Breakout Session Bios
Ishita Basu
D. Ishita Basu is a neural engineer with more than a decade of experience in brain signal analysis and modelling. Her research uses techniques from engineering and computational neuroscience to design innovative treatment paradigms for major neurological and psychiatric disorders. Born and brought up on the east coast of India, Ishita came to Chicago in 2006, where she received her PhD from the University of Illinois. She went on to complete postdoctoral fellowships at the Johns Hopkins University and Massachusetts General Hospital before taking her current position as an Assistant Professor in the Neurosurgery department at the University of Cincinnati. Her future vison is to integrate a diverse group of biomedical engineers, neuroscientists, psychiatrists, and medical students to advance the field of neural engineering and neuromodulation in mental disorders.
Stephanie Cernera
Dr. Stephanie Cernera is a postdoctoral scholar in Dr. Philip Starr’s laboratory at the University of California, San Francisco. Her project focuses on neural decoding of behavioral states using multimodal data collection (i.e., video kinematics and accelerometry) in freely moving patients with dystonia. Prior to arriving at UCSF, she earned her PhD in Biomedical Engineering at the University of Florida, in which her dissertation involved the development of a sensor-driven closed-loop deep brain stimulation paradigm in patients with essential tremor.
Paul Cisek
Paul Cisek is a full professor in the Department of Neuroscience at the University of Montreal. He has a background in computer science and artificial intelligence, doctoral training in computational neuroscience with Stephen Grossberg and Daniel Bullock, and postdoctoral training in neurophysiological recording in non-human primates with Stephen Scott and John Kalaska. His work combines these techniques into an interdisciplinary approach to understanding how the brain controls our interactions with the world. In particular, his theoretical work suggests that the brain is organized as a system of parallel sensorimotor streams that have been differentiated and elaborated over millions of years of evolution, and his empirical work demonstrates the neural dynamics of how potential actions are specified and how they compete in the cortical and subcortical circuits of humans and other primates.
Tim Dunn
Tim Dunn is an assistant professor of biomedical engineering at Duke University, where he works on understanding the brain and in health and disease using new platforms for animal behavior quantification. Tim is the creator and lead developer of DANNCE, a system for 3D pose estimation in freely moving laboratory. In addition to advancing methods for behavioral quantification, his lab is using these methods to study Parkinson’s disease, stroke, and autism spectrum disorders. Tim received his PhD from Harvard in 2015, where he studied the neural basis of larval zebrafish behavior.
Sara Goering
Sara Goering is Professor of Philosophy at the University of Washington, Seattle, where she co-leads the neuroethics group at the UW Center for Neurotechnology, and has affiliations with the UW Program on Ethics and the Disability Studies Program. She is co-PI with Eran Klein for an NIH R01 on brain computer interfaces and human agency. Her work includes normative philosophical argumentation in bioethics and neuroethics, as well as empirical work focused on understanding the lived experience of users of neural devices.
Wayne Goodman
Wayne Goodman, MD, D.C and Irene Ellwood Professor and Chair of the Menninger Department of Psychiatry and Behavioral Sciences at Baylor College of Medicine, specializes in Obsessive-Compulsive Disorder (OCD) and Deep Brain Stimulation (DBS) for intractable psychiatric illnesses. He is the principal developer of the Yale-Brown Obsessive Compulsive Scale (Y-BOCS), the gold standard for assessing OCD, and co-founder of the International OCD Foundation, the major advocacy group for patients with OCD. Prior to joining Baylor, he held senior administrative positions at Mount Sinai Hospital in NY, NIMH, and the University of Florida. He graduated from Columbia University with a degree in Electrical Engineering, received his medical degree from Boston University School of Medicine and completed his internship, residency, and research fellowship at Yale School of Medicine where he remained on faculty for 7 years. Dr. Goodman has received numerous awards and has published over 300 peer-reviewed articles with an h-index = 100. He is currently a Principal Investigator on grants from NIH’s BRAIN initiative including one on developing Adaptive DBS for OCD.
