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.
Olivia Brown— Machine Learning / AI Engineer Intern
Olivia (Liv) worked as a lifeguard and taught children how to swim year round for three years. Currently a sophomore at Johns Hopkins University, she studies international/global studies and computer science. She hopes to go into cybersecurity especially in developing countries upon graduation.
Natalie Olivo — Machine Learning / AI Engineer
Natalie is a meticulous and incisive insight-finder, a dynamic collaborator, and a life-long learner. She has an aptitude for technical challenges, and with experience in applied mathematics and training in data science, she brings a determined vivacity to each step of the problem-solving process, bringing grand visions to life.
— Machine Learning / AI Engineer Intern
Elizabeth is an undergraduate pursuing Computer Science at Johns Hopkins University. She enjoys exploring how to apply her programming and analysis skills to a diverse range of topics such as HealthCare and interactive web apps. Elizabeth is an avid dancer and has received an Associate of Arts Degree in Dance. She also loves to read, travel, and visit water parks.
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.
David Kaminsky — Machine Learning / AI Engineer Intern
David is a junior at Johns Hopkins University studying Applied Math and Statistics and Chemical and Biomolecular Engineering. His academic interests include big data modeling and alternative energy optimization. He is an executive board member of the marketing consulting club at Hopkins, mentors Baltimore middle school students in science and math, and is a Bloomberg Scholar. In his free time, he enjoys playing violin and taking his hometown Knicks way too seriously.
Justin Sech — Machine Learning / AI Engineer Intern
Justin is an undergraduate at Johns Hopkins University studying Computer Science and Robotics. On weekends, he teaches young children the fundamentals of computer science through fun, interactive projects. Additionally, Justin serves as a speech editor for Hopkins’ biannual TEDx events. In his free time Justin plays lead guitar in a band that hosts concerts for charity.
Brandon Fremin — Machine Learning / AI Engineer Intern
Brandon is a rising junior at Johns Hopkins University studying Mechanical Engineering and Computer Science with a focus in software engineering and a minor in Robotics. He is a catcher on the varsity baseball team, a calculus tutor, and a class representative for the Mechanical Engineering Undergraduate Student Council. Brandon’s experience includes creating a pitch clustering program to analyze and compare pitchers for the Baltimore Orioles. He enjoys designing digital logic circuits, writing programs which generate fractals, and learning new math proofs.
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.
Tiger Gao — Machine Learning / AI Engineer Intern
Tiger Gao is a current Combined Bachelor’s/Master’s in Computer Science student at Johns Hopkins University. His academic interests are in machine learning and information security. He was a research assistant in the Fertig bioinformatics lab at the Johns Hopkins Medical School. He competes on the Hopkins varsity fencing team.
Steven Solar — Machine Learning / AI Engineer Intern
Steven is an undergraduate at The Johns Hopkins University, studying Computer Science and Biomedical Engineering. His other work includes development of the Semester.ly platform, a website for course registration at Johns Hopkins. Additionally, he is a member of the Treyetech team, which has developed a novel patent-pending medical device to facilitate a kind of corneal transplant known as DMEK. In his free time, he loves to ski, read science fiction novels, and play ultimate frisbee.
Katherine Lee — Machine Learning / AI Design Strategist
Kat Lee is a passionate design strategist and artist from Phoenix, Arizona and is currently pursuing an MA/MBA in Design Leadership from Johns Hopkins Carey Business School and Maryland Institute College of Art.
She has worked as an Arts program director for Girl Scouts, traveled the world as a ceramics resident artist, apprentice for a silver smith in Taiwan, as well as a master forager who travels the world looking for natural medicines. Kat enjoys foraging and identifying medicinal herbs and mushrooms, Muay Thai kickboxing, open ocean kayaking, has a deep love for fresh mochi, and playing with her two cats Monkey and Silvio