Find Academic Supervisors

• Biomedical Signal and Image Processing
• Cardiovascular and Neural Modeling
• Physiologically-interpretable Artificial Intelligence systems
• +5 more

Gaetano Valenza is an Associate Professor of Bioengineering at the University of Pisa, Italy, where he leads the Neuro-Cardiovascular Intelligence Lab at the Enrico Piaggio Research Centre. He holds affiliations with the Neuroscience Statistics Research Laboratory at MIT and has served as a Research Fellow at Harvard Medical School and Massachusetts General Hospital. His academic work spans bioengineering, computational physiology, and affective computing. His research focuses on statistical and nonlinear biomedical signal and image processing , cardiovascular and neural modeling , and physiologically interpretable artificial intelligence . He develops wearable systems for physiological monitoring, with applications in autonomic nervous system assessment, brain-heart interactions, and mental health. His work has led to novel metrics such as the Sympathetic and Parasympathetic activity indices derived from ECG. The 15 most recent publications reflect a consistent trend in brain-heart interplay , complexity analysis of physiological signals , explainable AI in healthcare , and virtual reality applications in mental health . His work integrates advanced signal processing, nonlinear dynamics, and machine learning to decode emotional and cognitive states from physiological data. Dr. Valenza is a Senior Member of IEEE and serves on several technical committees. He is an active editorial leader, currently serving as Associate Editor for IEEE-EMBC , Plos One , Complexity , and Scientific Reports , and has guest-edited special issues in Philosophical Transactions of the Royal Society A and IEEE Journal of Biomedical and Health Informatics . He has led or participated in numerous international research projects, including FP7 and H2020 initiatives such as NEVERMIND and EXPERIENCE. He teaches courses in Biostatistics, Probability & Biostatistics, and Advanced Image Processing at the University of Pisa. As lab head and project coordinator, he leads a multidisciplinary team working on neuro-cardiovascular intelligence, wearable systems, and AI-driven mental health interventions.

• Contemporary Ethics
• History of Ethics
• Bioethics
• +3 more

Massimo Reichlin is a Full Professor of Moral Philosophy and the current Dean of the Faculty of Philosophy at Vita-Salute San Raffaele University (since 2022). He holds academic appointments in contemporary ethics, bioethics, and neuroethics. His teaching spans ethics of life, ethical theory, and bioethics, with roles at multiple Italian universities and institutions, including the University of Bergamo and Humanitas University Medical School. Education includes a Degree in Philosophy from the Catholic University of Milan, an Advanced Course in Bioethics from the University of Milan, and a Ph.D. in Bioethics from the University of Genoa. He has held scholarships and research roles at the Scientific Institute Ospedale San Raffaele and led EU-funded projects like 'Enhancing Human Capacities' (2005–2007). Research focuses on contemporary ethics (neo-Kantianism, deontology vs. consequentialism), history of ethics (utilitarianism, conscience), bioethics (beginning/end of life, neuroethics), and moral psychology (cognitive enhancement). He coordinates the Philosophy Ph.D. Program and the CeSEP Centre for Studies in Ethics and Politics. He serves on editorial boards of journals like Paradigmi and Notizie di Politeia , and contributes to public engagement through events like 'Neuroethics: New Ways of Investigating the Brain' (2021). His work bridges philosophical theory and applied ethics in medicine, technology, and policy.

• Artificial intelligence
• Biomedical signal processing
• Human movement analysis
• +12 more

Marco Ghislieri is an Assistant Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino, Italy. He is a member of the Interdepartmental Center PolitoBIOMed Lab and teaches in the Biomedical Engineering program, including courses like Neuroengineering and Design of Programmable Biomedical Devices . His research spans Artificial Intelligence, Biomedical Signal Processing, Neuroscience, and Rehabilitation Engineering . PhD in Bioengineering and Medical-Surgical Sciences (2017-2021) at Politecnico di Torino Thesis: Muscle Synergy Assessment during Cyclic and Non-Cyclic Movements His research focuses on muscle synergy analysis in Parkinson’s Disease (PD) patients post- Deep Brain Stimulation (DBS) , AI-driven gait analysis for fall prevention, and wearable sensor applications for stress-cognitive decline monitoring. He leads the S-CoDe and OMNIA-PARK projects, and contributes to PRIN as a team member. Recent publications highlight advancements in machine learning for intraoperative DBS targeting , statistical gait analysis , and neurorehabilitation tools . He serves as Associate Editor for Scientific Reports and Applied Bionics and Biomechanics , and Guest Editor for Frontiers in Neural Circuits . Awards include the Carlo J. De Luca Award (2022) , GNB Doctoral Award (2022) , and the Best Poster Award at M. Grattarola Summer School (2022) . He supervises Fabrizio Sciscenti (PhD candidate) and collaborates on neuroengineering and biomedical device design courses. His work addresses Goal 3 (Good Health) and Goal 4 (Quality Education) of the UN SDGs.

