Shaddy Abado is a Staff Data Scientist at General Electric Digital, where he researches and develops data analytics solutions for equipment predictive maintenance, condition based monitoring and Industrial Internet of Things. He also has five years of experience instructing in a graduate professional studies setting. Prior to joining GE, he researched light-fluid interactions and developed different sensors and numerical methods to analyze these interactions. He has presented research at national conferences and published papers in peer-reviewed journals and conference proceedings. He received his MSc and PhD in aerospace and mechanical engineering from the University of Notre Dame.
Courses: Linear Algebra & Matrix Analysis
Medy S.A. Agami is the vice-chairman and partner at Ben-Roz & Associates. He is an expert in strategy and economics, data analytics and decision sciences, risk management and governance, finance, and public policy. Medy was previously a co-founder and managing director of Opimas. Prior to founding Opimas, Medy was the head of governance at Northern Trust. Medy has also worked in strategic advisory, as well as in finance and risk advisory at Oliver Wyman, prior to Oliver Wyman he worked at FSCM as a strategist, head of strategy and quantitative research, and chief risk officer.
He has worked with many of the world's leading companies and their boards on a variety of issues including strategy, analytics, and innovation and helped launch several market-shaping innovations. He has also worked with business leaders in diverse sectors on risk management and governance, defense, public policy, business transformation, opportunities in technology, and other global trends.
Medy has pioneered new ways of organizational strategic planning and execution, analytic innovation, risk management, and public policy design through the development of various initiatives that are currently implemented at the world's leading asset managers, banks, insurers, energy companies, think-tanks, NGOs, central banks, and public utilities. He has spoken at several CEO, economics and policy-maker forums around the world and regularly publishes position papers. Moreover, he has published over 20 thought leadership articles and technical papers in trade journals, industry publications and with leading research firms, which are referred to extensively and that cover a series of topics across strategy, analytics, risk management, economics, and governance.
Medy studied financial engineering and quantitative analytics for his Masters in Mathematical Finance at IIT. He also received an Executive Masters in Business Administration from the University of Chicago's Booth School of Business.
Courses: Short Python Course
Arnie Aronoff is formerly the senior director for human resources at Princeton University and the University of Chicago, Arnie Aronoff has brought his professional expertise to educational, nonprofit, social service, and other organizations as a consultant, coach, and trainer for over fifteen years. Mr. Aronoff is an experienced instructor who has been teaching for the Professional Development Program at SSA since 1996. He earned his doctorate from the University of Chicago and pursued advanced training in organizational development from the National Training Laboratories in Applied Behavioral Science (NTL) and the Gestalt Institute of Cleveland.
Courses: Leadership Skills
Francisco Azeredo is a financial economist and data scientist with eight years of experience working for leading financial institutions and consulting firms in the Chicago area. He is presently a vice-president and specialist at Northern Trust, leading analytics projects in FX high-frequency trading and digital client experience. He also consulted on credit risk, operational risk, and macroeconomic modeling. Prior to Northern Trust, he consulted on a wide range of high profile cases involving large financial institutions and multinational corporations. His research in financial economics was recognized by leading economists in the Handbook of the Equity Risk Premium, Intermediate Financial Theory, and an encyclopedia of behavior economics. He currently teaches statistical analysis, linear and non-linear statistical modeling and optimization in the MSc. Analytics at the University of Chicago Graham School. He holds a Ph.D. in Economics from the University of California, Santa Barbara.
Courses: Linear and Nonlinear Models for Business Application, Statistical Analysis, Optimization for Analytics
Dr. Balasanov earned his Master’s degree in Applied Mathematics and Ph. D. in Probability Theory and Mathematical Statistics from the Moscow State University, Russia. His primary expertise and research interests are in the area of stochastic modeling and advanced data analysis with applications in many fields including finance and economics, marketing, biology, medical studies, etc. Yuri has led many research teams running data analysis projects and developing well known statistical software. He has published multiple articles with his academic and applied research and presented at scientific conferences across the world. Yuri spent significant part of his career in major institutions of financial industry as quantitative researcher, quantitative trader and head of trading research, Chief Investment Officer and risk manager. He is the founder and the President of Research Software International. He combines his work in the industry with years of teaching experience at the Moscow State University, Department of Mathematical Statistics and the University of Chicago, Graduate Program on Financial Mathematics and Graduate Program on Analytics.
