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Pernille HemmerView profile

Professor

• Cognitive Psychology
• Episodic Memory
• Semantic Memory
• +4 more

Pernille Hemmer is a Professor in the Department of Cognitive Psychology at Rutgers University. She joined the faculty in 2012 after completing a postdoctoral fellowship at Syracuse University and earning her Ph.D. from the University of California, Irvine's Department of Cognitive Science. Her research focuses on memory systems, decision-making in naturalistic environments, and Bayesian models of cognition. She leads the CCM Lab (https://sites.rutgers.edu/ccm-lab/), investigating how prior knowledge integrates with episodic memory and influences cognitive processes. Key research interests include: Episodic and semantic memory integration Optimal use of prior knowledge in cognitive tasks Bayesian analysis of individual differences in rational models Belief systems and agency perception Her work spans experimental psychology, computational modeling, and interdisciplinary approaches. Notable contributions include developing generalized Bayesian models of reconstructive memory and frameworks for understanding belief dynamics. Recent research explores socially cognizant robotics and counterintuitive concepts across domains. Awards: Higher-Level Cognition Modeling Prize (2008) Her National Science Foundation CAREER grant (2015) supports applications of Bayesian inference to memory and decision-making. Current projects examine temporal binding mechanisms and the memorability of supernatural concepts through novel methodological tools.

Umberto MichelucciView profile

Professor

• Machine Learning
• Artificial Intelligence
• Astrophysics
• +5 more

Umberto Michelucci is a Professor of Scientific Machine Learning at Lucerne University of Applied Sciences and Arts (HSLU), Switzerland. He holds a PhD in Machine Learning applied to Physics and has over 20 years of industry experience. He is the Subject Head of Applied Data Intelligence in Continuing and Executive Education, Head of Certificates in Machine Learning/Data Engineering, and founder of TOELT LLC and the AI Center of Excellence at Helsana Versicherung AG. His research focuses on machine learning applications in science, astrophysics, uncertainty quantification, and sensor technology. Education PhD in Machine Learning applied to Physics (Portsmouth University) Master in Theoretical Physics (University of Florence) Postgraduate Certificate in Higher Education (Open University, UK) Research Interests Michelucci’s work bridges machine learning and scientific disciplines. Key areas include: Machine learning for astrophysics (INAF collaborations) Uncertainty analysis in high-stakes ML systems Deep learning for optical sensing (e.g., olive oil quality analysis) Foundational mathematical concepts for ML in science Awards & Recognition World’s Top 2% Scientists (Stanford List) Google Developer Expert in Machine Learning AI Global Ambassador (2022) TOP AI Influencer in Switzerland (2021) Grants & Collaborations He collaborates with institutions like INAF (Italy) and NVIDIA/Google, leading projects on AI for agrifood, medical imaging, and astrophysics. His work includes $multi-million industry partnerships and EU-funded research. Labs & Teams Director of the TOELT AI Lab and oversees HSLU’s Applied Data Intelligence programs. Active in open-source initiatives and global AI standardization efforts.

Gregory MaioView profile

Professor

• Social Psychology
• Attitudes and Attitude Change
• Values in Relationships
• +3 more

Gregory Maio is a Professor in the Department of Psychology at the University of Bath, affiliated with the Bath Institute for the Augmented Human. He holds a PhD in Psychology from Western University and has held multiple external roles with organizations like the Economic and Social Research Council and the Netherlands Organisation for Scientific Research. Education: Doctor of Philosophy (Psychology), Western University (1993–1997) Master of Arts (Psychology), Western University (1991–1993) Bachelor of Science (Psychology), York University (1987–1991) Research Interests: Dr. Maio focuses on social psychology topics including social values, intellectual humility in debates, values in close relationships, and attitudes toward children. His work contributes to UN Sustainable Development Goals related to education. Key contributions include two books: The Psychology of Values and The Psychology of Attitudes and Attitude Change (3rd ed.). Recent Research Trends: His articles explore themes like group similarities, anti-immigrant prejudice, protest attitudes, and neuro-functional bases of persuasion. These studies emphasize individual differences, cognitive processes, and societal impacts. Collaborations span institutions in the UK and beyond. Grants & Projects: Lead Investigator on projects funded by the Economic and Social Research Council (e.g., mental representations of children, changing attitudes in public discourse). Panel roles for grant assessments and security threat mitigation initiatives. Labs/Teams: Active in interdisciplinary research through the Bath Institute for the Augmented Human, focusing on psychological and neuroscientific applications in social contexts.

