Acads courses provide students with the advanced training necessary to analyze, evaluate and apply analytical skills to handle large scale data problems. Our courses are designed to have a strong connection between theory and practice by having numerous projects implementation in Python and R. Classroom discussions, debates and group work are the primary medium of teaching in our courses. We encourage students to ask questions, challenge existing ideas and implement creative solutions
All our courses have been carefully designed by the collaborative effort of academicians and practitioners to have a right balance. Our advanced courses in data science and quantitative finance specializations are extremely demanding and intense as it introduces students to complex mathematical and statistical concepts.
Our Computer Science program offers courses in Python Programming, Database Design, Data Structures and Algorithms. Our Advanced Computing program offers courses in Operating System, Compilers and Computer Networks
Our Quant finance program offers courses in Portfolio Theory, Quantitative Trading Strategies and Risk Management and Portfolio Construction
Dr. Varghese John (VJ) is an experienced technologist with a scientific research background and a love for learning and teaching science, technology and mathematics. His research career in Physics includes work in String theory, Quantum Gravity, fluctuating membranes, matrix models and quantum mechanics. As a technologist, he has led global teams delivering innovative solutions to complex problems for leading financial service organizations. VJ is passionate about using his lifelong learning experiences to create and deliver innovative STEM education courses for children and adults in order to build a community of citizens who can apply logic and scientific thinking to address global challenges.
Niels O Nygaard is a Professor in the Department of Mathematics at the University of Chicago since 1982. Prior to joining the University of Chicago he taught at Princeton University. He holds a Ph.D. in Mathematics from MIT. Professor Nygaard was the Director of the Financial Mathematics Program since its inception in 1996 until April 2010. Besides his interest in Financial Mathematics he has done research in Arithmetic, Algebraic Geometry and Number Theory. Professor Nygaard was the founding director of both the Financial Mathematics Program and the Stevanovich Center for Financial Mathematics. Professor Nygaard is a recognized scientist in the field of financial mathematics and has a long list of publications
Dr. Ginensky has a M.S. and a Ph.D. in mathematics, both from the University of Chicago. He is currently teaching at the University of Chicago in their Master in Predictive Analytics Program. Prior to 2008, Adam worked as a market maker at the Chicago Mercantile Exchange and was involved in the mathematics of option pricing, but primarily was a floor trader. He has gave a number of talks in the University of Chicago Mathematical Finance Program. After 2008 he worked as a quantitative analyst for a proprietary trading company where he used Matlab and R (as well as SQL and various extensions) to perform data mining and statistical analysis of various financial data sets. His responsibilities included analyzing large (tick) data sets, performing statistical modeling of various time series of trading data, and writing the software packages to implement these goals. It was at this point that he became interested in applying statistics in other fields as well as finance. His current interests include both supervised and unsupervised learning as well as time series analysis. He is also currently exploring applications of algebraic geometry to statistics (algebraic statistics). In all aspects of his research and activity, he is fascinated by the practical applications of the theoretical ideas.
Amey Karkare is an Assitant Professor in the department of Computer Science at IIT Kanpur since 2010. He received BTech in Computer Science from IIT Kanpur in 1998 and Ph.D. degree in Computer Science from IIT Bombay in 2008. His area of research are Compilers, Data Flow Analysis and Heap Analysis. Dr Karkare has been teaching Fundamentals of Computing and Computer Organization at IIT Kanpur
Greg Zaric is a Professor of Management Science at the Ivey Business School, University of Western Ontario. He is also cross appointed in the Department of Statistical and Actuarial Sciences and the Department of Epidemiology and Biostatistics at Western. At Ivey he teaches at the undergraduate, master’s MBA and Executive MBA levels, and has twice won the Lawrence G. Tapp award for Excellence in MBA teaching. His research focuses on applications of statistics, analytics and operations research to problems in health economics and healthcare operations management. He received a BSc from the University of Western Ontario, an MSc from the University of Waterloo, and an MS and PhD from Stanford University.
Rafael is a Co-Founder and Chief Data Scientist at Next Level Analytics which provides high end data analytics solutions to corporate clients. He is also a Lecturer at Ivey Business School and his area of expertise are Financial Modeling, Machine Learning and High Performance Computing. Rafael holds MSc Management and HBA degree from Ivey Business School.
Dr. Ginensky has a M.S. and a Ph.D. in mathematics, both from the University of Chicago. He is currently teaching at the University of Chicago in their Master in Predictive Analytics Program. Prior to 2008, Adam worked as a market maker at the Chicago Mercantile Exchange and was involved in the mathematics of option pricing, but primarily was a floor trader. He has gave a number of talks in the University of Chicago Mathematical Finance Program. After 2008 he worked as a quantitative analyst for a proprietary trading company where he used Matlab and R (as well as SQL and various extensions) to perform data mining and statistical analysis of various financial data sets. His responsibilities included analyzing large (tick) data sets, performing statistical modeling of various time series of trading data, and writing the software packages to implement these goals. It was at this point that he became interested in applying statistics in other fields as well as finance. His current interests include both supervised and unsupervised learning as well as time series analysis. He is also currently exploring applications of algebraic geometry to statistics (algebraic statistics). In all aspects of his research and activity, he is fascinated by the practical applications of the theoretical ideas.
Yuri Balasanov is a faculty member at the University of Chicago since 1997. He teaches at Graduate Program on Financial Mathematics (MSFM) and Graduate Program on Analytics (MScA). He is also founder and President of Research Software International, Inc. since 1991 and iLykei Teaching Tech Corp since 2015. Dr. Balasanov earned his Master’s degree in Applied Mathematics and Ph. D. in Probability Theory and Mathematical Statistics from The Lomonosov Moscow State University, Russia, where he studied under Andrey Kolmogorov and leading members of his school. His primary expertise and research interests are in the area of stochastic modeling and advanced data analysis with applications in various fields including trading, risk management, finance and economics, business analytics, marketing, biology, medical studies. Dr. Balasanov has been a financial industry practitioner for more than 20 years, working at leading financial institutions as head quant, quantitative trader and risk manager.
