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DANIELA BRUNNER, PhD, EXECUTIVE DIRECTOR, EARLY SIGNAL
Dr. Brunner, the Founder and President of Early Signal, received her PhD from Cambridge University, did post-doctoral work at Columbia University, and had a lab at CUNY before joining PsychoGenics Inc. in 1999 as Director R&D, and later as Senior Vice President, until 2015. Dr. Brunner worked on developmental, psychiatric and neurodegenerative disease models for +20 years; she introduced computer vision and machine learning techniques to the study of behavioral signatures for phenotyping, drug screening and systems biology projects. Working with the Tuberous Sclerosis Alliance, Dr. Brunner set up a consortium of industry and academia to accelerate the drug development for tuberous sclerosis. At Early Signal Dr. Brunner is developing analytical systems for health care and monitoring in rare disorders and underserved populations, focusing on data passively captured with wearable and home sensors.
FRISO POSTMA, PhD, DEPUTY DIRECTOR, EARLY SIGNAL
Dr. Friso Postma has a masters in Medical Biology, University of Amsterdam, and a PhD on G-protein coupled receptor signaling and downstream cellular effectors, Netherlands Cancer Institute. As a post-doc at Harvard Medical School (Cambridge, MA) he used molecular and electrophysiological techniques to study the role of gap-junctions in the retina and CNS. As a Senior Scientist at Seaside Therapeutics (Cambridge MA) he worked on the development of treatments for fragile-X syndrome and Autism Spectrum Disorder. He continued his work as Associate Director of Electrophysiology at Psychogenics, a contract research organization, and as a scientific consultant for Boston-based biotech companies (SAGE therapeutics) and Early Signal. Dr. Postma joined Early Signal team in early 2017.
Udi Rubin worked for more than 10 years in the Israeli hi-tech industry. His experience alongside growing passion towards life sciences led Udi to pursue graduate studies in Biotechnology from Columbia University. In his research, Udi collaborated in developing data-driven computational frameworks for cancer genomics using topological data analysis and inferential statistics. Leveraging his mixed technological, analytical and life science background, Udi joined the Foundation in 2016, where he is developing Early Signal’s analytical platform, and overseeing all IT requirements.
ZHANNA ROZENBERG, BA, SENIOR MANAGER, DIGITAL HEALTH
Zhanna received her BA at Cornell University where she triple majored in Economics, Comparative Literature, and an College Scholars major that tread on philosophy, critical theory, and sociology. She completed a minor in East Asian Studies. She later went to study statistics, econometrics, and machine learning at the Ruprecht-Karls-Universität Heidelberg, Universität Mannheim, and the Metis’s data science bootcamp. Zhanna is interested in making technology that helps people live more meaningful lives, using data to improve human performance. Zhanna is active in NY's meetup culture focusing on data science, neuroscience, wearables, IoT, and habit design. Zhanna’s major individual project, "Hindsight", explored the interaction between subjective and objective measures of human performance. She joined Early Signal in 2017 where she is pursuing some of her favorite pastimes.
Dr. Shokhirev received a Master of Science Degree in theoretical physics from Novosibirsk State University, Russia, and his Doctor of Philosophy degree in Physics and Mathematics from the Russian Academy of Sciences, Novosibirsk. Dr. Shokhirev has conducted research in quantum mechanics, magnetic spectroscopy, econophysics, stochastic processes and kinetics. He has also been involved in data analysis and processing in pulse spectroscopy, indirect measurements and remote sensing, scientific, engineering and financial data. He has published over 70 papers in those fields. Dr. Shokhirev joined Early Signal to apply his data science skills to the emerging area of remote health monitoring and healthcare.
KEVIN URBAN, PHD, SENIOR DATA SCIENTIST, DIGITAL HEALTH
Kevin has over a decade of experience exploring a diverse range of complex data sets stemming from NASA and NOAA spacecraft missions in Earth’s ionosphere, magnetosphere, and interplanetary space, and from global-scale networks of ground-based instrumentation, and has leveraged this data to forecast space weather at the outer limits of Earth’s upper atmosphere and its effects in Earth’s polar cap regions, culminating in several peer-reviewed research papers. Kevin has also published on space mission design and dynamical system modeling of granular fluid systems. After receiving his PhD in physics from New Jersey Institute of Technology and Rutgers University, Kevin worked as a data scientist at WWE, where he built predictive models for subscriber behavior on the WWE Network (a monthly, direct-to-consumer, video streaming service averaging ~2 million daily active subscribers), and led various data engineering efforts, such as the collection, ingestion, and harmonization of WWE fan data across a host of social media and online platforms.
Carlos received his Bachelor of Science in Applied Mathematics in 2012 from the Instituto Tecnológico Autónomo de México. Carlos then worked for Sinnia until 2015 and then joined the eScience Institute, University of Washington, as Data Science for Social Good Fellow, where he worked on data science projects using data from urban environments, public health, sustainable urban planning, crime prevention, education, transportation, and social justice. Carlos obtained a M. Sc. In Data Science from Columbia University in the City of New York in 2016.