Emma ColamarinoView profile

Researcher

• Electroencephalographic (EEG) Signal Processing
• Electromyographic (EMG) Signal Processing
• Brain-Computer Interfaces (BCI)
• +4 more

Emma Colamarino is a Researcher at the Department of Computer, Control and Management Engineering "Antonio Ruberti" of Sapienza University of Rome. She holds an M.Sc. in Biomedical Engineering (2014, cum laude) and a Ph.D. in Bioengineering (2019). Since 2015, she has been a research collaborator at the Neuroelectrical Imaging and Brain-Computer Interfaces Lab of IRCCS Fondazione Santa Lucia in Rome and served as a Visiting Ph.D. student at Imperial College London (2018). From 2019 to March 2023, she was a Post-Doctoral Fellow at Sapienza University. Her research focuses on Advanced electroencephalographic (EEG) and electromyographic (EMG) signal processing Brain-Computer Interface (BCI) protocols for cerebral function recovery Machine learning in neurorehabilitation Hybrid BCIs integrating cortico-muscular networks Recent publications address stroke rehabilitation, BCI design, spectral graph theory, and EMG-EEG integration. Her work spans biomedical data analysis, neuroengineering, and rehabilitation technology validation. Scientific awards include multiple grants from Sapienza University and the Italian Ministry of Health, a Student Award at the 7th International BCI Meeting (2018), and recognition as a Subject Expert (2019). She has supervised/co-supervised 18 MD theses across Biomedical, Management, and Robotics Engineering disciplines.

Shervin ShirmohammadiView profile

Professor

• Computer Vision
• Image Processing
• Health Monitoring Systems
• +4 more

Dr. Shervin Shirmohammadi is a Professor at the University of Ottawa's Faculty of Engineering, specifically within the School of Electrical Engineering and Computer Science. With an impressive h-index of 41 and over 6,800 citations across 473 publications, his research has made significant contributions to the fields of computer vision, biomedical instrumentation, and health monitoring systems. His academic journey spans over two decades, beginning with work on communication architectures for virtual environments in 2001 and evolving toward practical healthcare applications. Dr. Shirmohammadi's research interests center on Computer Vision , Image Processing , and Embedded Systems with a strong focus on healthcare applications including nutrition monitoring, mental health assessment, and driver safety systems. His most influential work examines computer vision applications for health monitoring, particularly food calorie measurement systems that use smartphone cameras to analyze nutritional content. His research has evolved to include EEG-based systems for ADHD detection and serious games for autism therapy, demonstrating a consistent trajectory toward practical healthcare solutions using advanced instrumentation techniques. Dr. Shirmohammadi maintains active collaborations with researchers including A. Yassine (118 joint publications), D. Ahmed, Ali Asghar Nazari Shirehjini, and B. Hariri. His publications appear primarily in IEEE Transactions on Instrumentation and Measurement, reflecting his strong connection to the instrumentation and measurement community.