Courses: Statistical Analysis, Linear and Nonlinear Models for Business Applications, Financial Analytics, Real Time Analytics, Machine Learning and Predictive Analytics
Sema Barlas is the Director of MSc in Analytics Program. Her expertise is in the areas of applied marketing models, statistics, research methodology, and consumer behavior. Barlas’s research has been published in journals such as Organizational Behavior and Human Decision Processes and Applied Journal of Econometrics with over 500 citations. Prior to the University of Chicago, Barlas had taught at Argosy University in Chicago, McGill University in Canada, and University of Groningen in Netherlands and worked in industry for several years. At Sears, Roebuck, and Co., she developed credit risk, credit revenue, and line-of-credit models to manage acquisitions and portfolios of existing accounts. At Experian, she led projects in all aspects of database marketing. Barlas earned her PhD from the University of Chicago in Quantitative Psychology and Research Methodology and Master’s degree from University of Illinois at Urbana/Champaign in Applied Statistics.
Courses: Introduction to Statistical Concepts, Research Design for Business Applications
Shree Bharadwaj is the Director of Emerging Products at IRI, a market research company that provides clients with Market Performance and Strategy, Consumer and Shopper Intelligence, and In-Market Execution. In this role he is responsible for Innovation, Product Ownership of solutions revolving around Consumer and Media science such as Segmentation, Targeting and Activation, Campaign Measurement using Big Data, Predictive and Prescriptive Analytics, and Hyper Personalization. He has over 15 years of experience in the Telecommunications, Finance, Healthcare, Retail/CPG, and the Public Safety domains. During his early years he was part of the core team that built products from scratch that currently serve 60 percent wireless 911 calls in the United States. In addition to having filed for a couple of patents, he has an extensive background in formulating product launch strategies that have helped over a dozen products move from inception to market. Shree has a Master of Science in Analytics degree from The University of Chicago and a Bachelor of Science in Electronics and Communications Engineering from Manipal Institute of Technology. When not catching up on the latest developments in AI, Digital & Media or IoT, he spends his time with family and playing volleyball.
Courses: Database Design & Implementation
Arnab Bose is the Managing Director at Abzooba, a data analytics company. He is a 20 year veteran who enjoys working with data and has extensive analytics experience in healthcare and finance. Arnab is also a consultant in automated vehicle control. He focuses on natural language processing and machine learning models for unstructured and structured data. Arnab serves on the board of the financial engineering graduate program at University of Southern California. He is the Associate Editor for IEEE Transactions on Intelligent Transportation Systems. Arnab holds MS and PhD degrees in electrical engineering from University of Southern California, and a BS in electrical engineering from the Indian Institute of Technology in Kharagpur, India
Courses: Time Series and Forecasting, Machine Learning & Predictive Analytics, Health Analytics
Dr. Chaturvedi has over 25 years of professional experience at companies such as AT&T Bell Labs, Kraft Foods, Capital One, and Accenture. He has provided consulting services to Bank of America, Fannie Mae, Johnson & Johnson, and Proctor & Gamble. His general research interests include the areas of multivariate analysis methods for Big Data – multi-linear models, information mining, and business insights. He has co-authored a book "Mathematical Tools for Applied Multivariate Analysis" with the Late Professor Paul Green (University of Pennsylvania) and Professor J. Douglas Carroll (Rutgers University). He has patented and published analytical methods for Direct Marketing and Information Mining, Market Segmentation, New Product Development, Product Positioning, Customer Loyalty, Consumer Promotion Mix optimization, and Brand Strategy. He completed his PhD from Rutgers University, and PGDM from IIM Ahmedabad, India.
