with emphasis on cross-platform comparative studies and algorithmic amplification effects in news consumption. Analysis of his 15 most recent publications reveals consistent focus on temporal modeling of engagement decay, multi-format content interaction (photos/videos/albums), and the interplay between news source characteristics and user behavior. His methodological approach combines large-scale dataset analysis with network theory to identify virality predictors and platform-specific engagement mechanics. No scientific awards were documented in available sources. No advising roles or research grants were referenced in the provided materials. He operates within the ADIT research group at Linköping University, which specializes in advanced database and information systems for the digital society. This group forms part of IDA's broader WASP-affiliated ecosystem focused on AI-driven autonomous systems, enabling interdisciplinary collaboration on large-scale data challenges in social computing.

• Representative method
• non-random samples
• public statistics
• +2 more

Dr. Maciej Beręsewicz serves as a Professor in the Department of Statistics at Poznan University of Economics and Business (UEP), holding key institutional roles including Member of the Competition Committee for "Mini-grants for Research," University Evaluation Team, and Rector's Committee for Academic Teacher Awards. His office is located in Building C, Room 406, with contact email Maciej.Beresewicz@ue.poznan.pl and phone 61 854 36 80. His research centers on representative methods, non-random samples, public statistics, big data applications, and statistical package development. He specializes in methodological innovations for non-probability surveys, capture-recapture modeling, and integrating administrative/online data sources into official statistics frameworks. Recent publications demonstrate a cohesive trajectory in survey methodology, particularly calibration techniques for probability/non-probability sample integration, quantile estimation, and job vacancy analysis using online advertisements. His R packages ( nonprobsvy , singleRcapture ) operationalize these methods for practical statistical implementation. Prof. Beręsewicz maintains significant external engagements through the Central Statistical Office of Poland (Real Estate Price Statistics Team, Quality Group), Baltic-Nordic-Ukrainian Network on Survey Statistics (Scientific Committee), and international bodies including the International Association of Official Statisticians and International Association of Survey Statisticians.

• Organic Computing
• Evolutionary Algorithms
• Learning Classifier Systems
• +6 more

Professor Jörg Hähner holds the Chair of Organic Computing at the University of Augsburg's Faculty of Applied Computer Science within the Institute of Computer Science. He leads a research team focused on evolutionary computation, self-organizing systems, and intelligent computing approaches. His educational background includes computer science studies at TU Darmstadt. His academic career progression shows steady advancement in the field of organic and self-organizing computing systems. Prof. Hähner's research spans multiple interconnected domains in computational intelligence. His primary focus is on Organic Computing, which involves developing systems that can adapt and self-organize in complex environments. Within this framework, he has made significant contributions to Evolutionary Algorithms, particularly Cartesian Genetic Programming and Learning Classifier Systems. His work explores how these techniques can be applied to real-world problems such as predictive maintenance, energy systems optimization, and industrial automation. The research demonstrates a strong emphasis on both theoretical foundations and practical applications of self-adaptive systems. An analysis of his recent publications reveals a strong concentration on evolutionary computation techniques, particularly Cartesian Genetic Programming variants and Learning Classifier Systems. His research group has been actively developing frameworks like CRust_GP and GRAHF to advance modular construction of evolutionary algorithms. There's a clear trend toward applying these techniques to industrial problems including predictive maintenance, resource allocation in networks, and energy management systems. The publications show consistent exploration of fundamental questions about algorithm behavior while maintaining strong connections to practical applications. Prof. Hähner leads an active research group with numerous PhD students and collaborators, including Karen Poloczek, Henning Cui, Victor Gerling, Dr. Michael Heider, Marco Hüller, Neele Kemper, Helena Stegherr, Jonathan Wurth, and Roman Sraj. His team regularly publishes in top-tier conferences and journals in evolutionary computation, intelligent systems, and industrial applications. The Organic Computing research group maintains a strong presence in both theoretical and applied research, with projects spanning from foundational algorithm development to industrial applications in manufacturing, energy systems, and network optimization. The group's work demonstrates a cohesive research vision centered on creating adaptive, self-organizing computational systems that can operate effectively in complex real-world environments.

