Abid Ali is currently working in Capgemini as portfolio manager in the global insights and data practice supporting financial services group across banking and insurance. He has an undergraduate degree in computer sciences, a master's in business intelligence and data warehousing, another master's in information and knowledge strategy, an EMBA, and a Ph.D. in organizational leadership. He has various industry certifications such as Teradata certified master, SAFe agilist, Celonis sales professional, and Azure fundamentals. He has several years of international consulting experience leading, designing, and delivering large scale data and reporting solutions in the U.S., Great Britain, Europe, and Asia Pacific. He is experienced in various industries such as retail, insurance, finance, banking, telecom, and travel.  Ali specializes in data architecture design and implementation, data warehousing and business intelligence, and advanced analytics. His research interests include data analytics, organizational leadership, diversity and inclusion, and social and industrial/organizational psychology.  Ali delivers guest lectures in different universities and has also taught in Columbia University, NYC in their master's of applied analytics program.


Edward Arroyo has worked for both on-ground and online universities in a variety of capacities during the last fifteen years. During that period he has taught undergraduate and graduate mathematics courses as well as undergraduate programming and theoretical computer science courses. In addition, he worked for several years outside of academia as a test engineer for a digital media company. His research interests and publications are in the areas of combinatorics and image reconstruction algorithms in computerized and discrete tomography. He holds a Ph.D. in pure mathematics from the Graduate School and University Center of CUNY.


Lynd Bacon

Lynd Bacon

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Currently teaching:
Practical Machine Learning

Lynd Bacon is an applied scientist. He is an Adjunct Associate Professor in the Division of Epidemiology, Department of Internal Medicine, the University of Utah. At Utah he teaches graduate and post-graduate courses in data science, machine learning, statistics, and research methods. He does research about health services delivery, product and service design, and genomic testing. His prior teaching experience includes having taught at The David Eccles School of Business at the University of Utah, Notre Dame’s Mendoza School of Business, The University of Chicago’s Booth School of Business, Rush University, The University of Illinois at Urbana-Champaign, and the University of Illinois at Chicago. Bacon has founded two software companies, and has held senior management and chief research officer positions in venture-funded start-up companies and in global business intelligence enterprises. Bacon has a PhD and an MA in cognitive and physiological experimental Psychology from the University of Illinois at Chicago, and an MBA with specializations in marketing, econometrics, and healthcare management from the Booth School of Business. He completed a two year postdoctoral fellowship in neuropsychology at Rush University in Chicago, where he did neuroscience research on healthy and patient populations.


Atef Bader has been working in the IT industry for many years and currently is a member of the technical staff at Lucent Technologies. He is a recognized expert in object-oriented technology, automated software testing, concurrent software systems and software architecture. His technical papers have been presented at numerous conferences and published in technical journals. Bader holds a PhD in computer science from Illinois Institute of Technology.


Shreenidhi Bharadwaj

Shreenidhi Bharadwaj

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Shreenidhi Bharadwaj is an educator, data enthusiast and an analytics practitioner. Currently, as M&A COE lead, he advises Private Equity/Venture Capital firms and C-level Executives on value creation, post-close synergies along with data & analytics(BI/AI) strategies focused on business outcomes. In his previous executive leadership role at Syndigo, Bharadwaj led the data strategy, data science, next-gen platform and M&A integrations. His expertise revolves around driving innovation, standardization, development & operationalizing machine learning models, data engineering at scale using on premise & cloud platforms, effective data visualizations, model-driven design & algorithmic thinking. He was elected to the Global Standards Architecture Board at GS1, where he worked with global industry leaders to develop standards, road maps, governance & compliance requirements relating to food services, healthcare, retail, supply chain & CPG/FMCG verticals. His experience spans multiple verticals such as Healthcare, Retail, MarTech, AdTech, EdTech, FinTech, Telecom and public safety with companies operating as startups to fortune 100.  Bharadwaj is a graduate of the MS Analytics program from The University of Chicago and BE, Electronics and Communications from Manipal Institute of Technology, India. His interests include Data Engineering, Intelligent Systems and Robotics, Machine Learning at scale, Data Visualization & Knowledge Engineering