Roland BenedikterView profile

Lecturer

• Futures Studies
• Societal Transformation
• Re-Globalization
• +6 more

Roland Benedikter serves as a Lecturer at the Faculty of Design and Arts, Free University of Bozen-Bolzano and as Co-Head of the Center for Advanced Studies at Eurac Research. He holds the prestigious UNESCO Chair in Interdisciplinary Anticipation and Global-Local Transformation and is an Ordinary Member of the European Academy of Sciences and Arts. His work bridges academic scholarship with practical policy applications across European and global contexts, with particular focus on South Tyrol/Alto Adige as a model region. Benedikter's research interests span futures studies, societal transformation, re-globalization, neuroethics, and the intersection of technology with humanity. He specializes in interdisciplinary anticipation approaches that integrate macro, meso and micro perspectives to address complex global challenges. His expertise encompasses geopolitical analysis, international and local development, public policy, governance, and European Union affairs, with particular attention to the evolving relationship between global frameworks and local implementation. His recent publications reveal a strong emphasis on futures literacy as a critical capability for navigating systemic crises, with particular focus on neurotechnology standards, sustainable development trajectories, and the evolving nature of globalization. Benedikter's work consistently examines how societies can develop anticipatory governance capacities to better manage uncertainty and complexity in an era of rapid technological change. UNESCO Chair in Interdisciplinary Anticipation and Global-Local Transformation Ordinary Member of the European Academy of Sciences and Arts Co-Head of Center for Advanced Studies at Eurac Research Extensive publication record on re-globalization and futures studies Benedikter actively engages with policymakers and practitioners to translate futures research into actionable strategies. His work with the Center for Advanced Studies facilitates interdisciplinary collaboration across scientific disciplines to address complex societal challenges. He frequently contributes to public discourse on the future of European SMEs, digital transformation, and the ethical implications of emerging technologies, emphasizing the need for inclusive and participatory approaches to societal transformation.

Marco BuzzelliView profile

Assistant Professor

• Signal Processing
• Image Processing
• Video Processing
• +3 more

Marco Buzzelli is an Assistant Professor at the Department of Informatics, Systems and Communication (DISCo) at the University of Milan-Bicocca, where he also obtained his PhD in Computer Science in 2019. His academic career is centered around cutting-edge research in signal, image, and video processing with a specialized focus on color imaging and machine learning applications. Dr. Buzzelli's research interests span multiple interconnected domains within computer vision and image processing. He has established himself as a leading researcher in color constancy, with numerous publications exploring illuminant estimation, white balance algorithms, and perceptual aspects of color imaging. His work extends to video restoration, particularly addressing challenges in low-light conditions and HEVC-compressed video processing. Additional research areas include hyperspectral imaging applications for historical document analysis, food authentication technologies, and neural architecture search for various computer vision tasks. His publication record demonstrates a clear evolution from foundational work in logo recognition and saliency detection toward increasingly sophisticated approaches to color science and video processing. Recent work shows strong emphasis on uncertainty estimation in color constancy, Bayesian optimization for night photography, and multimodal approaches combining spectral information with traditional RGB imaging. His research often bridges theoretical advances with practical applications across diverse domains including cultural heritage preservation, food safety, and computational photography. As an active ELLIS member, Dr. Buzzelli maintains significant European collaborations with institutions including Universitat Autònoma de Barcelona, Universidade Nova de Lisboa, Université Jean Monnet, and Universidad de Granada. His research group participates in major challenges such as the NTIRE series on night photography rendering and spectral recovery, contributing both methodological innovations and comprehensive surveys of the field. His laboratory work focuses on developing practical imaging solutions with real-world applications, particularly evident in projects addressing food authentication, historical document analysis, and vision-based monitoring systems. The integration of traditional image processing techniques with modern deep learning approaches characterizes his methodological approach across multiple research domains.

• Cognitive Neuroscience
• Functional Neuroimaging
• Brain Mapping
• +3 more

Sabrina Pitzalis is an Associate Professor at the University of Rome 'Foro Italico', Department of Human Motor Sciences and Health. She serves as Delegate for Gender Budget and Head of the SACS (Student Counselling and Help Desk). Her research focuses on cognitive neuroscience, functional neuroimaging, and brain mapping, with specializations in neural mechanisms of perception, sensorimotor functions, and brain plasticity induced by motor activity. She leads projects like the 2019 study on neuromuscular electrical stimulation effects. Her work integrates neuroimaging techniques to explore topics such as anticipatory brain activity and motion perception. Pitzalis teaches courses in sport psychology, neuroscience, and pedagogy, emphasizing the interplay between cognitive and motor systems. Her research highlights neural adaptations to sensory and motor interventions, including multifocal contact lenses and exoskeleton-assisted rehabilitation. Research Themes: Neural basis of perceptual and sensorimotor functions Brain plasticity and motor learning Anticipatory neural processing during action preparation Integration of visual and motor signals in spatial navigation Recent Contributions: Her articles (2022–2025) reveal insights into how brain circuits process self-motion, adapt to sensory interventions, and modulate during complex cognitive-motor tasks. These studies use advanced neuroimaging and electrophysiological methods to map functional brain dynamics. Ongoing work explores neurocognitive trade-offs in dual-task scenarios and the role of parietal cortex in visuomotor integration. Teaching and Leadership: Pitzalis contributes to degree programs in Sports Sciences (L22), Preventive Motor Activities (LM67), and Sports Technology (LM68). She promotes interdisciplinary approaches, combining neuroscience with sport pedagogy. Her leadership roles emphasize institutional quality assurance and student support initiatives. Labs/Teams: Collaborates within university labs specializing in motor neuroscience and neuroimaging, contributing to projects on neural adaptation mechanisms and clinical applications in rehabilitation.

