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Suzanne van der VeldtView profile

Assistant Professor

• Neuroscience
• Behavioural Neuroscience
• Anxiety Disorders
• +5 more

Suzanne van der Veldt serves as an Assistant Professor at the University of Groningen's Faculty of Science and Engineering within the Groningen Institute for Evolutionary Life Sciences (GELIFES), specializing in the behavioural neuroscience cluster. Her research focuses on how the brain distinguishes between safe and threatening contexts, particularly examining failures in this process that lead to anxiety disorders, PTSD, and other fear-related conditions. PhD in Neuroscience from McGill University (2016-2021) as a Vanier Canada Graduate Scholar Postdoctoral fellowship at Université de Montréal and CHU Sainte-Justine (2021-2025) supported by CIHR and FRQS fellowships MSc in European Master in Neuroscience (Neurasmus program) (2013-2015) Her research integrates traditional laboratory approaches with innovative studies of free-roaming mice in semi-naturalistic environments to bridge the gap between controlled experiments and real-world complexity. She specializes in the septohippocampal system, employing cutting-edge techniques including multi-region neural recordings, cell-type specific manipulations, and miniaturized calcium imaging in freely behaving animals. Her work examines how neural circuits assign emotional value to places and experiences, with particular attention to sex differences in emotional processing and vulnerability to anxiety disorders. Analysis of her publication record reveals a consistent focus on hippocampal-septal circuitry, with significant contributions to understanding spatial memory coding, neural oscillations (particularly theta and gamma rhythms), and the neural basis of fear conditioning. Her research increasingly incorporates sex as a biological variable and examines circuit dysfunctions in psychiatric conditions. Vanier Canada Graduate Scholarship (prestigious Canadian doctoral award) CIHR Fellowship (Canadian Institutes of Health Research) FRQS Fellowship (Fonds de recherche du Québec - Santé) Dr. van der Veldt leads the Van der Veldt Lab for Behavioural Neuroscience, which investigates emotional processing through innovative approaches combining circuit neuroscience with ethologically relevant behavioral paradigms. Her lab receives funding through tenure-track mechanisms at the University of Groningen and previously secured competitive fellowships during her postdoctoral training. The lab actively collaborates with international neuroscience groups, particularly with researchers at McGill University and Université de Montréal.

Hitoshi MorikawaView profile

Associate Professor

• Neuroscience
• Addiction Research
• Neural Plasticity
• +5 more

Hitoshi Morikawa is an Associate Professor holding the M. June and J. Virgil Waggoner Professorship in Molecular Biology Neuroscience at the University of Texas at Austin, where he has been faculty since 2002. He directs the Morikawa Lab within the Neuroscience Interdisciplinary Life Sciences Graduate Programs, focusing on neural mechanisms of addiction and reward learning. Dr. Morikawa received his M.D. from Kyoto University in Japan in 1990 and completed clinical training in anesthesiology before pursuing basic research. He earned his Ph.D. in anesthesiology & neuropharmacology in 1999, followed by three years of postdoctoral training at the Vollum Institute in Portland, Oregon, working in John Williams' lab. His research career has evolved from studying opioid receptor mechanisms to sophisticated investigations of the mesostriatal dopaminergic system. His laboratory investigates neural plasticity in the mesostriatal dopaminergic system underlying reward-based learning and addiction development, with particular focus on calcium-dependent regulation of neuronal activity. Using brain slice electrophysiology, calcium imaging, UV photolysis of caged compounds, and behavioral assays combined with targeted pharmacological and viral interventions, his team links cellular and molecular processes to addictive behaviors in animal models. Recent work examines how daily life experiences (stress, diet, exercise) impact these processes to identify risk factors and therapeutic strategies for addiction, schizophrenia, and depression. Dr. Morikawa's publication record spans over 50 articles, with recent work focusing on L-type calcium channel blockers like isradipine for addiction treatment, stress interactions with drug reward, and calcium signaling in dopamine neurons. His work shows consistent progression from cellular mechanisms to translational applications. Japan Scholarship Foundation Predoctoral Scholarship (1994-1997) Ministry of Education, Science and Culture of Japan Grant-in-Aid for Scientific Research (1998-1999) Uehara Memorial Foundation Postdoctoral Fellowship (1999-2000) Dr. Morikawa actively mentors postdoctoral fellows including Saeideh Karimihaghighi and Alican Caglayan, and research assistants like Heather Wessel. His lab continues to recruit new researchers and investigate the cellular mechanisms driving addiction, with current work bridging molecular neuroscience with potential clinical applications for substance use disorders.

