Our third Stroke Translational Research Advancement Workshop (STRAW) will be held on April 20-21, 2022, in Lexington, KY.
Teaching Machines to Innovate: Big Data Analytics using Machine Learning in Translational Research will focus on artificial intelligence (AI) as a tool to reinvigorate stroke research.
Topics will include the use of AI such as machine learning to develop prognostics for stroke patient care and identify new therapeutic targets for treatment.
Speakers from academia and industry using AI in other pathologies will also be invited to demonstrate how AI is advancing research in their field.
The main goal of this workshop will be to connect stroke researchers with resources and individuals in AI and machine learning science, in order to provide new tools for stroke researchers in their respective areas.
As per tradition, the meeting will have no registration fee and will also include an optional excursion in the ‘land of horses and bourbon’, including an excursion to Mill Ridge Farm followed by bourbon tasting and dinner at the Castle and Key Distillery.
This workshop facilitates opportunities for networking with like-minded research scientists.
National Institute of Neurological Disorders and Stroke | Division of Translational Research
Dr. Natalie Trzcinski joined the National Institute of Neurological Disorders and Stroke (NINDS) Division of Translational Research (DTR) in 2017 and serves as a Scientific Project Manager in the Small Business programs, where she oversees a portfolio of small business innovative research (SBIR), small business technology transfer (STTR), and BRAIN Technology Integration and Dissemination projects. Prior to joining NINDS, she received her B.S. in Biological Sciences from Cornell University, where she researched mechanisms of electrocommunication and electroreception in weakly electric fish. She obtained her PhD in neuroscience from Johns Hopkins University, studying neural mechanisms of somatosensory selective attention and experience dependent plasticity at the Zanvyl Krieger Mind/Brain Institute. She then worked as a postdoctoral fellow at the Institute for Systems Research at University of Maryland (UMD), where she developed neurophysiology methods for extracellular chronic recording in auditory cortices and studied neural mechanisms of auditory attention and plasticity.
Sean Ekins, Ph.D., D.Sc.
Founder & CEO
Collaborations Pharmaceuticals, Inc.
Sean graduated from the University of Aberdeen; receiving his M.Sc., Ph.D. in Clinical Pharmacology and D.Sc. in Science. He then came to the USA and was a postdoctoral fellow at Lilly Research Laboratories, before working as a senior scientist at Pfizer and then Eli Lilly. He went on to join startup companies as Associate Director of Computational Drug Discovery at Concurrent Pharmaceuticals Inc. (now Allergan) and Vice President of Computational Biology at GeneGo (now Thomson Reuters). Dr. Ekins was CSO of Collaborative Drug Discovery, Inc and co-founder and CEO at Phoenix Nest Inc. He is now founder and CEO of Collaborations Pharmaceuticals, Inc. which is focused on using machine learning approaches for rare and neglected disease drug discovery. He is also the on the SAB of the Pitt Hopkins Research Foundation and Adjunct Professor at 3 US universities. Since 2005 he has been awarded 20 NIH and DOD grants (STTR/SBIR grants, R21, UH2 and R01) and performs as a consultant on many others. He has authored or co-authored >300 peer reviewed papers, book chapters, and edited 5 books. For over 23 years he has been at the forefront of using commercial and in-house developed software in drug discovery research. He has a passion for finding new collaborators and developing new treatments for neglected and rare disease.
Chris Mansi, M.D.
Co-Founder & CEO
Dr. Chris Mansi is a Neurosurgeon and the CEO of Viz.ai, an applied AI healthcare company. He is a clinician innovator and entrepreneur. He cares about healthcare access, building and supporting great teams, transformative technologies, and improving provider experience to effect and scale better patient outcomes. Viz was the first FDA cleared AI software, creating a new device category; Computer Aided Triage. It uses deep learning to automatically analyze CT scans of the brain and immediately alert the stroke team about large vessel occlusion strokes, synchronizing care across a hospital network and saving time. The dual clinical and financial value proposition has led to rapid adoption; in the 9 months Viz has been on the market it has been adopted by over 250 hospitals across the USA.
Andreas Rauschecker, M.D.
