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Maizie ZhouView profile

Assistant Professor

• Computational Genomics
• Bioinformatics
• Computational Neuroscience
• +6 more

Maizie Zhou is an Assistant Professor in Biomedical Engineering and Computer Science at Vanderbilt University’s School of Engineering. She holds dual PhDs in Computer Science (Stanford University) and Neuroscience (Wake Forest School of Medicine), with additional degrees from Wake Forest University and Huazhong University of Science and Technology. Her research focuses on computational genomics, bioinformatics, and machine learning applied to problems in cancer genomics, single-cell and spatial transcriptomics, and computational neuroscience. She leads the Zhou Lab, which develops algorithms for structural variant detection, neural circuit analysis, and integrative omics approaches. Recent work includes tools like VolcanoSV and stDyer, and she has received grants from NIH, Vanderbilt Brain Institute, and industry partnerships. Key achievements include VUSE Best Paper Awards, Global Engagement Travel Grants, and mentoring students in prestigious programs like the Provost’s Pathbreaking Discovery Award. Her lab also explores the neural underpinnings of cognitive maturation in primates, combining computational and experimental neuroscience. Education: PhDs in Computer Science (Stanford) and Neuroscience (Wake Forest), MS (Computer Science, Wake Forest), BS (Biotechnology, Huazhong). Research interests span computational genomics (e.g., structural variant detection, haplotype phasing), spatial transcriptomics (clustering, integration), and computational neuroscience (neural circuit dynamics, prefrontal cortex plasticity). Her lab’s tools address challenges in precision medicine, cancer genomics, and understanding adolescent brain development. Recent projects include NIH-funded work on spatial transcriptomics and collaborations with Dr. Meltzer’s lab on cancer genomics. Publications highlight advancements in bioinformatics tools and neural mechanisms, with trends toward multi-omics integration and algorithmic innovation in genomics. Awards include the Global Engagement Travel Grant and CCSB Accelerator Fund. Students under her mentorship have excelled in qualifying exams and travel grants, reflecting her impactful training program.

Tomaso A. PoggioView profile

Professor

• Computational Neuroscience
• Machine Learning
• Computer Vision
• +5 more

Tomaso A. Poggio is the Eugene McDermott Professor in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology , an investigator at the McGovern Institute for Brain Research , a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL) , and the director of both the MIT Center for Biological and Computational Learning (CBCL) and the multi-institutional Center for Brains, Minds and Machines (CBMM) . Research Interests Poggio’s research is fundamentally interdisciplinary, sitting at the intersection of computational neuroscience , machine learning , and computer vision . His work is driven by the conviction that learning is the core gateway to both biological intelligence and artificial systems. Current themes include: Mathematical foundations of statistical learning theory Engineering applications in computer vision, graphics, bioinformatics, and intelligent search Computational neuroscience of visual object recognition and the ventral stream of the visual cortex Scientific Awards & Honors Eugene McDermott Professorship, MIT Advising & Grants Over three decades, Poggio has advised a large cohort of doctoral and master’s students whose theses span machine learning, computer vision, neuroscience, and bioinformatics. Representative graduates include H. Jhuang, Stanley Bileschi, Jacob Bouvrie, Jennifer Louie, M. Kouh, Sayan Mukherjee, Ryan Rifkin, Alexander Rakhlin, Thomas Serre, Gene Yeo, and many others. His research has been continuously supported by major federal and private funding initiatives, most recently through the multi-institutional Center for Brains, Minds and Machines (CBMM) headquartered at the McGovern Institute since 2013. Laboratories & Teams Poggio directs the Poggio Lab (CBCL) at MIT, an interdisciplinary group comprising neuroscientists, computer scientists, mathematicians, and engineers. The lab collaborates closely with experimental neuroscientists to develop predictive computational theories of visual cortex function and to translate those insights into practical algorithms for computer vision and machine learning.