Eugenia ChiappeView profile

Researcher

• Neuroscience
• Sensorimotor Integration
• Neural Circuits
• +3 more

Eugenia Chiappe is a Principal Investigator at the Champalimaud Center for the Unknown , leading the Chiappe Lab . Her research focuses on the neural circuits involved in self-movement estimation and sensorimotor integration in Drosophila melanogaster , combining behavioral paradigms , neural activity recording , and genetic tools to uncover mechanistic explanations for brain function in adaptive behaviors. Research highlights : Investigation of HS and VS cells in flies as self-motion estimators . Development of head-fixed walking paradigms for reversible neural perturbation. Identification of nonvisual signals modulating visual responses during locomotion. Exploration of neural dynamics encoding combined visual and motor inputs. Scientific contributions : Marie Curie Career Integration Grant PCIG13-GA-2013-618854 Bial Foundation grant 191/12 Collaborative projects on state-dependent sensory processing (Journal of Neuroscience, 2017) Advising and Collaborations : Mentored Daniel Tendero (External PhD Student) and Miguel Paço (INDP PhD Student). Collaborations with teams at Yale University , MIT , and University College London .

• Neuroscience
• Cognitive Neuroscience
• Auditory Neuroscience
• +3 more

Robert Zatorre is a Professor in the Department of Neurology and Neurosurgery at McGill University's Faculty of Medicine. He is a leading expert in auditory neuroscience and music cognition, with significant contributions to understanding brain plasticity and reward mechanisms related to music. Zatorre co-founded the International Laboratory for Brain, Music and Sound (BRAMS) in 2006 - a multi-university consortium focused on cognitive neuroscience of music. Key Research Areas Functional and structural properties of the auditory cortex Hemispheric specialization in auditory processing Neural mechanisms of musical emotion and reward Brain plasticity from sensory loss or training Advanced neuroimaging techniques (fMRI, MEG, EEG) Scientific Achievements 2011 IPSEN Foundation Prize in Neuronal Plasticity 2013 Knowles Hearing Science Award 2017 Fellow of the Royal Society of Canada Advising Directed PhD research on auditory prediction mechanisms (2023) Publication Trends show consistent focus on music's neurobiological basis, with recent work exploring cortical rhythmic activity in Parkinson's disease, speech-in-noise perception, and neural correlates of singing. His research combines experimental neuroscience with theoretical frameworks in cognitive science.

Rüdiger KleinView profile

Professor

• Neuroscience
• Developmental Biology
• Neurodegeneration
• +7 more

Prof. Dr. Rüdiger Klein is the Director and Head of the Department of Molecules – Signaling – Development at the Max Planck Institute for Biological Intelligence. His research focuses on neuronal circuit formation, cell-cell communication, and neurodegenerative mechanisms using mouse models. Research Areas : Cortex development, amygdala circuits, optogenetics, mouse behavior, neurodegeneration studies Key Techniques : Genetic circuit manipulation, single-cell RNA sequencing, optogenetics, 2-photon calcium imaging Scientific Contributions : His work includes ERC-funded studies on synthetic neurocircuit reconstruction, FLRT protein roles in cortical folding, and amyloid-like aggregate toxicity in Huntington's disease. Advising : Mentored students including Aleksa Petković and Dr. Ylenia Mastrodicasa. Collaborates with Max Planck Institute of Biochemistry departments on proteostasis and neurodegeneration.