University of California, San Fransisco
Dr. Rauschecker is an Assistant Professor in the Neuroradiology Section of the Department of Radiology and Biomedical Imaging at the University of California San Francisco. Dr. Rauschecker earned a Master’s Degree in neuroscience at the University of Oxford prior to earning his MD and a PhD in Neuroscience at Stanford University. As a physician-scientist, Dr. Rauschecker has spent the last decade developing artificial intelligence tools for quantitatively describing abnormalities across large populations on brain MRI, including in the context of tumors, demyelinating disease, and pediatric leukodystrophies. Dr. Rauschecker also uses machine learning tools for understanding the normally developing brain from fetal MRI through adolescence. He is also a core member of UCSF’s Center for Intelligent Imaging (ci2), where he co-directs the education pillar.
Fabien Scalzo, Ph.D.
University of California, Los Angeles
Fabien Scalzo, PhD is Assistant Professor of Neurology and Director of the Artificial Intelligence in Imaging and Neuroscience Lab at UCLA. He holds joint appointments in the Department of Computer Science and Electrical and Computer Engineering where he teaches medical imaging and computer vision. Dr. Scalzo specializes in building computational models for neuroimaging and has published over 200 research papers. He has been an investigator on several neuroscience-related research projects funded by NIH, NSF, AHA, and DARPA.
Matt Gounis, Ph.D.
University of Massachusetts Medical School
Matt Gounis, PhD, is a biomedical engineer and Professor of the Department of Radiology, University of Massachusetts Medical School. He co-founded the New England Center for Stroke Research at UMASS in 2006 where the team works to bring new imaging and medical device technology from the bench to the clinic. For 20 years, Matt has performed research on the minimally invasive treatment of cerebrovascular disease with a focus on device technology, pre-clinical disease modeling, and image-guided surgery. Matt is the 2010 recipient of the Y.C. Fung Award from the ASME, the Founding President of the SB3C Foundation, the past Chair of the Bioengineering Division of the ASME and the AHA Clinical Bioengineering Committee, Fellow of ASME and currently serves as the Basic Science Associate Editor for the Journal of Neurointerventional Surgery and on the Editorial Board of the journals Stroke and Neurosurgery.
Wednesday, April 20, 2022
[Embassy Suites Conference Room, Lexington, KY]
8:00 AM - 8:20 AM: Registration, Continental Breakfast
8:20 AM - 8:30 AM: Welcome Remarks (University of Kentucky: Keith Pennypacker, Director, CATSS)
8:30 AM - 9:15 AM: Machine Learning in Neurovascular Care (Fabien Scalzo, UCLA)
9:15 AM - 10:15 AM: What is the matrix? Using AI to Recognize and Synchronize Acute Stroke Processes (Chris Mansi, Viz.ai)
10:15 AM - 10:30 AM: Coffee Break
10:30 AM - 11:30 AM: NINDS STTR/SBIR Program (Natalie Trzcinski, NINDS)
11:30 AM - 12:30 PM: Discovery Science with Industry Aid? The INSIGHT Study (Industry Representatives)
12:30 PM - 1:30 PM: Networking Lunch (University of Kentucky: Keith Pennypacker, Justin Fraser, Ann Stowe, Jill Roberts, Amanda Trout)
2:00 PM: Board Buses for Afternoon Activities
[Afternoon Destination Activities]
2:30 PM - 4:00 PM: Mill Ridge Farm
4:15 PM - 9:00 PM: Dinner at Bulleit Distillery
Thursday, April 21, 2022
[Embassy Suites Conference Room, Lexington, KY]
8:00 AM - 8:30 AM: Continental Breakfast and Announcements
8:30 AM - 9:30 AM: Artificial Intelligence for Creating Probabilistic Differential Diagnoses on Clinical Brain MRI (Andreas Rauschecker, UCSF)
9:30 AM - 10:15 AM: Building a Biotech Using Machine Learning for drug repurposing (Sean Ekins, Collaborations Pharmaceuticals, Inc.)
10:15 AM - 10:30 AM: Coffee Break
10:30 AM - 12:00 PM: Unifying Science: Pooling Support from Science and Industry to Propel Our Field (Matt Gounis, University of Massachusetts)
12:15 PM - 1:15 PM: Lunch
2:00 PM: Conclusion
For more information, contact the team behind the Center for Advanced Translational Stroke Science.