I never teach my pupils, I only attempt to provide the conditions in which they can learn."Albert Einstein
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.
Jaideep Vaidya is a Professor of Computer Information Systems at Rutgers University since 2004. He received the B.E. degree in Computer Engineering from the University of Mumbai in 1999 and a MS and Ph.D. degree in Computer Science from Purdue University in 2001 and 2004 respectively. His research is primarily focused on data mining, data management, security, and privacy. He has published over 140 technical papers in peer-reviewed journals and international conferences. His work has received over 5900 citations and has also been recognized with best paper awards from the premier conferences in data mining, databases, digital government, security, and informatics. He has received the NSF Career Award and the Rutgers Board of Trustees Fellowship for Excellence in Research. He is a senior member of the IEEE and an ACM Distinguished Scientist, and is currently the Vice Chair of the SIAM Activity Group on Data Mining and Analytics
Yuri Balasanov is a lecturer 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. He has lead research teams working on analytical and data driven projects as well as development of software for analytics.
Dr. Amey Karkare completed his Ph.D. from IIT Bombay in 2009 and his B.Tech. from IIT Kanpur in 1998. His areas of interest include Intelligent Tutoring Systems, Program Analysis, Compiler Optimizations, and Functional Programming. He has more than 7 years of industrial experience most of which is in the area of Compiler Optimizations. He is an Associate Professor in the Department of CSE at IIT Kanpur. He is currently the head of Computer Center and Associate Dean for Digital Infrastructure at IIT Kanpur. Dr. Karkare received prestigious Infosys fellowship during his Ph.D., and P. K. Kelkar Young Research Fellowship at IIT Kanpur. He has been visiting researcher at Microsoft Research, Redmond, and IIT Bombay. Last few years his focus is on improving how introductory programming courses are taught. He has co-taught large online courses on programming that had registration of more than 30,000 students. The software he developed is being used at several premier institutes in India like IIT Kanpur, IIT Bombay, IIT Goa, IISER Bhopal to name a few.
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.
Dr Gustavo is teaching in the department of Computer Science at Purdue University since 2000. He received his Ph.D. degree in Computer Science from Purdue University and MS degree in Electrical Engineering from ITESM campus, Monterrey Mexico. Besides many other teaching awards, Dr. Gustavo Rodriguez-Rivera was awarded the "Best Teacher in the School Of Science in 2014". Gustavo has more than 20 years of teaching experience. In his classes He emphasizes Systems Programming and Software Engineering. Gustavo's main areas of research are Operating Systems, Computer Networks, Memory Management, Embedded, and Real-Time Systems. He is also interested in Numerical Analysis, Computer Graphics, Computer Vision, Signal Processing, Artificial Intelligence, Data Structures, and Speech Recognition.
Koushik Sen is an associate professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. His research interest lies in Software Engineering, Programming Languages, and Formal methods. He is interested in developing software tools and methodologies that improve programmer productivity and software quality. He is best known for his work on “DART: Directed Automated Random Testing�? and concolic testing. He has received a NSF CAREER Award in 2008, a Haifa Verification Conference (HVC) Award in 2009, a IFIP TC2 Manfred Paul Award for Excellence in Software: Theory and Practice in 2010, a Sloan Foundation Fellowship in 2011, a Professor R. Narasimhan Lecture Award in 2014, and an Okawa Foundation Research Grant in 2015. He has won several ACM SIGSOFT Distinguished Paper Awards. He received the C.L. and Jane W-S. Liu Award in 2004, the C. W. Gear Outstanding Graduate Award in 2005, and the David J. Kuck Outstanding Ph.D. Thesis Award in 2007, and a Distinguished Alumni Educator Award in 2014 from the UIUC Department of Computer Science. He holds a B.Tech from Indian Institute of Technology, Kanpur, and M.S. and Ph.D. in CS from University of Illinois at Urbana-Champaign.
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.
Nav Vaidhyanathan heads the Model Validation function at M&T Bank. In this role, he is responsible for the soundness of hundreds of models used across various lines of businesses and functions within M&T. These include highly sophisticated and complex scorecard and loss forecast models in the area of credit risk including counterparty risk across retail and wholesale products, interest rate risk management models, liquidity risk management models, models within asset management, models in marketing, models used in BSA/AML compliance, pricing models, interest and noninterest income models, asset and deposit growth models among many others. He manages a large team of experienced quants, with advanced degrees, both onshore and offshore. During his tenure at M&T, Nav has raised the bar significantly for sound model development within the organization by publishing various white papers on various aspects of model development and testing for different types of models. Prior to M&T, Nav helped set up, build, and grow the Model Validation function for Wintrust. Nav also managed development of various stress test models at Northern Trust. Nav also managed the model validation function for stress test models at Discover Financial Services. Nav has deep expertise and experience in stress test (CCAR / DFAST) model development and validation. Nav has spoken on various aspects of Model Validation in a number of conferences. Nav received his BTech degree from IIT Kanpur, MS degree in Civil Engineering from Purdue University, MS degree in Electrical and Computer Engineering from Purdue University, MBA degree from Purdue University.