Aysegul Gunduz
Dr. Aysegul “Ayse” Gunduz is an Associate Professor in the J. Crayton Pruitt Family Department of Biomedical Engineering at the University of Florida. Her research interests include neural interfacing, neural signal processing, neuromodulation, neurological disorders, as well as cortical and deep brain stimulation in human subjects. She is the recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE, 2019), National Science Foundation Early CAREER Award (2016), and International Academy of Medical and Biological Engineering Early Career Award (2015).
Kim Hoke
Kim Hoke is a Professor of Biology at Colorado State University. After undergraduate degrees in Physics and Biology, Kim received her Ph.D. in Neurosciences at Stanford University by applying molecular and cellular approaches to study photoreceptor development in a cichlid fish. As a postdoctoral fellow at the Smithsonian Tropical Research Institute and University of Texas at Austin, Kim studied neural systems underlying acoustic communication in frogs. She extended her work on auditory system evolution as a new faculty member when she initiated a research project focused on the evolved loss of middle ears in toads. Her lab also began a line of research examining the genetic, molecular, and neural substrates shaping the evolution of social and anti predator decisions in Trinidadian guppies. Today, the lab adopts integrative approaches to link variation in natural behaviors among individuals, populations, and species to developmental, genetic, and physiological mechanisms. Kim is also passionate about mentoring, teaching, cooking, and being outdoors in the mountains.
Ann Kennedy
Ann Kennedy is a theoretical neuroscientist investigating neural computation and the structure of behavior. She is an Assistant Professor in the Department of Neuroscience at Northwestern University Feinberg School of Medicine. She was previously a postdoctoral researcher in the David Anderson research group at Caltech, where she worked with experimentalist lab members to characterize the dynamics of hypothalamic circuits that governs social and fear behaviors. She also worked on automated classification of social behaviors in interacting mice, with members of the lab of Pietro Perona. She earned her PhD with Larry Abbott at the Center for Theoretical Neuroscience at Columbia University, studying neural representations and learning in two cerebellum-like structures: the electrosensory lobe of the electric fish, and the Drosophila mushroom body. She is broadly interested in how the representation of sensory and internal variables by neural populations shapes the brain’s capacity for learning, decision-making, and control of goal-directed behavior.
Wyatt Korff
Wyatt Korff is the Director of Project Teams at HHMI’s Janelia Research Campus. Project Teams bring together scientists of many different backgrounds to tackle long-term high risk but high reward efforts that are unlikely to be successful in the academic ecosystem. Some examples are the GENIE Project Team which developed a family of calcium sensors widely used in neuroscience, the FlyLight Project Team, which produced a library of transgenic fruit flies, and the FlyEM Project Team which has produced the largest animal connectome to date. These tools, datasets, and reagents help Janelia fulfill its mission of open and collaborative science. In addition, Wyatt co-founded ICOR, an effort to develop an evidence-based framework that supports this mission more broadly.
Wyatt received his Ph.D. in 2005 from the Department of Integrative Biology at the University of California, Berkeley. His research focused on understanding how terrestrial animals move over complex substrates, specifically the biomechanics of lizards running on sand and other natural environments. This work was the catalyst for the co-founding of a field that intersects granular physics and biology. He moved to the California Institute of Technology in the Department of Bioengineering with Michael Dickinson, to study how the nervous system controls power output in the flight system of Drosophila melanogaster during his postdoctoral fellowship. He came to Janelia in 2009 to lead a Project Team that developed neurogenetic screens of fly behavior and now oversees the Project Team portfolio. Wyatt has taught at the Neural Systems and Behavior at the MBL in Woods Hole, Friday Harbor Labs at University of Washington and at Berkeley.
James Liao
James C. Liao is an Associate Professor of Biology at the University of Florida and the Whitney Laboratory for Marine Bioscience, a UF University Term Professor, and Affiliate Professor in the Clayton Pruitt Family Department of Biomedical Engineering. His research integrates approaches from engineering, neuroscience and physiology to understand the fundamental principles of animal sensing and locomotion. In particular, he is interested in understanding how fishes behave from the perspective of multiple biological levels, from single neurons to group behavior. He is a Research Associate at the American Museum of Natural History and an Affiliate Curator of Ichthyology at the Florida Museum of Natural History. James received his B.A. from Wesleyan University (magna cum laude) and his M.A. and Ph.D. from Harvard University. He was then an NIH NRSA postdoc and Research Associate in the Department of Neurobiology and Behavior at Cornell University. He has been recognized by the Derek Bok Center for Excellence in Teaching at Harvard and is the Program Officer in the Division of Comparative Biomechanics for the Society of Integrative and Comparative Biology.