Candice Bradley is a quantitative social scientist with over two decades experience teaching statistics and research methods at the graduate level. Trained at UC Irvine’s interdisciplinary Social Relations program, Bradley followed her doctoral studies with a Fulbright Fellowship to Africa, engaging in fieldwork documenting the start of Kenya’s fertility decline. As a quantitative anthropologist, a rather rare specialization in a discipline not known for number crunching, Bradley has published research using multivariate analyses in such areas as demography, academic advancement of women, cross-cultural methodology, deep ecology, and time allocation. Bradley earned her PhD and masters from UC Irvine in social sciences.


Kimberly Chulis is cofounder and CEO of Core Analytics, LLC. With over 20 years of professional advanced analytics experience, Chulis demonstrated analytic expertise on projects at numerous companies and industries, including Microsoft, IBM, Dell, WellPoint, HCSC, UHG, Great West, Accenture, Ogilvy, MSN, Sprint/Nextel, Commonwealth Edison, TXU, Eloyalty, SPSS, General Motors, Allstate, Cendant, and others in the financial, telecommunications, healthcare, energy, nonprofit, retail, and educational sectors. Her current research focus is on Social Media Behavioral Applications, Big Data, Applied and Predictive Analytics. Her secondary focus is social media as a platform to drive positive public health, disease-related community support, early detection and intervention for healthcare outcomes. Chulis holds a PhD from Purdue University's Health and Human Sciences Consumer Behavior program, and a masters degree in economics with a focus on health economics and econometrics from the University of Illinois at Chicago. She is faculty in the MS Predictive Analytics program at Northwestern University since 2014, and served in the role of Director, Business Analytics Certificate Program at University of Chicago Graham School.


John Derwent is an experienced learning professional with an analytical bent and is currently adjunct faculty and program advisor for the Certificate in Predictive Business Analytics program and adjunct faculty with the Masters of Science in Predictive Analytics program at Northwestern University. After completing his graduate work, he moved into the world of corporate education and development practicing mainly in the software and technology industries. Most recently, Derwent led content and offering strategy for education services in the business analytics area with SPSS, Inc and IBM. His main professional goal is to help people understand how mathematics can improve businesses and the world. Derwent earned his PhD at Northwestern University in applied mathematics.


Sharon Dill is an Information Technology professional with 35 years’ experience. She recently retired from the Professional Association of Diving Instructors (PADI) where she was the Chief Information Officer and the Chief Data Officer. Throughout all the technology implementations over Sharon’s 28 years at PADI, data was always at the center and a focus. Sharon created an enterprise data rich environment that allowed for strategic planning and business decisions to be made based on data-driven insights. She also has vast knowledge on global data requirements, third party integrations data sharing and implementing self service business intelligence with data warehouse implementation. Sharon has a doctorate in computer science from Colorado Technical University with an emphasis in Enterprise Information Systems and she is a graduate of Northwestern’s M.S. in Predictive Analytics program.


Lawrence Fulton

Lawrence Fulton

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Currently teaching:
Practical Machine Learning

Lawrence Van Fulton is an associate professor at Texas State University. His research interests include the application of machine learning, simulation, optimization, statistics, and decision science to aeromedical evacuation, sustainability, and healthcare in general. Currently, he is applying machine learning techniques for classification of brain imagery. He has published in journals including Multivariate Behavioral Research, Pain, Interfaces, Simulation, IIE Transactions on Healthcare Systems Engineering, Journal of Healthcare Management, Journal of Nursing Administration, and many others. Dr. Fulton served a quarter of a century in the U.S. Army Medical Department, attaining the rank of colonel prior to his retirement. His earned PhD in management science is from the University of Texas at Austin, and he holds five separate masters degrees, including a master of science in statistics from UT Austin.