Alessandro CheccoView profile

Assistant Professor

• Crowdsourcing
• Human Computation
• Distributed Systems
• +7 more

Alessandro Checco is an Assistant Professor in the Computer Science Department at University of Rome La Sapienza. His research focuses on crowdsourcing, distributed systems, and privacy-preserving technologies, bridging theoretical computer science with practical applications that consider human factors in technological systems. He has established himself as a significant contributor to the field of human computation and privacy-aware systems. His educational background includes: 2020: Fellowship of Higher Education from The University of Sheffield, Higher Education Academy 2015: Ph.D. in Mathematics from Hamilton Institute (Design of decentralised algorithms applied to channel/code selection and convex optimisation for throughput fairness of 802.11 networks) 2010: M.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction) 2009: Erasmus Scholarship at Universiteit Gent, Department of Telecommunications 2007: B.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction) Checco's research spans multiple areas at the intersection of computer science and social implications of technology. He is particularly interested in Crowdsourcing for Human Computation, Distributed Private Recommender Systems, Information Retrieval, Data Privacy, Distributed Systems, User Data Obfuscation in Web Systems, Societal and Economic Analysis of Online Work, Crowd Workers Unionisation, and Algorithmic Bias. His work often examines how technological systems can be designed to respect user privacy while maintaining functionality, and how crowd work can be structured to be more equitable for workers. His recent publications demonstrate a clear evolution in research focus, beginning with foundational work in wireless networks and distributed algorithms, then shifting toward human computation and privacy-preserving systems. His most recent work increasingly addresses the societal implications of crowd work, including investigations into crowd worker unionization and cooperative models. Several publications examine gender bias in algorithmic systems, reflecting growing attention to fairness and ethical considerations in his field. Among his notable achievements: All That Glitters is Gold-An Attack Scheme on Gold Questions in Crowdsourcing (Best Paper Award) Checco has secured significant research funding and led important projects including the H2020-funded FashionBrain project as Research Director and the EPSRC-funded BetterCrowd project as Research Associate. His work on the FashionBrain project demonstrates his ability to lead large-scale, interdisciplinary research initiatives. He has also received the Technology Innovation Development Award (TIDA) from Science Foundation Ireland. His research has practical applications across multiple domains including recommendation systems (BLC: Private Matrix Factorization Recommenders), peer review assistance using AI, smart farming technologies, and cooperative models for crowd workers (CrowdCO-OP). He has developed frameworks for understanding worker behavior in crowdsourcing platforms and created methods for improving quality control in human computation systems.

James KesbyView profile

Lecturer

• Cognitive Neuroscience
• Psychiatry
• Neurobiology
• +5 more

Dr. James Kesby is a Lecturer at the School of Biomedical Sciences , University of Queensland, with a focus on developmental neurobiology and psychosis research. He is affiliated with the Queensland Centre for Mental Health Research and leads a cross-species research program connecting corticostriatal circuitry to decision-making deficits in schizophrenia. Research Interests: Corticostriatal circuitry in psychosis Decision-making and cognitive flexibility Translational rodent-human models Dopamine and schizophrenia Developmental neurobiology Neurochemical mechanisms of cognitive deficits Article Trends (2025–2023): Recent studies focus on corticostriatal interactions in reversal learning, dopamine modulation in cognitive flexibility, and translational paradigms for psychosis. Articles from 2022–2021 extend findings to clinical schizophrenia subtypes and novel therapeutic targets like GLP-1RAs. Education and Academic History: Dr. Kesby completed his PhD in 2010 at University of Queensland with Prof. Darryl Eyles and A/Prof. Thomas Burne, studying developmental vitamin D deficiency and dopamine systems in schizophrenia models. Research Infrastructure: His work operates within the Developmental Neurobiology Research Stream at the Queensland Centre for Mental Health Research, integrating clinical and preclinical methodologies.