Joe PatonView profile

Professor

• Neural Mechanisms of Time
• Interval Timing
• Rodent Neurophysiology
• +5 more

Joe Paton is a Professor and Principal Investigator at the Champalimaud Neuroscience Programme, Champalimaud Foundation in Lisbon, Portugal. He leads the Paton Lab which focuses on understanding how animals determine which environmental cues are predictive of behaviorally relevant events, known as the credit assignment problem. His research combines behavioral experiments with neurophysiological recordings in rodents to investigate neural mechanisms of time perception and decision making. Dr. Paton's research interests center on interval timing, temporal processing in the brain, and the neural basis of learning. His work particularly examines how the striatum and dopamine systems contribute to time perception and how animals solve the credit assignment problem through statistical inference in the time domain. His lab employs advanced techniques including optogenetics, neural recordings, and computational modeling to address these questions. Analysis of Dr. Paton's recent publications reveals a strong focus on striatal function in timing processes, with particular attention to how neural populations encode temporal information. His work bridges behavioral neuroscience with computational approaches, demonstrating how timing mechanisms influence decision making and learning processes. The research spans multiple levels from cellular mechanisms to behavioral outputs. Midbrain dopamine neurons control judgment of time (2016) Striatal dynamics explain duration judgments (2015) A Scalable Population Code for Time in the Striatum (2015) The Neural Basis of Timing: Distributed Mechanisms for Diverse Functions (2018) Dr. Paton has mentored numerous PhD students and postdoctoral researchers through the INDP (International Neuroscience Doctoral Program) and supervises a diverse team including research technicians, postdocs, and students. His lab has contributed significantly to understanding the neural basis of time perception and its role in learning and decision making. The Paton Lab also develops experimental tools and frameworks like Bonsai for behavioral neuroscience research.

Ramana VinjamuriView profile

Associate Professor

• Brain-Machine Interfaces
• Neuroprosthetics and Exoskeletons
• Machine Learning
• +4 more

Ramana Vinjamuri is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He holds a secondary appointment as Visiting Professor at the Indian Institute of Technology, Hyderabad, India. His academic journey includes a Ph.D. in Electrical Engineering from the University of Pittsburgh (2008), M.S. in Bioinstrumentation from Villanova University (2004), and B.Tech. in Electrical and Electronics Engineering from Kakatiya University (2002). Dr. Vinjamuri's research focuses on Brain-Machine Interfaces (BMIs) for upper-limb prostheses control , neuroprosthetics and exoskeletons , machine learning in motor control , and neurophysiological signal processing . His work extends synergy-based models to control 37-dimensional hand movements, addresses human-robot interaction through emotionally intelligent systems, and develops neurotechnologies for substance use disorder using wearable sensors and AI. NSF CAREER Award (2019) NSF IUCRC BRAIN Center Planning Grant (2020) Harvey N Davis Distinguished Teaching Assistant Professor Award (2018) His publications demonstrate expertise in EEG and EMG signal analysis , deep learning for motor decoding , synergy modeling , and humanoid robot control . The Vinjamuri Lab at UMBC involves graduate, undergraduate, and high school researchers, with international collaborations in India and the US.

• Neuroscience
• Artificial Intelligence
• Neuronal Modeling
• +5 more

Eilif B. MULLER is a Professor in the Department of Neurosciences at Université de Montréal, Principal Investigator of the Architectures of Biological Learning Lab (ABL-Lab) at CHU Sainte-Justine Research Center, and Associate Faculty at Mila (Quebec AI Institute). His work bridges neuroscience and artificial intelligence, focusing on understanding how sensory perception is learned in the neocortex through biophysical simulations and deep learning models. He holds affiliations with IVADO (Institute for Data Valorization) and contributes to strategic initiatives like the UNIQUE Québec Center. His research integrates empirical neurophysiology with computational models, exploring dendritic processing and synaptic plasticity to inform both biological understanding and AI advancements. Teaches NSC-6044 and NSC-6045 (Neuroscience Colloquia) at Université de Montréal. Leads projects on neocortical learning mechanisms and their implications for neurodevelopmental disorders. Recipient of grants from CRSNG (Natural Sciences and Engineering Research Council), FRSQ (Health Research Fund), and institutional funding. Publications span topics in computational neuroscience, neural network modeling, and interdisciplinary AI-neuroscience research. Collaborates extensively across institutions to advance large-scale brain simulations and data-driven models.