Calogero Maria OddoView profile

Associate Professor

• Bionic tactile sensing
• Neurophysiology of touch
• Artificial intelligence in tactile systems
• +5 more

Calogero Maria Oddo is an Associate Professor at Sant’Anna School of Advanced Studies, affiliated with the BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence. He leads the Neuro-Robotic Touch Laboratory, coordinating a team of 25+ researchers. His work bridges neuroscience and engineering, focusing on tactile sensing, neuroprosthetics, and biomedical robotics. He holds a national qualification as Full Professor of Bioengineering and serves in academic governance roles, including Vice-Coordinator of the BioRobotics PhD program and President of the University Committee for Equal Opportunities. His research has been featured in top journals like Nature Machine Intelligence and recognized by prestigious awards such as the Feltrinelli Prize under 40 (2023). Education BSc in Electronic Engineering (University of Pisa, 2005, 1st in cohort) MSc in Electronic Engineering (University of Pisa, 2007, Excellence Track) PhD in Innovative Technologies (Sant’Anna School of Advanced Studies, 2011) Graduate of Sant’Anna Honours College (2008, 2006) Research Interests His lab develops tactile sensors inspired by human neurophysiology, with applications in bionic prostheses, robotic surgery, and healthcare. Key areas include neuromorphic engineering, mechanotransduction, and sensory feedback systems. Collaborations span institutions like the National Research Council, University of Pisa, and international partners such as École Normale Supérieure. Grants & Awards Coordinator of €10M+ in research funding from EU, Italian ministries, and private foundations Contributions to technology transfer via RoboIT and the ARTES 4.0 Competence Center Labs & Teams Leads the Neuro-Robotic Touch Lab and collaborates with the N2Lab (National Research Council), focusing on clinical translation of tactile technologies.

Francesca NonisView profile

Assistant Professor

• Facial Expression Recognition
• Deep Learning
• Human-Computer Interaction
• +6 more

Francesca Nonis is an Assistant Professor and Fixed-term researcher at Politecnico di Torino's Department of Management and Production Engineering (DIGEP). She is an invited member of both the College of Architecture and Design and the College of Mechanical, Aerospace, and Automotive Engineering. As part of the 3D LAB research group, she contributes to cutting-edge research in human-computer interaction applications and 3D data visualization. Dr. Nonis specializes in Facial Expression Recognition (FER) using Deep Learning techniques, with a focus on 3D data applications for human-computer interaction. Her research spans multiple domains including virtual reality, affective computing, and cultural heritage preservation. She has developed methodologies for real-time facial expression recognition and has contributed to building spontaneous 3D facial expression databases that have advanced the field of emotion recognition. Her recent publications reveal a strong trend toward interdisciplinary research that bridges computer science, psychology, and cultural applications. She has made significant contributions to metaverse platforms for cultural heritage preservation, user engagement studies using EEG in museum settings, and the development of affective virtual reality environments. Her work consistently applies advanced computer vision and deep learning techniques to solve real-world problems in human-computer interaction. Dr. Nonis has co-authored a national patent titled "Methodology for real-time facial expression recognition" with Federica Marcolin, Luca Ulrich, and Enrico Vezzetti. Her teaching portfolio includes Industrial Technical Drawing and Modeling Design courses across multiple engineering disciplines including Aerospace Engineering, Mechanical Engineering, Chemical and Food Engineering, and Design and Communication programs. As a core member of the 3D LAB research group, Dr. Nonis collaborates on projects involving facial morphology studies, innovative surgical guides, augmented reality applications, and e-learning solutions. The lab's work leverages 3D sensors, augmented and virtual reality, and machine learning techniques to develop applications for medical, security, and marketing domains.