Ashutosh TrivediView profile

Associate Professor

• Formal Methods
• Cyber-Physical Systems
• Reinforcement Learning
• +5 more

Ashutosh Trivedi is an Associate Professor of Computer Science at the University of Colorado Boulder, currently on leave from his position as Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Bombay. He is affiliated with multiple research initiatives including the Centre for Formal Design and Verification of Software (CFDVS) at IIT Bombay, Free and Open Source Software for Education (FOSSEE), and the Indo-French project on Algorithmic Verification of Real-Time Systems (AVeRTS). At CU Boulder, he leads the Programming Languages and Verification (CUPLV) research group focusing on trustworthy AI systems. Trivedi's research centers on bridging formal methods with artificial intelligence to create more trustworthy systems. His work spans formal verification of cyber-physical systems, reinforcement learning with formal guarantees, and developing techniques for ensuring software fairness and accountability. He specializes in using formal languages, automata, and logic to transform vague natural-language instructions into precise specifications for AI systems. His recent projects include developing reinforcement learning algorithms for cardiac pacemaker design based on formal safety requirements, using SAT solvers to ground large language model outputs in logical reasoning, and encoding state representations in reinforcement learning using formal languages. His publication trends reveal a strong focus on neurosymbolic approaches that combine neural networks with symbolic reasoning, particularly for safety-critical applications. Recent work demonstrates increasing integration of formal methods with reinforcement learning, with applications spanning medical devices, tax preparation software, and puzzle-solving AI. His research shows a clear trajectory toward making AI systems more explainable, accountable, and verifiable through principled mathematical frameworks. Distinguished Paper Award at CAV for Regular Reinforcement Learning (2024) NeuS 2025 Disruptive Idea Award for Stochastic Neural Simulation Relations for Transferring Control under Uncertainty ACM Senior Member recognition (2024) Royal Society Wolfson Visiting Fellowship (2024) Trivedi has successfully advised multiple PhD students to completion, including Shadi Tasdighi Kalat (2025), Mateo Perez (2025), John Komp (2024), Vishnu Murali (2024), and Taylor Dohmen (2024). His teaching portfolio includes foundational courses in automata theory, digital logic design, and cyber-physical systems at both IIT Bombay and CU Boulder. He has served on program committees for major conferences including FSTTCS, HSCC, and FORMATS, and organized workshops such as ICLA 2015 and ALC 2015. As leader of the CUPLV research group, Trivedi directs projects focused on formal verification of AI systems, reinforcement learning with safety guarantees, and software fairness. His group collaborates with medical researchers on cardiac device verification and with legal scholars on tax software accountability, reflecting his commitment to applying formal methods to real-world problems with significant societal impact.

Frederick ShicView profile

Professor

• Computational Neuroscience
• Neuroengineering
• Autism Spectrum Disorder (ASD) Research
• +6 more

Dr. Frederick Shic is a Professor of Pediatrics at the University of Washington School of Medicine and a Principal Investigator at Seattle Children's Research Institute. He also holds adjunct appointments in Computer Science & Engineering and Psychology at UW. His research integrates computer science, engineering, and developmental science to create innovative tools for understanding and improving outcomes for children with autism spectrum disorder (ASD) and other developmental conditions. Academic Affiliation: University of Washington (School of Medicine, Department of Pediatrics, General Pediatrics Division) Laboratory: Seattle Children's Innovative Technologies Laboratory (SCITL) Dr. Shic's expertise spans computational neuroscience, neuroengineering, and human-centered computing, with a focus on non-invasive technologies like eye tracking, functional near-infrared spectroscopy (fNIRS), and social robots. His work has been funded by the National Institute of Mental Health (NIMH), Institute of Education Sciences (IES), Simons Foundation, and Autism Speaks. Key contributions include: Development of interactive eye-tracking methodologies for joint attention assessment Investigation of physiological biomarkers (e.g., heart rate-defined sustained attention) in neurodiverse populations Creation of novel computational models for analyzing eye-tracking data Exploration of genetic contributions to attention through twin studies Application of social robots for in-home ASD interventions Analysis of spatiotemporal eye movement patterns as potential ASD biomarkers His academic journey includes: B.S. in Engineering and Applied Science from Caltech Ph.D. in Computer Science from Yale University Postdoctoral training at Yale Child Study Center under NIMH T32 program Prior roles: Associate Research Scientist at Yale, Software Engineer at Sony Interactive Studios, MRS Researcher at Huntington Medical Research Institutes Current research directions include: Standardization of clinical eye-tracking protocols through the International Society for Clinical Eye Tracking (ISCET) Development of accessible, technology-enhanced behavioral paradigms Investigation of reward and motivation mechanisms in ASD attention patterns Translation of EEG and eye-tracking findings into clinical applications