Angela D. FriedericiView profile

Professor

• Cognitive Neuroscience
• Neuroscience
• Language Processing
• +4 more

Professor Angela D. Friederici is a leading cognitive neuroscientist and Director of the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. She holds honorary professorships at the University of Leipzig, University of Potsdam, and Charité University Medicine Berlin. Her work focuses on the neural basis of language processing, syntax, and developmental cognitive neuroscience. Friederici has published over 500 peer-reviewed papers and received numerous accolades, including the APS William James Fellow Award (2023) and the Huttenlocher Award (2021). Education: PhD in Linguistics (1976, University of Bonn), Habilitation in Psychology (1986, Justus Liebig University Giessen). Affiliations: Founding Director of the Max Planck Institute for Human Cognitive and Brain Sciences since 1994. Served as Vice-President of the Max Planck Society (2014–2020). Research Interests: Evolution of language networks, syntax processing, neuroanatomical correlates of language, and developmental trajectories of cognitive abilities. Awards: Includes Leibniz Prize (1997), Wilhelm Wundt Medal (2018), and Gauss Medal (2011). Her recent work explores the neural underpinnings of syntax in humans and primates, with studies on chimpanzee communication and cross-linguistic brain plasticity. Friederici has pioneered methods in neuroimaging and electrophysiology to dissect language networks.

Sheng LiView profile

Adjunct Assistant Professor

• Machine Learning
• Artificial Intelligence
• Computer Vision
• +4 more

Sheng Li is an Adjunct Assistant Professor in the School of Computing at the University of Georgia (UGA). He holds roles such as Graduate Program Faculty and Courtesy Faculty in the Institute of Bioinformatics. Previously, he served as an Assistant Professor at UGA from August 2018 to July 2022. His research focuses on Machine Learning, Computer Vision, Data Mining, Natural Language Processing, Causal Inference, and User Modeling. Li earned his Ph.D. in Computer Engineering from Northeastern University in 2017, following degrees from Nanjing Institute of Post and Telecommunications in China. His work bridges theoretical advancements and practical applications, including AI solutions for healthcare (e.g., medication adherence monitoring), computer vision for wildlife tracking (fish re-identification), and causal inference methodologies. He has received notable awards like the Fred C. Davison Early Career Scholar Award (2022) and the Aharon Katzir Young Investigator Award (2020). His research is funded by grants from agencies such as the US Department of Defense and NIH, supporting projects like Knowledge-Guided Scene Graph Generation and Reasoning for Visual Understanding. Li’s publications span top venues in AI and computer science, addressing challenges in domain adaptation, trustworthy AI, and multimodal learning. He has collaborated on interdisciplinary projects, including bioinformatics and agricultural NLP. His contributions emphasize both technical innovation and societal impact.

• Statistics
• Data Modeling
• Medical Research
• +3 more

Hassan Doosti is a Senior Lecturer at the School of Mathematical and Physical Sciences, Macquarie University. His research focuses on statistical methodologies, particularly in flexible modeling techniques for complex datasets, with applications in medical studies and business analytics. He has authored or edited books such as Flexible Nonparametric Curve Estimation and Ethics in Statistics: Opportunities and Challenges . Research Interests Nonparametric estimation including wavelet methods and density estimation Statistical modeling of health-related data (e.g., colorectal cancer, stroke) Development of novel statistical algorithms (e.g., censored regression, numerical dependency analysis) Ethical considerations in data analysis for medical sciences Recent Projects Outside Studies Program (2025) APRIntern: Disease Risk Modelling (2019) Key Contributions His work bridges theoretical statistics with practical applications, including: Development of adaptive wavelet quantile density estimation techniques Statistical analysis of neurological and oncological data Advancing methods for handling censored and zero-inflated datasets Awards Recipient of the Faculty of Science and Engineering Award for Inter-School Collaboration (2023) for collaborative research excellence. Professional Activities Editor of multiple peer-reviewed books and active contributor to interdisciplinary projects involving healthcare, data science, and biostatistics.

• Neuro-Oncology
• Neurology
• Hematology
• +3 more

David Cachia is a Professor in the Department of Medicine at UMass Chan Medical School, affiliated with the T.H. Chan School of Medicine's Hematology/Oncology division. He earned his MD from the University of Malta Medical School in Malta. His research focuses on neuro-oncology, particularly brain tumors such as meningiomas, glioblastoma, and ependymomas, with an emphasis on clinical trials, molecular mechanisms, and translational therapies. He has contributed to over 100 peer-reviewed publications and collaborates with multidisciplinary teams including neurosurgery, radiology, and oncology. Key research areas include targeted therapies for NF2-related tumors, caregiver support in neuro-oncology, and optimizing treatment protocols for recurrent high-grade gliomas. His work bridges basic science (e.g., drug sensitivity studies) with clinical practice (e.g., phase II trials). Notable collaborations include the RANO-Cares working group and the Alliance A071401 trial initiative. Publications span topics like imaging biomarkers, EEG features in metastatic brain tumors, and standardized tissue preservation methods. He actively participates in institutional tumor boards for rare CNS tumors and explores synergistic drug combinations to enhance glioblastoma treatment efficacy.