• Nanomechanical sensing
• Memristive nanodevices
• Biosensors
• +6 more

Carlo Ricciardi is a Full Professor in the Department of Applied Science and Technology (DISAT) at the Polytechnic University of Turin, where he serves as Coordinator of basic subjects for the 2nd year of Engineering and is a member of the Interdepartmental Center CWC - CleanWaterCenter@PoliTo. His research focuses on nanomechanical sensing and memristive nanodevices, with applications spanning biomedical engineering, environmental monitoring, and brain-inspired computing systems. His research interests center on the intersection of nanotechnology and biological systems, particularly in developing bio-inspired nanodevices for sensing applications. Ricciardi's work bridges fundamental nanoscience with practical implementations in memristive devices , nanomechanical sensors , and brain-inspired computing architectures . His research group explores how nanoscale phenomena can be harnessed for biomedical applications, environmental monitoring, and next-generation computing paradigms that mimic neural processing. The recent publications reveal a strong trend toward neuromorphic computing using nanowire networks, with significant work on self-organizing systems that exhibit brain-like computational properties. His research spans multiple disciplines including nanotechnology, materials science, electronics, and biophysics, with a particular emphasis on creating sustainable and efficient computing systems inspired by biological principles. The work often combines experimental fabrication with theoretical modeling to understand complex phenomena at the nanoscale. Young Scientist Award (European Materials Research Society, 2002) Keynote Paper Finalist, Biosensors 2010 (2010) Premio Giovedì Scienza (2012) National Scientific Qualification as Associate Professor Sector 02/B1 (MIUR, 2013) National Scientific Qualification - Second Band - Sector 02/B3 (MIUR, 2013) Ricciardi actively mentors doctoral students and serves on multiple PhD program committees across Physics and Engineering disciplines. He has secured substantial research funding through competitive national and international projects including the EU-funded GreenChips-EDU (2023-2027), NEURONE (2023-2025), and MEMQuD (2021-2024) projects. His collaborations span academia and industry, with partnerships including the University of California Berkeley and various European research institutions. As Principal Investigator of the NaMeS research group, Ricciardi leads investigations into two interconnected research domains: nanomechanical sensing and memristive nanodevices. The group operates specialized laboratories including the CHILAB Laboratory in Chivasso and the Nanoscience Vibrometric Lab, focusing on developing innovative sensor technologies and neuromorphic computing architectures that draw inspiration from biological systems.

• Biomedical signal processing
• Gait analysis
• Motor control
• +8 more

Valentina Agostini is an Associate Professor in the Department of Electronics and Telecommunications (DET) at Polytechnic University of Turin, where she has established herself as a leading researcher in biomedical engineering with expertise in human movement analysis and signal processing. She is also a member of the Interdepartmental Center PolitoBIOMed Lab - Biomedical Engineering Lab, contributing significantly to the university's biomedical research infrastructure. Her primary research interests include biomedical signal processing, gait analysis, motor control, muscle synergies, postural control, and neuroengineering. Dr. Agostini leads the Biolab: Biomedical Engineering Group within DET, conducting research at the intersection of engineering principles and clinical applications. Her work spans fundamental signal processing techniques to clinical applications for neurological disorders, orthopedic recovery, and aging populations. Dr. Agostini's recent publications demonstrate a strong focus on applying engineering methodologies to understand human movement, with increasing integration of machine learning and AI approaches. Her research shows evolution from foundational work on EMG signal processing toward sophisticated clinical applications, particularly for Parkinson's disease and cognitive-motor interactions. The trend indicates growing emphasis on wearable sensor technology, objective clinical assessment tools, and AI-driven diagnostic and therapeutic support systems. SIAMOC Best Methodological Paper Award (2009) Young Research Award from Società Italiana di Analisi del Movimento in Clinica (2010) AITA Best Paper Award (2013) MEMEA Best paper award from IEEE Instrumentation and Measurement Society (2014) Dr. Agostini serves as a dedicated mentor, currently supervising PhD student Fabrizio Sciscenti on neuroengineering techniques for Parkinson's Disease management. She leads significant research projects including S-CoDe (2025-2027) on stress and cognitive decline assessment, and PD_DBS (2023-2025) examining deep brain stimulation effects. Her editorial service includes Scientific Reports, Sensors, and Frontiers in Sports and Active Living, reflecting her standing in the international research community. She is a founding member of the National Bioengineering Group (GNB) and maintains active roles in professional societies including IEEE-HKN. Her laboratory work centers around the PolitoBIOMed Lab, where her team develops innovative approaches to biomedical signal processing, human movement analysis, and neuroengineering applications for healthcare, with particular focus on translating research findings into clinical practice for improved patient outcomes.