Mackenzie Mathis
Prof. Mackenzie Mathis is the Bertarelli Foundation Chair of Integrative Neuroscience and an Assistant Professor at the Swiss Federal Institute of Technology, Lausanne (EPFL). Following the award of her PhD at Harvard University in 2017 with Prof. Naoshige Uchida, she was awarded the prestigious Rowland Fellowship at Harvard to start her independent laboratory (2017-2020). Before starting her group, she worked with Prof. Matthias Bethge at the University of Tübingen in the summer of 2017 with the support of the Women & the Brain Project ALS Fellowship. She is an ELLIS Scholar, a former NSF Graduate Fellow, and her work has been featured in the news at Bloomberg BusinessWeek, Nature, and The Atlantic. She was awarded the FENS EJN Young Investigator Prize 2022.
Her lab works on mechanisms underlying adaptive behavior in intelligent systems. Specifically, the laboratory combines machine learning, computer vision, and experimental work in rodents with the combined goal of understanding the neural basis of adaptive motor control.
Cory Miller
Dr. Cory Miller received in PhD from Harvard University and was a post-doctoral fellow in the Department of Biomedical Engineering at Johns Hopkins University before joining the faculty at the University of California San Diego, where he is currently an Associate Professor. His primary research interests are in the neural basis of natural behavior in primates. Research in his lab currently focuses on several lines of work in marmoset monkeys, including social communication, exploration & navigation and active vision.
Louis-Philippe Morency
Louise-Phillipe Morency is a tenure-track Faculty at CMU Language Technology Institute where I lead the Multimodal Communication and Machine Learning Laboratory (MultiComp Lab). He was previously Research Faculty at USC Computer Science Department. He received my Ph.D. in Computer Science from MIT Computer Science and Artificial Intelligence Laboratory.
His research focuses on building the computational foundations to enable computers with the abilities to analyze, recognize and predict subtle human communicative behaviors during social interactions. Central to this research effort is the technical challenge of multimodal machine learning: mathematical foundation to study heterogeneous multimodal data and the contingency often found between modalities. This multi-disciplinary research topic overlaps the fields of multimodal interaction, social psychology, computer vision, machine learning and artificial intelligence, and has many applications in areas as diverse as medicine, robotics and education.
His research focuses on building the computational foundations to enable computers with the abilities to analyze, recognize and predict subtle human communicative behaviors during social interactions. Central to this research effort is the technical challenge of multimodal machine learning: mathematical foundation to study heterogeneous multimodal data and the contingency often found between modalities. This multi-disciplinary research topic overlaps the fields of multimodal interaction, social psychology, computer vision, machine learning and artificial intelligence, and has many applications in areas as diverse as medicine, robotics and education.
Alex Ophir
Alexander (Alex) Ophir studied psychology and anthropology at the University of Texas, at Austin. He earned his PhD in experimental psychology (animal behavior) at McMaster University in 2004, and was a postdoctoral associate at the University of Florida, where he studied behavioral ecology and neurobiology of social behavior. Dr. Ophir is now an Associate Professor in the Department of Psychology at Cornell University, where he has developed an active research group, motivated to understand the proximate control of social behavior and the ultimate consequences of social and cognitive systems. Dr. Ophir’s work is conducted in the laboratory and field (in the USA and Tanzania). Ophir’s current work focuses on rodents (prairie voles and African giant pouched rats), but he has worked with other species including frogs, fish, and birds. Dr. Ophir’s interests rest at the interface between the brain and behavior, where animals must react to internal and external forces to successfully navigate their social world. His research program focuses on three central questions: (1) how does the postnatal social environment shape adult behavior (e.g., social cognition & reproductive decisions) and neural phenotype (e.g., nonapeptides – like oxytocin and vasopressin), (2) how does the social brain shape mating decisions, with a focus on monogamy and alternative mating tactics, socio-spatial memory, social recognition, attachment, aggression, and parental care, and (3) what are the genomic and neural correlates of individual variation in behavior? His work has been funded by generous grants from the National Science Foundation, the National Institutes for Health, and the Army Research Office at the Department of Defense.