Bijan PesaranView profile

Professor

• Neuronal Dynamics
• Decision Making
• Brain Networks
• +7 more

Bijan Pesaran is a Global Distinguished Professor at New York University's Center for Neural Science, where he leads an active research laboratory focused on understanding large-scale brain circuits and developing brain-based therapies. His research investigates the dynamics of neuronal activity to understand how brain areas interact during decision-making processes. Pesaran's research interests focus on neuronal dynamics and decision-making, with particular emphasis on how distributed brain networks coordinate movements such as saccadic eye movements and reaches. His work examines how specific patterns of neural activity can predict our choices before movements are executed. He employs a combination of experimental and engineering approaches, including multiple-area neural recordings and stimulation, to probe the network mechanisms of decision-making, coordination, and other cognitive functions. His research has significant implications for developing brain-machine interfaces that can translate thought into action, with potential applications for treating neurological disorders. Pesaran's laboratory has produced influential research on local field potential (LFP) activity and its relation to spiking and behavior, finding that oscillations in LFP predict movement direction and are coherent with single cell spiking. His work on correlations between neural activity in different brain areas has revealed how these correlations reflect whether a subject is making choices or following instructions, potentially reflecting communication between decision-making areas. His lab continues to expand tools for multi-area recordings and stimulation to understand how different brain systems work together to guide behavior. Pesaran has mentored numerous postdoctoral fellows and students who have gone on to academic and research positions. His laboratory has received funding for research on brain-machine interfaces, neural prosthetics, and understanding the neural basis of cognitive processes. The lab utilizes advanced technologies including virtual reality, motion capture systems, and neural recording systems to investigate large-scale brain networks.

• Educational Technology
• Computer Education
• Instructional Technology
• +5 more

MEHMET CAN ŞAHİN serves as Assistant Professor and current Head of Department (since 2020) in the Computer and Educational Technologies Education Department at Cukurova University's Faculty of Education. With continuous service since 2010 and prior research assistant roles at both Cukurova and Anadolu Universities, his career demonstrates deep institutional commitment and progressive leadership including Deputy Head of Department (2014-2020). His academic foundation includes: Doctorate (2005-2010) in Computer and Educational Technologies Education from Anadolu University Postgraduate (2002-2005) in same field from Cukurova University Undergraduate (1994-1999) in Computer Education from Middle East Technical University Dr. Şahin's research centers on Educational Technology and Computer Education, with significant contributions to gamification, interactive media design, and Science-Technology-Society intersections. His work critically examines technology integration across educational levels—from preschool tablet applications to higher education academic integrity—while addressing rural-urban disparities and teacher training challenges. Methodologically, he employs mixed approaches including scale development, comparative studies, and qualitative classroom analysis. Publication analysis reveals consistent focus on practical educational technology implementation, particularly measuring impacts of gamification, interactive whiteboards, and emerging tools like VR. His work bridges theoretical frameworks (e.g., OECD's New Millennium Learners) with measurable classroom outcomes, emphasizing contextual adaptation in Turkish and global settings. As thesis advisor for master's research on programming education and principal investigator for the 2013-2014 tablet integration project in preschools, he demonstrates applied research leadership. He further contributes through editorial service on Cukurova University's Faculty of Education Journal Publication Committee since 2010 and teaching graduate courses in Gamification and Instructional Technologies.

• Human Reinforcement Learning
• Cognitive Neuroscience
• Computational Neuroscience
• +3 more

Romane Cecchi is a Research Fellow at the Laboratory for Cognitive and Computational Neuroscience (LNC2) at Ecole Normale Superieure in Paris, France, affiliated with the Human Reinforcement Learning team. Her work bridges experimental psychology, neuroscience, and computational modeling to investigate learning mechanisms in humans. Her research centers on human reinforcement learning, examining how reward-based learning shapes decision-making through cognitive and neural processes. This spans computational neuroscience for modeling neural pathways, cognitive neuroscience for behavioral analysis, and machine learning for algorithmic insights into adaptive behaviors. Key subfields include neural coding of rewards, computational psychiatry applications, and cross-species learning comparisons. At LNC2, she contributes to interdisciplinary projects within the Human Reinforcement Learning team, utilizing methodologies from behavioral experiments to neuroimaging. The laboratory's focus on computational approaches to cognition drives innovation in understanding learning pathologies and developing AI-inspired cognitive models.