Catherine JutzelerView profile

Assistant Professor

• Spinal Cord Injury
• Pain Management
• Machine Learning in Medicine
• +3 more

Prof. Dr. Catherine Jutzeler is an Assistant Professor at the Department of Health Sciences and Technology (D-HEST) at ETH Zurich. Her research focuses on spinal cord injury, pain management, and the application of machine learning in medical diagnostics and rehabilitation. She specializes in developing advanced computational methods for analyzing spinal MRI scans, predicting clinical outcomes, and optimizing therapeutic interventions. Her work bridges biomedical engineering and clinical neuroscience, with a strong emphasis on translational research. Key areas include neuroimaging analysis, serological biomarker discovery, and the development of predictive models for neurological recovery. Recent studies have explored the impact of pharmacological treatments, racial disparities in biomarker responses, and biomechanical thresholds in cervical myelopathy. Prof. Jutzeler collaborates extensively on interdisciplinary projects, integrating clinical data with machine learning frameworks. She is particularly known for pioneering diffusion-based models for lumbar spine segmentation and advancing data standards in spinal cord injury research. Her contributions aim to improve diagnostic accuracy and personalize patient care in neurotrauma and chronic pain management.

• Speech Recognition
• Natural Language Processing
• Machine Learning
• +3 more

Tien Ping Tan is an experienced researcher specializing in speech recognition , natural language processing , and machine learning applications. With a PhD in Automatic Speech Recognition for Non-Native Speakers from Joseph Fourier University (2008), his career spans two decades of impactful contributions across multiple domains.

Durjoy LahiriView profile

Assistant Professor

• Alzheimer’s Disease
• Fluid Biomarkers
• Neuromodulation Techniques (e.g., tDCS)
• +6 more

Dr. Durjoy Lahiri is an Assistant Professor in the Department of Medicine at Queen’s University, affiliated with the Faculty of Health Sciences. He holds a MBBS, MD, and DM from institutions in India, including Nil Ratan Sircar Medical College and the Institute of Postgraduate Medical Education and Research (IPGME&R). His clinical expertise spans primary cognitive and behavioral disorders (e.g., Alzheimer’s Disease, Fronto-Temporal Dementia) and cognitive dysfunctions in neurological conditions like ALS and atypical parkinsonism. He completed a clinical fellowship at Baycrest Academy for Research and Education (affiliated with the University of Toronto) as a Bresver Family Fellow. Dr. Lahiri’s research focuses on fluid biomarkers, emerging Alzheimer’s therapies, and neuromodulation techniques like Transcranial Direct Current Stimulation (tDCS). He has published extensively on dementia, cognitive dysfunction, and neurological disorders. Key awards include the Sandra Black Award and Young Investigator Award from the Academy of Aphasia. His teaching activities are extensive, with involvement in medical and neurology residency programs. Clinically, he specializes in telemedicine for behavioral dysfunctions in dementia, having contributed to the Virtual Behavioral Medicine (VBM) program at Baycrest. He has also received travel scholarships and grants supporting his academic contributions.

• Musicology
• Music and Brain Research
• Performance Evaluation
• +5 more

Assoc. Prof. Dr. Şevki Özer Akçay is an Associate Professor at the Department of Music Sciences, Faculty of Fine Arts, Atatürk University. He holds a PhD from Gazi University (2015) and has conducted extensive research in musicology, neuromusicology, music education, and the relationship between music and brain activity. His work includes developing performance assessment scales for guitar education and exploring cognitive approaches in music research. He teaches courses such as individual guitar performance, music sociology, and scientific research methods at both undergraduate and graduate levels. His academic activities include jury participation, editorial roles in scientific journals, and leadership in research projects. Notable contributions include studies on hemodynamic brain activity during guitar performance using fNIRS technology and analyses of music preferences among university students. Dr. Akçay has composed original music for theater and promotional films, arranged traditional Turkish music for guitar, and performed as a soloist in multiple concerts. His research spans music policy studies, music sociology, and interdisciplinary methodologies in musicology. His educational background includes a B.Ed. from Atatürk University (2007), M.Ed. from Atatürk University (2011), and PhD from Gazi University (2015), all in music education fields. He has advised five theses and participated in ten research projects.