Dana BrooksView profile

Research Professor

• Biomedical Signal Processing
• Medical Imaging
• Statistical Signal Processing
• +8 more

Dana Brooks is a Research Professor in the Department of Electrical and Computer Engineering at Northeastern University, with affiliations in Bioengineering. He holds a PhD from Northeastern University (1991) and has received the Søren Buus Outstanding Research Award (2006). His primary research focuses on biomedical signal and image processing, medical imaging techniques (including MRI and electrocardiography), and neuromodulation technologies such as transcranial magnetic stimulation (TMS). He is also involved in protein conformation estimation using X-ray scattering and optimization algorithms for medical applications. Dr. Brooks leads the Biomedical Signals Processing Lab and collaborates with the Center for Integrative Biomedical Computing . His work bridges engineering and medicine, with recent grants including a $400K NSF MRI grant for advanced TMS systems and a $600K NSF grant for motor cortical organization studies. He has advised students like Setareh Ariafar (PhD’20) and contributed to innovations in image mosaicking for confocal microscopy and machine learning applications in dermatology. His publications span computational neuroscience, cardiac imaging, and uncertainty quantification in biomedical simulations. Notable achievements include developing algorithms for ECG imaging, optimizing TMS protocols, and creating tools like UncertainSCI for simulation reliability assessment.

Barbara NamerView profile

Adjunct Professor

• Translational Pain Research
• Neurophysiology
• Peripheral Nervous System
• +6 more

Barbara Namer is an Adjunct Professor at Friedrich-Alexander University Erlangen-Nuremberg and leads the IZKF-funded "Neuroscience: translational pain research" group at RWTH Aachen University Hospital. Her career spans 20+ years in neurophysiological pain research with clinical translations. Doctor of Medicine (2000-2004), Erlangen-Nuremberg Venia Legendi (Habilitation) in Physiology (2010) Adjunct Professor title (2018) Her research focuses on nociceptor mechanisms in diabetic neuropathy, migraine pathophysiology, and TRPA1 channel dynamics . Computational modeling and human microneurography techniques are central to her work. Key publication trends show expertise in peripheral nerve sensitization , diabetic pain mechanisms , translational pain modeling , and ion channel pharmacology . She has received multiple DGSS and German Neurology Society awards for her pain research. 2019 - DGSS Poster Award 2015 - DGSS Poster Award 2010 - EFIC Grünenthal Grant 2003 & 2018 - German Neurology Society Awards National and international collaborations include research stays in Norway and Sweden, with extensive grant funding from DFG and IZKF projects.

Anne DanielsenView profile

Professor

• Popular Music
• African-American Music
• Rhythm and Sound Analysis
• +5 more

Anne Danielsen is a Professor and Deputy Head at the RITMO Center for Interdisciplinary Studies of Rhythm, Time, and Motion at the University of Oslo. Her research bridges musicology, cognitive science, and interdisciplinary studies, focusing on rhythm, music production, and the intersection of music, media, and technology. University: University of Oslo Role: Professor Projects: TIME (NFR TOP RESEARCH), RITMO (NFR Center of Excellence) Danielsen’s work explores microrhythm , groove , and temporal perception in music, with a particular emphasis on popular and African-American music . She investigates how music cognition interacts with sonic features and body posture in performance, integrating psychological and acoustic analysis . Her recent projects include MusicLab Copenhagen , a dataset for interdisciplinary concert research, and studies on beta oscillations and pupil responses in groove perception. Danielsen collaborates across disciplines, examining how personality traits and genetic factors influence musical sensibility through twin studies. In music production , she analyzes how digital audio workstations transform rhythmic structures and investigates acoustic chamber design for sound experiments. Her research also addresses gender patterns in music mediation and the cultural implications of rhythmic aesthetics.