Misha Pavel
Misha Pavel holds a joint faculty appointment in Northeastern University’s Khoury College of Computer Sciences and Bouvé College of Health Sciences. His background comprises electrical engineering, computer science, and experimental psychology, and his research is focused on multi-scale computational modeling of behaviors and their control, with applications ranging from elder care to augmentation of human performance. Pavel uses these model-based approaches to develop algorithms transforming unobtrusive monitoring from smart homes and mobile devices to useful and actionable knowledge for diagnosis and intervention. Under the auspices of the Northeastern-based Consortium on Technology for Proactive Care, Pavel and his colleagues target technological innovations to support the development of economically feasible, proactive, distributed, and individual-centered healthcare. In addition, Pavel is investigating approaches to inferring and augmenting human intelligence using computer games, EEG, and transcranial electrical stimulation.
Previously, Pavel was the director of the Smart and Connected Health Program at the National Science Foundation, a program co-sponsored by the National Institutes of Health. Earlier, he served as the chair of the Department of Biomedical Engineering at Oregon Health & Science University, a Technology Leader at AT&T Laboratories, a member of the technical staff at Bell Laboratories, and faculty member at Stanford University and New York University. He is a senior life member of IEEE.
Previously, Pavel was the director of the Smart and Connected Health Program at the National Science Foundation, a program co-sponsored by the National Institutes of Health. Earlier, he served as the chair of the Department of Biomedical Engineering at Oregon Health & Science University, a Technology Leader at AT&T Laboratories, a member of the technical staff at Bell Laboratories, and faculty member at Stanford University and New York University. He is a senior life member of IEEE.
Talmo Pereira
Dr. Talmo Pereira is a Principal Investigator at the Salk Institute for Biological Studies in San Diego, CA where he leads a research group as a Salk Fellow. His lab focuses on the development of deep learning-based computational methods for recognition and modeling of complex biological systems, with applications ranging from social and motor neuroscience to plant biology. His recent work has demonstrated how advances in deep learning and computer vision can enable quantitative phenotyping of complex behaviors through the development and application of approaches for markerless motion capture. This work has been published in Nature Methods and featured in The Scientist, Nature Lab Animal, Nature Toolbox, and Quanta Magazine. Prior to joining Salk, Talmo worked as a research intern in Perception at Google AI working on pose-based action recognition and received his PhD in Neuroscience from Princeton University where he was also a recipient of the NSF Graduate Research Fellowship and the Porter Ogden Jacobus Fellowship — Princeton University’s top graduate student honor.
Sridevi Sarma
Sridevi Sarma, associate professor in the Department of Biomedical Engineering and vice dean for graduate education at the Whiting School of Engineering, develops computational, data-driven, and biological approaches to advance the knowledge and treatment of diseases of the nervous system including epilepsy, chronic pain, Parkinson’s disease, and insomnia. She also harnesses dynamical systems and control theory to understand how the brain governs complex behaviors, including motor control and decision making.
Sarma, who is the associate director of Hopkins’ Institute of Computational Medicine (ICM), founded and directs the Neuromedical Control Systems Lab (NCSL). The mission of NCSL is to develop knowledge and computational tools that can be translated into the clinic. As an example, her groundbreaking research and tools are helping to shape treatment of epilepsy. Drug treatment does not work for 30 percent of the world’s 60-million-plus epilepsy sufferers. Hope for these patients lies in removal of the brain’s epileptogenic zone (EZ), where seizures originate. Currently, EZ localization is done manually through the daunting visual inspection of hundreds of intracranial EEG recordings. Within six-months post-surgery, there is an average of 50 percent chance of seizure recurrence, most likely caused by misidentification and/or nonresection of the entire EZ.
Sarma’s additional research in pain control includes constructing computational models of the dorsal horn (DH) circuit in the spinal cord to predict how different electrical stimulation treatments alter neuronal activity in the DH. Sarma’s team also created the first-ever computational model of the motor network under Parkinson’s Disease (PD) conditions to study the effects of deep brain stimulation (DBS). She found that high frequency DBS actually restores pathological network dynamics in the brain, while many thought that it was blocking abnormal activity.