Andrea VinciView profile

Researcher

• Quantum Computing
• Edge-Cloud Computing
• Internet of Things (IoT)
• +5 more

Andrea Vinci is an accomplished researcher with 66 publications and 1,261 citations, specializing in the intersection of quantum computing, edge-cloud architectures, and Internet of Things (IoT) systems. His work demonstrates significant contributions to solving complex computational problems through innovative approaches that bridge theoretical quantum algorithms with practical distributed computing applications. His research interests span quantum computing applications for resource management, multi-density clustering techniques for urban analytics, and platform-independent IoT application development. Vinci has pioneered work in variational quantum algorithms for cloud/edge resource allocation, quantum kernels for IoT data classification, and distributed AI for cognitive building systems. His research demonstrates a consistent focus on addressing NP-hard problems through quantum-classical hybrid approaches. Analysis of Vinci's publication trends reveals a strategic research trajectory moving from foundational work in smart city analytics and crime prediction toward cutting-edge quantum computing applications for IoT and edge-cloud systems. His recent publications (2023-2025) show increasing focus on quantum machine learning techniques specifically tailored for IoT data processing, with significant attention to practical implementation challenges. Vinci maintains an extensive collaborative network, frequently publishing with researchers including Fabrizio Marozzo, C. Mastroianni, J. Settino, and Antonio Guerrieri across multiple high-impact venues including IEEE Transactions, ACM conferences, and specialized journals in quantum computing and distributed systems. His technical contributions include the development of the COGITO platform for cognitive buildings, novel approaches to multi-density crime prediction, and significant advancements in quantum kernel methods for IoT data analysis. Vinci's tutorial publications indicate his role in educating the broader research community about emerging quantum computing applications for distributed systems.

Vincenzo CatramboneView profile

Assistant Professor

• Biomedical Signal Processing
• Brain-Heart Interactions
• Computational Neuroscience
• +3 more

Dr. Vincenzo Catrambone is an Assistant Professor in the Department of Information Engineering at the University of Pisa and a fellow of the Neuro-Cardiovascular Intelligence Lab. His research focuses on integrative approaches to understanding brain-body interactions using advanced signal processing and computational modeling techniques. His research program investigates functional interactions between cardiovascular dynamics and neural activity in both physiological and pathological conditions. Key areas include neuro-cardiac coupling mechanisms, emotion-time perception relationships in depression, multisensory integration, and brain-computer interface development. His methodological approaches combine EEG analysis, computational modeling, physiological monitoring, and neuromodulation techniques. Recent publications demonstrate increasing focus on clinical applications, particularly in depression, epilepsy, and trauma-related disorders. His work on brain-heart interplay has evolved toward translational studies investigating how psychotherapeutic interventions modulate neuro-autonomic communication pathways.

• Cognitive Science
• Computer Science
• Linguistics
• +9 more

Jakub Krzysztof Szymanik is a Polish computer scientist and cognitive scientist currently serving as an Associate Professor at the Interdepartmental Center for Mind/Brain Sciences (CIMEC) and the Department of Information Engineering and Computer Science at the University of Trento, Italy. PhD in Computer Science (2009) from the University of Amsterdam Associate Professor at University of Trento (2022–) Former Associate Professor at University of Amsterdam (2013–2022) His research focuses on the intersection of computational linguistics, cognitive science, and formal semantics. He explores how generalized quantifiers and logical structures relate to human cognition, with applications in: Computational models of language and meaning Neurocognitive architectures Machine learning approaches to linguistic theory Formal epistemology of social interactions Scientific Awards: ERC Starting Grant (2016) NWO VENI Fellowship (2012) Swedish Research Council Postdoctoral Fellowship (2009) He has served as a principal investigator in the Language in Interaction consortium and maintains affiliations with multiple research groups including Amsterdam Brain and Cognition. His teaching focuses on computational logic, language modeling, and semantics-cognition interfaces.