Courses: Data Mining Principles, Marketing Analytics, Research Design for Business Applications
Sebastien Donadio is currently head of software engineering at HC Technologies. There, he is responsible for managing software development. He has a wide variety of professional experience, including being a quantitative trading strategy software developer at Sun Trading, working as project lead for the Department of Defense. He also has research experience with Bull SAS, and an IT Credit Risk Manager with Société Générale while in France. Sebastien has taught various computer science courses for the past ten years. This time was spent between the University of Versailles and the University of Delaware. Courses included: Computer Architecture, Parallel Architecture, Operating System, and Advanced Programming. Sebastien is also an instructor in the Master Program in Computer Science and FIN-MATH program of the university where he teaches advanced programming.
Courses: Advanced Python for Streaming Analytics
Jim Guangjin Xiao is an AVP Analytics at CNA Insurance Companies. He received his Master of Science in Applied Statistics from Bowling Green State University in Ohio. Mr. Xiao is a fellow actuary (FCAS) practicing in the property and casualty insurance industry, and is an active member of Casualty Actuarial Society and American Academy of Actuaries. Mr. Xiao has ten years of research and modeling experience in predictive analytics for both personal and commercial lines focusing on insurance product pricing, customer segmentation, and risk management.
Courses: Credit and Insurance Risk Analytics
Kevin Hartman is a devoted and artistic practitioner of data. He believes data must do more than simply provide insights that motivate creative thought. Rather, data must express insights in ways that are just as creative as the ideas they inspire. As Head of Industry at Google, Kevin and his team partner with major advertisers, creative agencies, and media companies to develop digital solutions that build businesses and brands. His approach mixes science and art to deliver inventive, fact-based strategies that reduce uncertainty and increase effectiveness in the marketing and advertising programs they create. Kevin’s roster of client work is long and varied, and includes brand names such as Nestle, General Mills, Kellogg's, Anheuser-Busch, MillerCoors, Motorola, the United States Postal Service, Taco Bell, Kentucky Fried Chicken, Del Monte, Boeing, Qualcomm, Wagner USA, ABN Amro, Bank of America, and the Chicago Board of Trade, among others. Kevin holds a BA from the University of Notre Dame, a MPP from the University of Chicago's Harris School, and an MBA with honors from the University of Chicago's Graduate School of Business. He teaches extensively on topics related to marketing, digital analytics, and data management and is on the adjunct teaching staffs at the University of Chicago, the University of Notre Dame, and the University of Illinois.
Courses: Digital Marketing Analytics in Theory and Practice
Joon-Ku Im is a statistical modeler at one of the leading U.S. consumer financial service companies. His experience includes development of loss forecasting models for consumer loan portfolio as well as development of scorecard models for consumer loan underwriting. He enjoys translating analytical findings into business insights. Joon-Ku earned his PhD in Industrial Engineering and Management Sciences from Northwestern University and his dissertation discusses methodologies for identification of nonlinear variation sources. He also earned MS in Mathematics from The Ohio State University and BS in Mathematics from Seoul National University (South Korea). While studying in The Ohio State University, he worked as a lecturer for 2 years and found it both interesting and challenging to deliver technical knowledge to students.
Courses: Credit and Insurance Risk Analytics
Nick Kadochnikov is a Distinguished Engineer in Data Science and Cognitive Analytics within IBM's Chief Analytics Office. Nick's expertise lies in the areas of Big Data, data mining, predictive modeling, econometric modeling, social media analytics and natural language processing. In his 15+ years professional career Nick has been applying analytics to various areas of the business, such as marketing, sales, fraud detection, product development, financial optimization, process simplification, and engagement analytics. Nick has been leveraging Big Data and data mining techniques to develop a multitude of analytical deliverables, including client wallet estimates and client segmentation models; cost-benefit modeling; propensity to buy, cross-sell and up-sell modeling; fraud, abuse and error detection; development productivity optimization and social business analytics.