She received her BS in Electrical Engineering (1994) from Cornell University and her SM (1997) and PhD (2006) in Electrical Engineering and Computer Science from the Massachussets Institute of Technology (MIT). She was a postdoctoral fellow in Statistical Neural Data Analysis in the Neuroscience Statistics Research Laboratory at Massachusetts General Hospital and Harvard Medical School and at MIT’s Computational Neuroscience Laboratory in the Brain and Cognitive Science Department.
Sarma, who is the associate director of Hopkins’ Institute of Computational Medicine (ICM), founded and directs the Neuromedical Control Systems Lab (NCSL). The mission of NCSL is to develop knowledge and computational tools that can be translated into the clinic. As an example, her groundbreaking research and tools are helping to shape treatment of epilepsy. Drug treatment does not work for 30 percent of the world’s 60-million-plus epilepsy sufferers. Hope for these patients lies in removal of the brain’s epileptogenic zone (EZ), where seizures originate. Currently, EZ localization is done manually through the daunting visual inspection of hundreds of intracranial EEG recordings. Within six-months post-surgery, there is an average of 50 percent chance of seizure recurrence, most likely caused by misidentification and/or nonresection of the entire EZ.
Sarma’s additional research in pain control includes constructing computational models of the dorsal horn (DH) circuit in the spinal cord to predict how different electrical stimulation treatments alter neuronal activity in the DH. Sarma’s team also created the first-ever computational model of the motor network under Parkinson’s Disease (PD) conditions to study the effects of deep brain stimulation (DBS). She found that high frequency DBS actually restores pathological network dynamics in the brain, while many thought that it was blocking abnormal activity.
She received her BS in Electrical Engineering (1994) from Cornell University and her SM (1997) and PhD (2006) in Electrical Engineering and Computer Science from the Massachussets Institute of Technology (MIT). She was a postdoctoral fellow in Statistical Neural Data Analysis in the Neuroscience Statistics Research Laboratory at Massachusetts General Hospital and Harvard Medical School and at MIT’s Computational Neuroscience Laboratory in the Brain and Cognitive Science Department.
Katherine Scangos
Katherine Scangos, MD, PhD, is a psychiatrist and neuroscientist with an interest in developing novel therapies for neuropsychiatric conditions. She is an Assistant Professor at the University of California, San Francisco Department of Psychiatry. There she conducts quantitative circuit-based neuroscience research to identify electrophysiologic biomarkers of mood disorders and new forms of responsive brain stimulation therapies. She led a clinical trial of personalized closed-loop deep brain stimulation for treatment resistant depression. Clinically, she co-directs the Transcranial Magnetic Stimulation and Neuromodulation clinic and research program at UCSF. She is currently a Medical Director at Neumora Therapeutics, where she works to integrate multimodal biomarker development into clinical trials on a large scale.
Katherine is a recipient of the National Institute of Mental Health’s Outstanding Resident Award Program (2017) and the 1907 Trailblazer Award (2020). She received funding from the Brain and Behavioral Research Foundation NARSAD Young Investigator Grant, the National Institute of Neurological Disorders and National Institute of Mental Health. Her published work was featured on National Public Radio and in the New York Times.
Katherine received her undergraduate degree from Amherst College and her medical degree and a doctorate in neuroscience from Johns Hopkins School of Medicine. She subsequently completed psychiatry residency at University of California, Davis and a fellowship in Interventional Psychiatry and Neuroengineering at University of California, San Francisco.
Alik Widge
Alik Widge, MD, PhD is a brain stimulation psychiatrist and biomedical engineer. He is an Assistant Professor of Psychiatry at the University of Minnesota, where he directs the Translational NeuroEngineering Lab. His research focuses on brain stimulation for severe and treatment-resistant mental illness, with particular emphasis on deep brain stimulation and related implantable technologies. Dr. Widge’s recent work has demonstrated new algorithms for closed-loop brain stimulation and stimulation methods for modifying connectivity in the distributed circuits of mental illness. His laboratory studies rodent models for prototyping these new technologies and human patients to identify biomarkers and targets for future intervention. He also co-leads programs to design new neurostimulation technologies in the central and peripheral nervous systems.