• Human-Machine Interaction
• User Experience
• Law and Rights in the Digital Society
• +7 more

Nuno Guimarães is a Full Professor at ISCTE – University Institute of Lisbon, affiliated with the Department of Information Science and Technology in the School of Technology and Architecture. He is also an Integrated Researcher at ISTAR-Iscte, where he leads the 'Digital Living Spaces' research group. He previously served as Dean of the Faculty of Sciences at the University of Lisbon (2003–2009), Pro-Rector (2012–2013), and Vice-Rector (2014–2018) at ISCTE-IUL, demonstrating extensive academic leadership. Aggregation in Computing, University of Lisbon (1999) PhD in Electrical and Computer Engineering, Instituto Superior Técnico, Technical University of Lisbon (1992) MSc in Electrical and Computer Engineering, Instituto Superior Técnico (1987) BSc in Electrical Engineering, Instituto Superior Técnico (1983) His research focuses on human-machine interaction, user experience, and the intersection of digital technologies with law, rights, and cultural diversity. He explores how technology can be designed to be more inclusive, ethical, and cognitively supportive, often using neurophysiological methods such as EEG to assess usability and mental workload. His recent publications (2024–2009) show a consistent trajectory in interdisciplinary research combining computer science, cognitive science, and legal informatics. Key themes include data privacy in microservices, normative systems in digital society, EEG-based usability analysis, and interactive learning environments. The works demonstrate a strong emphasis on practical tools, real-world applications, and the societal implications of digital technologies. ACM Senior Member (since 2012) Chair of the Board of ISOC (PT) (2021–2025) Guimarães has held numerous academic management roles, including Director of ISTAR-Iscte and the Master’s program in Information Systems Management. While no direct student advising list is provided, his extensive collaborations and leadership in research projects suggest active mentorship. His work bridges technical innovation with social responsibility, particularly in digital rights and inclusive design. He has led and contributed to research in areas such as interactive architecture, media façades, digital talking books, and judicial dialogue systems. His team, 'Digital Living Spaces,' focuses on creating intelligent, adaptive environments that respond to human behavior and cognitive states, integrating insights from architecture, computing, and neuroscience.

Sven ApelView profile

Professor

• Software Engineering
• Software Variability and Configuration
• AI-based Program Generation and Optimization
• +7 more

Sven Apel is Professor of Computer Science at Saarland University, where he holds the Chair of Software Engineering and directs the Saarbrücken Graduate School of Computer Science within the Saarland Informatics Campus. His research aims to advance software engineering into an era of intensive automation by developing methods, tools, and theories for building efficient, reliable, and maintainable software systems, with a strong emphasis on the human factor and interdisciplinary inquiry. His primary research interests include software variability and configuration, AI-based program generation and optimization, socio-technical software analysis, and the application of empirical and neurophysiological methods to study program comprehension. He actively collaborates with industry partners such as Siemens AG, Bosch Engineering, and Airbus Helicopters to apply his research in real-world contexts. His recent publications demonstrate a strong trend towards integrating artificial intelligence and neurocognitive methods into software engineering, focusing on configurable systems, performance modeling, debugging processes, and the scientific validity of empirical studies. His work spans top venues like ICSE, FSE, ASE, and IEEE TSE. ERC Advanced Grant “Brains On Code” ASE Fellow ACM Distinguished Member Hugo Junkers Award for Research and Innovation Heisenberg Professorship (DFG) Emmy-Noether Fellowship (DFG) Best Doctoral Dissertation Awards (University of Magdeburg, Ernst-Denert Foundation, 2007) Most Influential Paper Awards (SPLC'19, ICPC'22, GPCE'23) ACM SIGSOFT Distinguished Paper Awards (ICSE'15, ICSE'21) Best Paper Awards (SPLC'11, Modularity'15, Academy of Management'18) Distinguished Reviewer Awards (ASE'18, ICSE'24, FSE'24) Sven Apel has secured significant research funding, including an ERC Advanced Grant (€2.5M) and multiple DFG grants as Principal Investigator and Project Leader. He has advised numerous PhD and Master’s students and is actively involved in the academic community through program committees for major conferences like ICSE, FSE, and ASE. His work is conducted within a collaborative environment that includes close partnerships with researchers at the Max Planck Institute for Informatics and other institutions within the Saarland Informatics Campus.