Sergio López-SancioView profile

Researcher

• Psycholinguistics
• Natural Language Processing (NLP)
• Data Science
• +3 more

Sergio López-Sancio is a psycholinguist specializing in human language processing and Natural Language Processing (NLP). He holds a PhD from the University of the Basque Country (UPV/EHU), an MA in Linguistics from the same institution, and a BA in English Philology from the University of Oviedo, where he earned the National Award for Excellence in Academic Performance and an Outstanding Degree Award for his honors thesis on the subjunctive mood in English and Spanish. His research focuses on real-time dependency processing, combining EEG and behavioral methods to study syntactic structures across languages. He has presented at prestigious conferences such as the Linguistic Society of America and AMLaP, addressing topics like dependency locality, island effects, and cross-linguistic variation in Basque, Spanish, and Italian. López-Sancio has contributed to research projects including OVO: Originating Variation from Order (MINECO-funded), The Bilingual Mind (Basque Government), and AThEME (EU-funded), totaling over €5M in funding. His current role at Amazon involves enhancing Alexa's Spanish language understanding through NLP tools. Key Awards: National Award for Excellence in Academic Performance, Outstanding Degree Award, Outstanding Cum Laude Dissertation Research Themes: Dependency Parsing, Locality Effects, Cognitive Modeling, Cross-Linguistic Syntax

Elmar RueckertView profile

Professor

• Cyber-Physical Systems
• Robotics
• Machine Learning
• +9 more

Prof. Elmar Rueckert is the Chair of the Cyber-Physical-Systems Institute at Montanuniversität Leoben in Austria since March 2021. He holds a PhD in Computer Science from TU Graz (2014) and previously served as a Senior Researcher at TU Darmstadt (2014–2018) and Assistant Professor at the University of Lübeck (2018–2021). His research focuses on Cyber-Physical Systems, Robotics, Machine Learning, and Human Motor Control, with applications in industrial automation, healthcare robotics, and environmental sustainability. Key research interests include stochastic machine/deep learning, reinforcement learning, brain-computer interfaces, and tactile learning. His work bridges robotics, neuroscience, and AI, emphasizing practical applications such as autonomous navigation, exoskeleton control, and sensor-based recycling technologies. Rueckert has led projects like the AI Robot Lab funded by Robert Bosch Stiftung and the KIRAMET recycling initiative. Recent publications highlight advancements in neural networks for industrial condition monitoring, multimodal robotic learning, and environmental infrastructure modeling. Awards include the German Young Researcher Award (2019) and the Advanced Robotics Best Paper Award (2018). Rueckert advises a team of researchers, including notable students like Daniel Tanneberg (PhD graduate, 2019) and Linus Nwankwo (best student paper winner, 2023). His lab develops open-source tools like ROMR and collaborates on datasets like EnvoDat for robotic spatial reasoning.

• Neuroscience
• Microbiome Analysis
• Environmental Health
• +3 more

Yu Sun is an Associate Research Scientist in Neuroscience at Yale School of Medicine (Yale University). Their research focuses on interdisciplinary areas including neurodegenerative biomarkers, microbiome-metabolome interactions, environmental health impacts, and neuroinflammation mechanisms. Sun has contributed to high-impact studies such as the Aging Biomarker Consortium framework for auditory system aging and novel PET tracer development for oxidative stress imaging. Their work bridges molecular biology, biomedical engineering, and computational methods to address complex health challenges. Research highlights include investigating microglial regulation of cerebrovascular reactivity and environmental determinants of childhood rhinitis. Sun has published extensively in prestigious journals like Nature Biomedical Engineering and Cell Research, with a strong emphasis on translational neuroscience and systems biology approaches.

• Alzheimer's Disease
• Dementia
• Clinical Trials
• +3 more

Howard Feldman, MD, FRCPC, FAAN is an Adjunct Professor in the Department of Neurology at Yale School of Medicine, Yale University. His research focuses on Alzheimer’s disease and dementia, with a strong emphasis on clinical trials and biomarker development. He has contributed to major studies such as the evoke and evoke+ trials evaluating semaglutide, and has led initiatives like the Asian Cohort for Alzheimer Disease (ACAD) pilot study. His work spans drug discovery, therapeutic target validation, and translational medicine. Education: MD from McGill University Faculty of Medicine (1978). Research Interests: Alzheimer’s disease mechanisms, clinical trial design, plasma biomarkers, tau immunotherapy, and drug repurposing. His studies often integrate multidisciplinary approaches, including neuroimaging (PET/MRI) and pharmacokinetic analyses. Recent Article Trends: Focus on phase 2/3 clinical trials (e.g., semaglutide, benfotiamine, varoglutamstat), biomarker validation, and global demographic studies. Highlights include evaluating plasma biomarkers for trial design and analyzing regional differences in Alzheimer’s patient populations. Grants & Labs: Involved in multi-center collaborations and translational research programs. Key projects include the BenfoTeam trial (phase 2A/B for benfotiamine) and the ADAMANT tau immunotherapy trial.