Noah Gift

Noah Gift

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Currently teaching:
Practical Machine Learning

Noah Gift is lecturer and consultant at both UC Davis Graduate School of Management MSBA program and the Graduate Data Science program, MSDS, at Northwestern . He is teaching and designing graduate machine learning, AI, Data Science courses and consulting on Machine Learning and Cloud Architecture for students and faculty. These responsibilities including leading a multi-cloud certification initiative for students. He has published close to 100 technical publications including two books on subjects ranging from Cloud Machine Learning to DevOps. Gift received an MBA from UC Davis, a M.S. in Computer Information Systems from Cal State Los Angeles, and a B.S. in Nutritional Science from Cal Poly San Luis Obispo.  Currently he is consulting startups and other companies, on Machine Learning, Cloud Architecture and CTO level consulting as the founder of Pragmatic AI Labs. His most recent book is Pragmatic AI: An introduction to Cloud-Based Machine Learning (Pearson, 2018).


Lance Levenson

Lance Levenson

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Lance Levenson is a Principal Data Scientist and Analytics Team Lead at Walmart Labs where he is responsible for architecting, designing, and implementing enterprise level machine learning and analytics products/services for various internal business groups across the globe. Prior to Walmart, he was an analytics consultant working with various trading firms and hedge funds in the Chicago and New York areas, building and implementing quantitative and predictive models using massive financial datasets. He is an experienced instructor of quantitative disciplines at both the undergraduate and graduate levels, having also held teaching positions in the fields of physics, astronomy, and mathematics. Levenson also teaches the Advanced Modeling and Risk Analytics courses in the Predictive Business Analytics Program, where he received the 2015 Distinguished Teaching Award. He holds bachelor’s degrees in Astrophysics and Mathematics from Arizona State University and a master’s degree in Financial/Applied Mathematics from the University of Chicago.


Nethra Sambamoorthi is an adviser for CRMportals, a global analytics consulting company. In addition to delivering client solutions, he specializes in building best practices in data capture, designing innovative solutions and creating thought leadership in consumer dynamics and marketing intelligence. Sambamoorthi has produced many of the best practices in predictive modeling across multiple industries—credit cards, auto insurance, investment services, retail, CPG and pharmaceutical marketing. He previously was an entrepreneur, focusing on developing and delivering real-time email marketing systems and ROI trends. He has also worked with XLmarketing Corporation, Acxiom Corporation, Schering Plough Corporation, American Express and Prudential, using marketing analytics to address regulatory aspects while optimizing for return on investment and for consumer engagement. Sambamoorthi received a PhD from the University of Pittsburgh, specializing in applied multivariate statistics, and an MA in mathematics and an MSc in statistics from the University of Madras.


Irene Tsapara has worked in the financial industry for 5 years as a financial engineer, building financial algorithms for trading systems at Goldman Sachs/Hull Trading and Hedge Fund Research company. She has taught for over 20 years in universities across the US and Europe and speaks English and Greek fluently and she has a good knowledge of French and Spanish. Tsapara earned her PhD in mathematical computer science from University of Illinois with a focus in computational learning theory and universal algebra. She holds a masters in computer science from University of Illinois and a bachelors in mathematics from University of Patras.


Donald Wedding

Donald Wedding

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Currently teaching:
Practical Machine Learning

Donald Wedding has over twenty years of experience in the field of Data Science. He has worked in a variety of industries including Banking, Insurance, and Telecom. He has also spent time as a freelance consultant and spent over 10 years working at the SAS Institute. He currently works as a Customer Facing Data Scientist for Data Robot. Dr. Wedding joined the faculty of Northwestern in 2013 and has developed and taught a variety of courses. He is a frequent presenter on analytic topics at conferences, user groups and industry meetings. He is particularly interested in segmentation and cluster analysis and machine learning algorithms. He received his PhD in Engineering Systems from the University of Toledo, where he specialized in machine learning and expert systems. He has an MS in Engineering from the University of Toledo, an MS in Management from the University of Akron and an MS in Data Mining from Central Connecticut State University. He is also a graduate of the Stonier Graduate School of Banking.


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