Mark BaileyView profile

Professor

• Computer Security
• Computer Architecture
• Embedded Systems
• +2 more

Mark Bailey is the Robert and Pamela (Craig) Delaney Professor of Computer Science at Hamilton College, where he has served as Chair of the Department of Computer Science since 2011. He teaches foundational courses including Introduction to Computer Science, Data Structures, and Computer Organization, and pioneered the innovative course Secrets, Lies, and Digital Threats that pairs Hamilton students with high school classes for cybersecurity education. His educational background includes: Ph.D. in Computer Science from the University of Virginia M.C.S. from the University of Virginia B.S. from the University of Massachusetts Dr. Bailey's research bridges theoretical computer science and practical applications, with primary focus areas in computer security , embedded systems optimization , and compiler design . His work on mobile encryption architectures and fault-tolerant distributed systems demonstrates interdisciplinary innovation, while his educational initiatives like the high school cybersecurity outreach program reflect commitment to real-world impact. Recent publications show increasing emphasis on mobile security and interactive optimization tools for embedded environments. His publication trends reveal consistent exploration of security vulnerabilities across computing layers—from low-power mobile encryption to server protection models—with growing attention to educational applications of security research since 2008. The interdisciplinary nature of his work connects hardware architecture, software engineering, and pedagogical innovation. Key recognitions include: Three competitive National Science Foundation grants Two Microsoft Research grants National Research Council/Air Force Research Laboratory Faculty Fellowship Hamilton College's Richardson Award for Faculty Innovation Dr. Bailey has secured over $1.2M in external funding through NSF and Microsoft Research grants, and provided consultancy for the Air Force Research Laboratory and Assured Information Security. His academic service includes editorial leadership as Editor-in-Chief of ACM Inroads and membership on the Barry Goldwater Scholarship review committee. Campus leadership roles span the Information Security Review Board, High Performance Computing Advisory Committee, and multiple college governance bodies since 1997. He actively shapes academic infrastructure through committee work including the Committee on Information Technology (chaired 2003–2005) and Science Facilities Faculty Committee, while maintaining strong industry connections through conference organization for SIGPLAN and NYCWiC.

Shuting HanView profile

Research Fellow

• Neuroscience
• Cortical Dynamics
• Sensory Processing
• +3 more

Dr. Shuting Han leads a Junior Research Group at the University of Zurich under the Helmchen Lab, funded by the SNSF Ambizione Fellowship since 2024. She holds a Research Fellow position focusing on cortical dynamics underlying sensory processing and memory. Her research examines how distributed cortical areas interact during sensory processing and memory formation, utilizing multi-area two-photon calcium imaging, virtual reality behavior paradigms, electrophysiology, and advanced data analysis techniques. Key projects include investigating sensory representation in cortical areas, predictive processing in neural circuits, cortico-cortical interactions, memory consolidation across the neocortex, and developing high-throughput imaging methodologies. Her recent publications demonstrate expertise in cross-modal predictions, cortical microstates during consciousness alterations, and neural ensemble dynamics. She directs research on top-down predictive signals in neocortex and develops tools for volumetric neural imaging. SNSF Ambizione Fellowship Dr. Han mentors PhD students Maï Ly Leclair and Saidong Ma in the Helmchen Lab. Her group develops custom multi-area two-photon microscopes and applies machine learning for neural data analysis, bridging experimental neuroscience with computational approaches to decode cortical information processing.

Mario Marques FreireView profile

Professor

• Computer Systems and Networks
• Cloud Computing
• Computer Security and Privacy
• +3 more

Mário Marques Freire is a Full Professor at the University of Beira Interior, where he serves as President of the Faculty of Engineering and Professor in the Department of Computer Science. He is also a Senior Researcher at Instituto de Telecomunicações, leading the Secure and Intelligent Networked Software Systems Lab. His academic qualifications include a Dr. habil. in Computer Science (2007) and Ph.D. in Electrical Engineering (2000) from the University of Beira Interior, complemented by an M.Sc. in Systems and Automation and B.Sc. in Electrical Engineering from the University of Coimbra. Freire's research spans Computer Systems and Networks, with specific expertise in Cloud Systems, Computer Networking, Security & Privacy, and AI applications. His work focuses on infrastructure virtualization, encrypted traffic classification, DDoS attack detection, and malware analysis. Recent publications demonstrate strong emphasis on cloud security, AI-enhanced defect prediction, and IoT security frameworks. He has received several scientific awards including multiple Conference Best Paper Awards and an ACM Certificate of Appreciation for his long-term contributions. Freire has supervised over 35 graduate students (10 PhD graduates) and led numerous research projects such as 'Towards the assurance of SECURity by dESIGN of the Internet of Things' (FCT/COMPETE/FEDER) and 'Cloud Computing Competence Center'. At the University of Beira Interior, Freire has held significant administrative roles including Vice-Rector (2020-2021), Director of Computer Science Services (2009-2013), and multiple terms as President of the Faculty of Engineering. He leads the Network Applications and Services research group at Instituto de Telecomunicações, focusing on secure networked systems.