Christophe GrovaView profile

Professor

• Biomedical Engineering
• Neuroscience
• Epilepsy Research
• +5 more

Christophe Grova , Professor in the Department of Physics at Concordia University and scientific lead of the PERFORM physiology platform , is a multidisciplinary researcher at the intersection of Biomedical Engineering , Neuroscience , and Medical Physics . He directs the Multimodal Functional Imaging Laboratory , focusing on advanced neuroimaging techniques like EEG/MEG , fMRI , and fNIRS to study brain mechanisms in epilepsy and sleep . His work emphasizes multimodal data fusion to uncover neurovascular coupling and functional connectivity patterns, with software developments such as MEM and NIRSTORM enhancing analysis precision. Key Research Areas : Epilepsy, Sleep Studies, Neuroimaging, Computational Neuroscience, Multimodal Data Fusion Affiliations : Full Professor at Concordia University (Physics), Adjunct Professor at McGill University (Biomedical Engineering, Neurology and Neurosurgery). Scientific Awards : Not explicitly listed in the provided text. Software Contributions : Developed MEM (EEG/MEG source localization) and NIRSTORM (fNIRS analysis) for open-source platforms like Brainstorm .

Christian TetzlaffView profile

Professor

• Computational Neuroscience
• Synaptic Physiology
• Neuromorphic Engineering
• +4 more

Prof. Christian Tetzlaff holds a W2 Professorship at the Department for Neuro- and Sensory Physiology, University Medical Center Göttingen. He leads the Computational Synaptic Physiology group, focusing on integrating computational methods to understand neural systems' principles and translating these into technologies like robotics and neuromorphic engineering. His work spans scales from synaptic protein interactions to large neural networks, leveraging disciplines such as nonlinear dynamics and machine learning. Educational Background: 2009: Diploma in Physics, Georg-August University Göttingen 2013: PhD in Physics (Dr.rer.nat.), Georg-August University Göttingen Research Leadership & Grants: Principal Investigator in EU Horizon 2020 Projects (Plan4Act, ADOPD, Human Brain Project's FIPPA) Lead in DFG-funded SFB 1286 (Quantitative Synaptology) INRC member (Intel Neuromorphic Research Community) BMBF-funded KISSKI project (2022–present) Research Interests: His lab explores synaptic mechanisms underlying learning, memory consolidation via synaptic tagging-and-capture, and neuromorphic hardware implementations. Recent work emphasizes calcium signaling in synapses, memristive devices for synaptic working memory, and robust trajectory generation using neuromorphic chips like Loihi. Affiliations: Co-coordinator of Plan4Act (2017–2021) and active in the Göttingen Graduate Center for Neurosciences (GGNB). Collaborates globally with institutions like the Weizmann Institute and Columbia University. Laboratory: Visit tetzlab.com for lab activities and open-source tools like Plastic Arbor .

