SoKat Consulting, LLC was founded by Susan An and Jim Liew in 2014. SoKat creates world-class Machine Learning / AI and Blockchain products and services primarily servicing government agencies, institutional investors, academic institutions, and select-startups.
Susan An, Esq. — Chief Executive Officer and co-Founder
Susan was the Chief Compliance Officer of Calypso Capital Management, LLC where she served as in-house counsel to the $1 billion long-short equity hedge fund, providing legal guidance to the investment manager, senior management, and employees on Federal securities regulation. She was successful in registering Calypso as an investment adviser with the SEC. She graduated with a JD at University of Maryland Francis King Carey School of Law where she served as President of the Asian American Law Students Association.
Dr. Jim Kyung-Soo Liew — Chief Operating Officer and co-Founder
Jim is an Assistant Professor of Finance at Johns Hopkins Carey Business School and revels in pushing the boundaries of financial knowledge both as an academic and FinTech Entrepreneur. He has published pioneering research in the intersection of social media big data and financial markets. He currently teaches Blockchain, Big Data Machine Learning, and Leading Entrepreneurship. Additionally, he serves as the Chairman of the Johns Hopkins Innovation Factory and has received the Dean’s Award for Faculty Excellence in 2015-2017. He also serves on the Editorial Board of Journal of Portfolio Management. Previously, Jim has worked at the Carlyle Asset Management Group, Campbell and Company, and Morgan Stanley. He holds a BA in Math from the University of Chicago and a Ph.D. in Finance from Columbia University. He currently lives just outside of Baltimore with his wife and two daughters, who he plans to raise as the next generation disruptors.
Dr. Alexander Szalay — Senior Scientific Advisor Chief Big Data Scientist
Dr. Alexander Szalay is a Bloomberg Distinguished Professor, the Alumni Centennial Professor of Astronomy, and Professor in the Department of Computer Science. He is the Director of the Institute for Data Intensive Science. He is a cosmologist, working on the statistical measures of the spatial distribution of galaxies and galaxy formation. He is a Corresponding Member of the Hungarian Academy of Sciences, and a Fellow of the American Academy of Arts and Sciences. In 2004 he received an Alexander Von Humboldt Award in Physical Sciences, in 2007 the Microsoft Jim Gray Award. In 2008 he became Doctor Honoris Causa of the Eotvos University, Budapest. He has written over 450 papers in various scientific journals, covering areas from theoretical cosmology to observational astronomy, spatial statistics and computer science.
Dr. Tamás Budavári — Scientific Advisor Chief Machine Learning Scientist
Dr. Tamas Budavari is Assistant Professor of Applied Mathematics & Statistics at The Johns Hopkins University, where he focuses on computational and mathematical aspects of Big Data analytics with applications in astronomy, materials research, urban planning and finance. He is a builder of the Sloan Digital Sky Survey and its data science solution as well as the Hubble Source Catalog: the ultimate legacy of NASA's Hubble Space Telescope. In addition to research, he currently teaches "Data Mining" in JHU's Whiting School of Engineering. Budavari is the Data Science PI in the Center for Materials in Extreme Dynamic Environments, affiliated with the Institute for Data Intensive Engineering & Science (IDIES), and is Steering Committee Member of the 21st Century Cities signature initiative (21CC) at Hopkins. He is founding Editor of the Journal Astronomy & Computing.
Lucy Zhang — Machine Learning / AI Engineer Intern
Lucy is a current an undergraduate at Johns Hopkins University studying Computer Science. Her prior experiences include working as a Research Assistant in the Joel Bader Lab in the Department of Biomedical Engineering. Additionally, she has served as a Teaching Assistant for the Introduction to Java course at Johns Hopkins. She enjoy developing Machine Learning and AI models that attempt to predict the health of grantee-organizations.