Cian O'DonnellView profile

Senior Lecturer

• Computational Neuroscience
• Synaptic Plasticity
• Neural Circuit Dysfunction in Autism
• +3 more

Dr. Cian O'Donnell is a Senior Lecturer in Data Analytics at Ulster University's School of Computing, Engineering & Intelligent Systems. He holds honorary positions at the University of Bristol and leads a computational neuroscience research group focused on synaptic plasticity, autism-related neural circuit dysfunction, and statistical methods for neural data analysis. He obtained his PhD in Neuroinformatics from the University of Edinburgh after completing a BSc in Applied Physics at Dublin City University. His research explores three primary areas: (1) mechanisms of learning and memory via synaptic plasticity models, (2) neural circuit alterations in autism using computational approaches, and (3) development of Bayesian and machine learning methods for analyzing neuroscience datasets. His group actively collaborates with institutions like the Salk Institute and UCLA. Recent publications emphasize Bayesian inference in neural systems, synaptic plasticity dynamics, deep learning applications for neural decoding, and computational psychiatry. His grants include funding from the BBSRC, Leverhulme Trust, and Medical Research Council. He received the Best Student Paper Award at UKCI 2024. Dr. O'Donnell advises multiple PhD students and postdoctoral researchers. Current projects investigate synaptic stability, neural network topologies, and autism biomarkers. His lab utilizes computational modeling, Bayesian statistics, and machine learning to address fundamental questions in neuroscience.

• Systems Neuroscience
• Social Cognition
• Mirror Neuron System
• +5 more

Koen Nelissen is a Senior Lecturer at the Faculty of Medicine, KU Leuven, Belgium, affiliated with the Department of Neuroscience and the Laboratory for Neuro- and Psychophysiology. He is also a member of the LBI-KU Leuven Brain Institute and serves on the Faculty Council of Medicine and the Departmental Council of Neurosciences. Research Focus: His research centers on systems neuroscience in non-human primates, particularly the neural mechanisms underlying action observation, social cognition, and the functional organization of cortical areas such as the insula and the mirror neuron system. Using advanced fMRI techniques in macaque monkeys, he investigates how the brain processes and learns from actions in social contexts. Recent Projects: Nelissen leads or co-leads several high-impact projects, including: Causal role of social brain networks during real-life social interactions (2023–2026) Perceptual Learning from Actions in Non-human Primates (2021–2025) Dynamics of plasticity in the adult brain (2021–2025) Functional organization of the macaque insula (2019–2024) Role of prefrontal cortex and amygdala in social cognition and reward-based learning (2018–2025) Publications: His scholarly output includes over 70 peer-reviewed articles, with recent work appearing in NeuroImage , Brain Sciences , and Frontiers in Integrative Neuroscience . These studies collectively advance our understanding of how the primate brain supports social interaction, learning, and sensorimotor integration. Advising & Collaboration: Nelissen supervises doctoral students such as Laurens Sypré, Ding Cui, and Shivangi Sharma, and collaborates within the KU Leuven Brain Institute and international primate neurobiology networks. Laboratory: He heads research activities at the Laboratory for Neuro- and Psychophysiology, located at ON2 Herestraat 49, 3000 Leuven, Belgium.

Mieke VerfaellieView profile

Professor

• Cognitive Neuroscience
• Neuropsychology
• Memory Disorders
• +6 more

Mieke Verfaellie is a Professor of Psychiatry at Boston University School of Medicine and serves as the Director of the BU Memory Disorders Research Center . Additionally, she is a Research Career Scientist at the VA Boston Healthcare System. Her research focuses on the cognitive and neural foundations of human memory, particularly in clinical populations like PTSD and traumatic brain injury patients. Education: PhD in Psychology from Université catholique de Louvain (1986) Training: Predoctoral research at University of Florida, postdoctoral training at VA Boston Healthcare System/Boston University School of Medicine Verfaellie’s work explores memory disorders through neuroimaging, epigenetics, and behavioral studies. Her research is funded by the National Institutes of Health (NIH) and the Department of Veterans Affairs . Recent publications highlight PTSD-related DNA methylation patterns, memory sampling in decision-making, and hippocampal contributions to procedural memory. She serves on the editorial boards of Neuropsychology , Neuropsychologia , and Journal of Memory and Language , and has received fellowships from leading psychological societies.