Established leaders from the world of Astronomy, Applied Mathematics, Computer Science, Finance, Law and Statistics.
SoKat Consulting, LLC was founded by Dr. Jim Liew in 2014 as a way to bridge academics with industry in the field of AI. Since then, SoKat has evolved into one of the most innovative AI tech companies providing full-stack software solutions for the federal government and private companies. SoKat’s competitive niche is that our small business is leveraging the value of applying the brightest minds in academia to develop AI solutions to real world problems. Our executive and advisory team are faculty at Johns Hopkins University, and our talented AI engineers are Johns Hopkins University graduates. With this rich pipeline of creativity, rigor and talent, SoKat has and continues to exceed client expectations in creating AI tools to enhance and improve human lives.
Susan An, Esq.
Chief Executive Officer
Susan has a long history with guiding entrepreneurial ventures, including having helped academics commercialize their intellectual property as a contracts attorney at Johns Hopkins Technology Ventures. Prior to that, she served as the Chief Compliance Officer at a young, start-up hedge fund in NYC with $1B in assets, providing legal guidance to the investment manager, senior management, and analysts on Federal securities regulation. In addition to her passion for technology entrepreneurism, she is equally dedicated to empowering marginalized communities, which is the basis for her work in the 2021 AI technology accelerator program at Women in AI (WAI), in which she is creating a mechanism to bring more women to the AI table, globally. She is also part of the 2021 SBA Emerging Leaders cohort. Along with a BA in Political Science and Economics, she also earned a JD from the University of Maryland Francis King Carey School of Law and is admitted to the New York State Bar.
Dr. Jim Kyung-Soo Liew
President and Co-founder
Avinash Sharma, MSE
Chief Technology Officer (CTO)
Avinash Sharma is the Director of Artificial Intelligence at SoKat. He brings in his unique experience and perspectives from engineering, neuroscience, and AI. Avinash graduated from The Johns Hopkins University with a Master of Science in Engineering (MSE) in Bioengineering and Biomedical Engineering with a Neuroengineering Research Track. He obtained his Bachelor of Technology (B. Tech) from the Mechanical Engineering Department from the Indian Institute of Technology (Delhi). At Johns Hopkins, he served as the head of Teaching Assistants for Professor Jim Kyung Soo Liew’s Big Data Machine Learning course and Professor Najim Dehak’s Machine Learning for Signal Processing. Mr. Sharma master’s thesis weaved myoelectric prosthesis/bionic technologies of tactile, sensory substitution, and EMG classification into Augmented Reality systems.
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.
Dr. Brian Caffo
Scientific Advisor Chief Data Scientist
I am a professor of Biostatistics at the Johns Hopkins University Bloomberg School of Public Health. I graduated from the University of Florida’s Department of Mathematics (BS) and Department of Statistics (MS and PhD).
I have worked on statistical computing and algorithms, hierarchical models, longitudinal and multivariate data analysis, sleep and its health consequences, neuro- and pharmacological imaging and finally educational innovation though Massive Open Online Courses.
Dr. Jordan J. Green
Dr. Jordan J. Green is a Professor of Biomedical Engineering, Ophthalmology, Oncology, Neurosurgery, and Materials Science & Engineering at the Johns Hopkins University School of Medicine. He is also an executive committee member of the Institute for NanoBioTechnology and co-founder of the Translational Tissue Engineering Center.
Dr. Green received his B.S. in chemical engineering and in biomedical engineering from Carnegie Mellon University in 2003 and completed his Ph.D. in biological engineering from the Massachusetts Institute of Technology in 2007. Subsequently, Dr. Green was a postdoctoral associate at MIT in chemical engineering from 2007-2008.