Emma Zhang — Machine Learning / AI Engineer Intern
Emma Zhang is currently an undergraduate at the University of Chicago pursuing her BA in Public Policy & Statistics. Previously she worked as a Web Developer at the Chicago Booth School of Business Digital Marketing where she enhanced the user experience for faculty and graduate students. She is original from Virginia graduating from Thomas Jefferson High School for Science & Technology.
— Business Development Lead for SoKat Labs
Andrew enjoys studying Economics and History as a Junior at the Johns Hopkins University. He is the Leader of The Johns Hopkins Hodson Scholar Community and a Trust Scholar. He enjoys programming Python, Swift, and Hyperledger. Additionally, he enjoys equity trading and practicing his Spanish at every opportunity.
Matthew Marcetich — Machine Learning / AI Team Lead
Matt graduated from Marquette University with a BS in Biochemistry/Molecular Biology, with a MPH from Johns Hopkins Bloomberg School of Public Health and with a Certificate in Investments from Johns Hopkins Carey Business School. His previous work has included diagnostic assay development, and support of enterprise informatics for medical research. Matt loves to golf and hike, and he has hiked in the Grand Canyon.
Sinan Ozdemir — Founder and CTO at Kylie.ai Technical Advisor
Sinan graduated from The Johns Hopkins University with a BA and MA in Pure Mathematics. Sinan served as an Adjunct Lecturer for Business Analytics, Calculus, and Programming while at Hopkins. Currently, he is the Founder and CTO of Kylie.ai, an AI company that clones employee personalities to automate conversations between a company and its customers. Sinan recently published Principles of Data Science.
Dr. Alexander Antoniou — Machine Learning / AI Engineer
Dr. Antoniou is a board certified physician and fellowship trained informatics specialist from Johns Hopkins. He is a former fund manager and investment advisor (Series 65) and former McKinsey Management Consultant in the field of big data and advanced analytics. Most recently, Dr. Antoniou is the founder and Chief Medical Officer of BlockMedx, a blockchain based health technology company using machine learning and AI to combat drug addiction and overdose.
Chaim Gluck — Machine Learning / AI Engineer
Chaim is currently completing his B.A. in Liberal Studies at Thomas Edison State University. Before pursuing his interest in Machine Learning, he managed operations for an e-commerce company. He followed his passion for Natural Language Processing to General Assembly’s Data Science Immersive course, where he studied various Machine Learning algorithms and their implementations in Python. Chaim plays a mean game of ping-pong, thoroughly enjoys breakfast cereal, and is always in middle of a good book.
Himanshu Makharia — Data Scientist & Machine Learning / AI Engineer
Himanshu is a recent graduate from the Johns Hopkins Carey Business School with a MS in Information Systems. During his graduate studies, he worked for a healthcare startup, building predictive analytical models for diseases such as heart failure, diabetes and stroke by developing machine learning algorithms including random forest, neural networks and SVM. He completed his undergraduate degree from Boston University in Finance, and his current interests include deep learning analytics.
Ravpritpal Kohli — Machine Learning / AI Engineer
Ravpritpal (Ravi) Kohli, received his MS in Finance in 2016 from Johns Hopkins University. Prior to this, he completed his undergraduate degree in Accounting and Business from Delhi University. He has worked as a Financial Data Analyst with a startup that produces mobile games and was a Risk Analyst at Transamerica. He has co-developed India Fama-French Factors with Professor Jim Liew. He loves guitar performing and has created two demo albums.
Matthew Grobis — Machine Learning / AI Engineer
Matt has a background in experimental biology. He is currently pursuing a PhD at Princeton University, studying information transfer in fish schools. Matt employs generalized linear models, time series analysis, and machine learning to answer questions in his thesis and at SoKat.
Li Sun — Machine Learning / AI Engineer
Li Sun graduated from Georgetown with a MS in Analytics concentrating in Data Science, where he studied the full-stack of data tools, including crawling, modeling and visualizing the data. Prior to that he completed his Master's degree from Johns Hopkins Carey Business School. Li enjoys cycling and playing video games. He is on the way to save the Princess Zelda.