• Educational Technology
• Augmented Reality in Education
• STEM Learning
• +4 more

MARIA BLANCA IBAÑEZ ESPIGA is an Associate Professor at the Telematics Engineering Department of Carlos III University of Madrid , specializing in educational technology and immersive learning environments. Her research focuses on integrating augmented reality (AR), virtual reality (VR), and artificial intelligence (AI) into educational practices to enhance student engagement and learning outcomes. Research Focus: Dr. Ibañez Espiga explores the application of augmented reality in STEM education, gamification for learning activities, and learning analytics to model student behavior in immersive systems. She has developed tools like BabloXR for WebXR applications, XploRe for solar system education, and Reaq for chemistry tutoring, demonstrating her commitment to innovative pedagogical solutions. Publications: Recent work includes studies on generative AI in education , cloud-based universities , and AR simulations in problem-based learning . Her research spans from 2010 to 2025, showing sustained contributions to technology-enhanced learning methodologies. Labs & Teams: She is affiliated with the eMadrid Network , a research group focused on learning methodologies, gamification, and quality in educational technology. Her projects often involve interdisciplinary collaboration, leveraging telematics engineering to create scalable educational solutions.

Sayanton DibboView profile

Assistant Professor

• Deep Learning
• Computer Vision
• Secure & Trustworthy AI/ML
• +5 more

Dr. Sayanton Dibbo is an Assistant Professor in the Department of Computer Science at the University of Alabama, where he leads the Trustworthy AI Lab. He is also a faculty affiliate of the Alabama Center for the Advancement of AI (ALA-AI) and Alabama Cyber Institution & HPC. His academic journey includes a PhD in Computer Science from Dartmouth College (2020-2025) and an MS in Computer Science from the University of California, Riverside (2017-2019). Dr. Dibbo's research spans several critical areas in modern computing: Deep Learning and Computer Vision Secure & Trustworthy AI/ML modeling Analysis of foundation models (LLMs and Multimodal systems) Security and privacy aspects of machine learning systems Biometric-based user authentication for IoT devices His recent work focuses on developing defenses against model inversion attacks using sparse coding architectures, improving robustness in audio classification, and creating secure authentication systems for wearable devices. Dr. Dibbo's research spans multiple data modalities including images, tabular data, audio, and text, addressing critical security and privacy challenges in AI systems. Dr. Dibbo has received recognition for his work including the Dartmouth Graduate Student Council Travel Grant for ICASSP 2024 and the Cybersecurity Cluster Research Fellowship. His service to the academic community includes reviewing for Women in Computer Vision (WiCV) at ECCV 2024, Computers and Security Journal, and Neural Networks Journal. As an educator and mentor, Dr. Dibbo is actively seeking highly motivated undergraduate and graduate students to join his research team at the University of Alabama. His lab focuses on cutting-edge problems at the intersection of AI security, privacy, and robustness, offering students opportunities to work on impactful research with real-world applications.

• Computer Networks
• Network Security
• Internet of Things
• +3 more

Utz Roedig is a Full Professor of Computer Science at University College Cork (UCC), Ireland, and a Principal Investigator at the CONNECT Centre. Previously, he served as Professor at Lancaster University, UK, leading the Academic Centre of Excellence in Cyber Security Research (ACE-CSR), and held research positions at UCC and Darmstadt University of Technology, Germany. Education: Dipl.-Ing in Engineering from Darmstadt University of Technology Dr.-Ing (Doctor of Engineering) from Darmstadt University of Technology His research spans computer networks and network security , with over 150 publications in IoT security, industrial control systems, 5G networks, and voice assistant vulnerabilities. Recent work integrates machine learning for intrusion detection and fault prediction while addressing human factors in secure coding. Industry collaborations have yielded multiple patents. Analysis of 2023-2025 publications reveals dominant themes in industrial IoT security (e.g., resilient time-sensitive networking), 5G infrastructure protection, and voice assistant threats (wake word jamming/spoofing). His team develops countermeasures using protocol design and ML-driven anomaly detection, with growing emphasis on human-centric security challenges. Scientific Awards: No specific awards are documented, though research impact is evidenced by patents and sustained funding from major international bodies. Advising and Grants: Secured funding from EU, EPSRC, and industry partners. Serves as grant reviewer for EPSRC (UK), ESF (EU), and FWO (Belgium), and on TPCs for DCOSS, EWSN, and IPSN conferences. Student supervision details are unavailable, but research leadership implies active mentoring. Grants: EU, EPSRC, Industry Review Roles: EPSRC, ESF, FWO Labs and Teams: Leads research at UCC's CONNECT Centre (telecommunications security). Previously directed Lancaster University's ACE-CSR, a UK government-designated cybersecurity research hub.