Christopher MyersView profile

Adjunct Professor

• Biological Physics
• Complex Systems
• Networks
• +9 more

Christopher Myers is an Adjunct Professor in the Department of Physics at Cornell University and a Senior Research Associate at the Cornell Center for Advanced Computing. He is also a member of the graduate faculty in Physics, Computational Biology, Applied Mathematics, and Computational Science and Engineering. His research spans multiple disciplines, connecting physics, biology, and computational science. Myers earned his B.A. in History from Yale University in 1984 and his Ph.D. in Physics from Cornell University in 1991. His academic journey includes postdoctoral positions at UC Santa Barbara and the Cornell Theory Center, followed by various research roles at Cornell institutions including the Institute of Biotechnology and arXiv.org (where he served as Scientific Director from 2014-2016). Myers' research focuses on complex systems at the intersection of physics, biology, and computational science. His primary areas include infectious disease dynamics and host-pathogen interactions, theoretical and computational systems biology, biological information processing, dynamics and cascades on networks, and the structure and dynamics of intracellular networks. He has made significant contributions to understanding how complex systems behave across multiple scales, from molecular networks to ecological communities. His work often employs computational approaches to model and analyze biological phenomena. His recent publications (2020-2024) show a strong trend toward interdisciplinary research connecting computational methods with biological and ecological systems. There's a clear focus on network approaches to understanding disease transmission, particularly in plant-pollinator communities, as well as developing new computational methods for analyzing complex systems. His work increasingly integrates machine learning techniques with traditional modeling approaches to address complex biological questions. Myers has been actively involved in teaching and mentoring, having served as an Adjunct Professor since 2010 and teaching courses such as 'Computational Methods for Complex Systems' (Physics 7682). He has also developed and taught workshops on Python for high performance computing, data science, and AI with deep learning through Cornell's various educational programs including CVW and eCornell. His research has been conducted through multiple labs and teams, including the Cornell Center for Advanced Computing (current), the Institute of Biotechnology (2007-2017), and the Cornell Theory Center (1993-1997, 1998-2007). These teams have focused on computational approaches to biological problems, with particular emphasis on systems biology, infectious disease modeling, and software development for scientific computing.

Sebastian MichelmannView profile

Assistant Professor

• Cognitive Neuroscience
• Memory Processes
• Neurophysiology
• +7 more

Sebastian Michelmann is an Assistant Professor of Psychology at New York University's College of Arts and Science. His research focuses on understanding how temporal dynamic content is neurally represented and processed in episodic memory, with particular emphasis on fast-timescale memory retrieval mechanisms and their interaction with event knowledge. He employs electrophysiological methods (EEG/MEG), computational modeling, and behavioral experiments to study memory formation under naturalistic conditions. Education: PhD in Psychology from the University of Birmingham (2018), thesis awarded the Glushko Dissertation Prize (2020) Master's (Diploma) in Psychology from Julius-Maximilians-Universitaet Wuerzburg (2014) Postdoctoral research at Princeton University (2018–2023) under Professors Ken Norman and Uri Hasson Research interests include neural oscillations, event segmentation, and the role of generalized event knowledge in memory retrieval. His work bridges cognitive neuroscience with computational approaches, exploring how the brain encodes, stores, and retrieves temporally precise information. Key research directions involve studying how memory processes are embedded in continuous experience and developing tools to analyze neural data (e.g., intracranial EEG re-referencing). Recent studies explore event boundary detection using large language models and investigate the neural correlates of natural language comprehension through ECoG datasets. Scientific Awards: Glushko Dissertation Prize (2020) Laboratory activities focus on future projects combining electrophysiology with computational modeling to understand interactive dynamics of episodic memory. Collaborative efforts include developing semi-automatic alignment tools and cloud-based neuroimaging frameworks.

Grzegorz J. NalepaView profile

Professor

• Artificial Intelligence
• Affective Computing
• Context-Aware Systems
• +9 more

Prof. Grzegorz J. Nalepa holds the position of Full Professor at the Faculty of Physics, Astronomy, and Applied Computer Science, Jagiellonian University, Poland. He leads the Jagiellonian Human-Centered Artificial Intelligence Lab and is involved in international projects such as the CHISTERA XPM initiative on explainable AI in predictive maintenance. His academic journey includes a PhD (2004), habilitation (2012), and a philosophy MA (2012). Research focuses on AI, affective computing, context-aware systems, and explainable AI (XAI). He has authored over 200 papers, two monographs, and edited volumes. Key projects include the BIRAFFE2 dataset for emotion-based personalization and the GEIST team's semantic wiki tools. Holds leadership roles in conferences (e.g., ECAI 2023) and serves on editorial boards of journals like Sensors and Intelligent Sensors Section . Awards include the 2018 Outstanding Monograph Prize and multiple AGH-UST Rector's Prizes for scientific achievements. Advises PhD and master students, supervising 36 MSc theses. Active in professional organizations like the Polish Alliance for AI and the IEEE Computational Collective Intelligence TC. His contributions span industrial collaborations, software tools (e.g., InXAI, LUX, KnAC), and international research networks.