Courses: Big Data and Text Analytics, Data Visualization Techniques
Dr. Lam is a data scientist with over twenty years of practicing predictive analytics in software development, property and casualty insurance, and retail financial service industries. Ming-Long has strong expertise in developing statistical algorithms, customizing solutions for analyzing person data, and implementing solutions in major statistical software. Ming-Long is currently a Senior Manager of Advanced Analytics R&D at the SAS Institute. Prior to the SAS Institute, Ming-Long had a rewarding career in directing development of analytical features in SPSS. In between these two major statistical software vendors, Ming-Long developed rating plans for Allstate to set insurance premiums and assessment models for Chase to recruit their retail financial staff. Ming-Long has co-published the book Using Data Analysis to Improve Student Learning: Toward 100% Proficiency. Ming-Long holds a PhD in Statistics from the University of Chicago.
Courses: Data Mining Principles, Statistical Analysis
Katie Malone is a data scientist with experience in data science consulting, software development, management, and machine learning education. She currently is the Director of Data Science Research and Development at Civis Analytics, a Chicago-based data science software and consulting firm, where she manages a team of data scientists who specialize in causal inference, supervised and unsupervised machine learning, and predicting individual-level attitudes and behavior. Her previous experience includes spending two years in Switzerland doing Higgs boson research at CERN, and also teaching the Introduction to Machine Learning course for the online education startup Udacity. She holds a PhD in experimental particle physics from Stanford University and hosts Linear Digressions, a podcast on data science and machine learning.
Courses: Machine Learning and Predictive Analytics
Roger is a Senior Director at Gartner, the world's leading information technology research and advisory firm. Roger assists clients in the application of data and analytics to drive new insights and better decisions. Roger has also worked at Sagence, Booz & Co, PwC, Diamond Management & Technology Partners and the Boston Consulting Group. His experience spans financial services, insurance, manufacturing, retail, industrial goods and healthcare. Roger is active in the data, analytics and technology communities in the Chicago area. He attends many MeetUps, roundtables and industry events. Roger founded and chairs the Chicago Booth Big Data & Analytics Roundtable and is a board member of the Chicago City Data User Group. Roger has experience speaking in many venues, including providing the opening address at the Predictive Analytics & Business Insights 2015 Conference. He has also spoken at the Executives Club, Booth Innovation Roundtable, DePaul Predictive Analytics Club, UIC CRIM Speaker Series, Indiana University ICSAC Conference, University of Chicago GradUCon and UIUC Speaker Series. Roger holds an MBA with focus in Finance and Statistics from the University of Chicago's Booth School of Business. He also received a BS in Electrical and Computer Engineering from the University of Wisconsin - Madison
Courses: Leadership Skills
Courses: Programming for Analytics, R Workshop
Ashish Pujari is a leader in data and analytics, IT strategy and technology consulting. As a Director of Analytics at GLG, Ashish leads the design and implementation of business intelligence, predictive analytics and visualization. Prior to joining GLG, Ashish served as an AVP of Analytics Architecture for CNA Insurance where he was responsible for insurance analytics platforms and data strategy.
Ashish specializes in big-data analytics, cloud computing, algorithm development, application and database design, decision management and visualization technologies. Ashish has been involved in technology consulting in finance, banking, insurance and communications domains for clients in Europe, North America and Asia.
Ashish earned a Master of Science in Analytics from the University of Chicago, and Bachelor’s in Electrical Engineering from the National Institute of Technology, Rourkela. His research interests include parallel and distributed systems and machine learning.
Courses: Data Engineering Platforms for Analytics, Big Data Platforms, Deep Learning and Image Recognition
Jonathan Williams has been working in statistical consulting for ten years, and currently manages data science teams at Civis Analytics, working on behalf of public sector clients. Previously he worked as a Vice President at Compass Lexecon, providing and supporting expert reports and expert testimony for litigation. Jonathan earned Bachelor's and Master's degrees in Statistics from the University of Chicago ('07, '08) and is also a recent alumni of the MSCA program ('16). He also co-instructs courses for the Graham School certificate programs along with Professor Yuri Balasanov. Jonathan's focuses include data visualization, technical writing, financial valuation, mortgage portfolio modeling, and damages estimation.
Courses: Statistical Analysis Review
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