Ujjal Kumar Mukherjee

Ujjal Kumar Mukherjee Ph.D. Candidate Phone (o): (612) 626-9762 Supply Chain and Operations Department Cell: (651) 497-8617 Carlson School of Management Fax: (612) 624-8804 321 19 th Street South Minneapolis, MN 55455 AREAS OF INTEREST Research: (Topical Interests) Management of Technology and Innovation, Supply Chain Analytics, Healthcare Management. (Methodological Interests) Big Data Analytics, Predictive Analytic Modeling, Machine Learning Methods, and Advanced Econometrics Teaching: Supply Chain and Operations Management, Supply Chain Analytics, Big Data Analytics in Operations Management, Managing Technologies in Supply Chains, Project Management and New Product Development EDUCATION 1. Ph.D. in Business Administration, Expected 2015 Major: Supply Chain and Operations Management Supporting Field: Statistics Dissertation Title: Managing the Risk and Potential of High Tech Innovations-in-Use: Two Big Data Analytic Modeling Studies and One Longitudinal Field Study 2. MS in Statistics, (All requirements completed) Expected 2015 Thesis Title: High Dimensional Data Geometry Based Multiclass Classification 3. Masters of Business Administration, Xavier Labor Relations Institute (XLRI), India 2002 4. Bachelor of Engineering in Mechanical Engineering, Jadavpur University, India 1997 RECOGNITIONS AND HONORS 1. Qualified as a semi-finalist for the INFORMS Innovative Applications in Analytics Award Competition (in-progress) To be announced in April 2015 2. Carlson School Doctoral Dissertation Fellowship 2014-15 3. Carlson School Ph.D. Student Award for Excellence in Teaching 2014 4. Roger and Marlene Schroeder Ph.D. Doctoral Research Grant 2014 5. Juran Doctoral Research Fellowship Award 2013-14 6. Kristy Cua Doctoral Student Excellence Award and Fellowship 2012 RESEARCH GRANT Co-Principal Investigator on a research grant from Social Media and Business Analytic Collaborative (SOBACO), an inter-disciplinary initiative between the Carlson School of Management and the College of Science and Engineering,, 2013-2014; Grant Amount = $38,000. Page 1

RESEARCH PAPERS Dissertation Research Papers 1. Mukherjee, U. K., and Sinha, K. K. Predicting Failures of High Tech Innovations-in-Use: Application of Predictive Analytics to Big Data on Market Failures of Medical Devices, with Kingshuk K. Sinha,. Job Market Paper. Target Journal: Management Science. [Selected as a semi-finalist in the 2015 INFORMS Innovative Applications in Analytics Award Competition (currently in-progress). The paper was selected for presentation at the 2014 Wharton Technology and Innovation Conference, and at the 2014 Product and Service Innovation Conference at University of Utah.] 2. Mukherjee, U. K., Sinha, S., Bosch, S., and Sinha, K. K. Critical and Complex Technological Capability Development for Health Care Delivery: Multiyear Field Study of a Surgical (da Vinci) Robot in a Multispecialty Hospital, published in Journal of Medical Devices [an American Society of Mechanical Engineers (ASME) journal] Vol. 8, No. 3, September 2014. 3. Mukherjee, U. K., Sinha, S., Bosch, S., and Sinha, K. K. Enabling Health Care Delivery with high Tech Innovation: A Longitudinal Field Study of Robot-Assisted Surgery, Target Journal: Management Science. Research Methods Papers on Big Data Predictive Analytics 4. Mukherjee, U. K., and Chatterjee, S. Fast Algorithm for Computing Weighted Projection Quantiles, Quantile Regression and Data Depth for High-Dimensional Large Data Clouds, Accepted for publication in the Proceedings of Workshop on Scalable Machine Learning: Theory and Applications, October 2014. [The Proceedings has 10% acceptance rate.] [Note: This paper was the outcome of a project in the Research Methods seminar course in the School of Statistics.] [Target Journal for Full Paper: Technometrics] 5. Mukherjee, U. K., and Chatterjee, S. A Fay-Herriot Type Approach to Better Prediction in Multi-indexed Response with Application to Arctic Sea-water Data Analysis, published in Journal of Indian Society of Agricultural Statistics, Vol. 68, No. 2, 2014 (Special Issue on Statistical and Computational Methods for Massive Datasets) [Note: This paper was the outcome of a project in the course on Non-parametric Statistics in the School of Statistics.] Working Papers (In-Progress) 6. Mukherjee, U. K., and Sinha, K. K. Evaluating Judgment Bias in Detecting Failures of High tech Innovations-in-Use: Analysis of Big 7. Juneja, B. S.. Mukherjee, U. K., and Sinha, K. K. The Effect of Social Disparity, Access and Affordability on Cardiac Healthcare Delivery: A Population-level Study using National Health and Nutrition Study (NHANES) Multi-year Database. PRESENTATIONS 1. IEEE Conference on Big Data Analytics, Workshop on Scalable Machine Learning: Theory and Applications, Washington D.C., October 2014. Fast Algorithm for Computing Weighted Projection Quantiles, Quantile Regression and Data Depth for High-Dimensional Large Data Clouds. Page 2

2. Medtronic Big Data and Advanced Analytics Symposium, Minneapolis, September 2014. 3. Annual Conference of the Institute of Engineering in Medicine,, September 2014. 4. Annual Conference of the North Central Biomedical Association, Rochester, September 2014. Strategic Management of Medical Equipment and Devices: From Maintenance Management to Strategic Asset Management. 5. Multidisciplinary Academic Research Summit, Carlson School of Management, August 2014. 6. Special Interest Group on Healthcare Operations, Annual MSOM Conference Workshop, University of Washington at Seattle, June 2014. Variations. 7. American Society of Quality (ASQ), Minnesota Chapter, Annual Meeting, May 2014. 8. Social Media and Business Analytics Collaborative (SOBACO) Annual Conference, University of Minnesota, May 2014. 9. Production & Operations Management Society Annual Meeting, Atlanta, USA, May 2014. (a) Econometric Analysis of the Effect of Technology Innovation on Reducing Process and Outcome Variations. (b) Predicting Failures of High Tech Innovations-in-Use: Application of Predictive Analytics to Big 10. Wharton Technology and Innovation Conference, University of Pennsylvania, April 2014. 11. Minnesota Healthcare Research Conference,, March 2014. Variation. 12. International Symposium of Information Systems, Indian School of Business, India, January 2014. Page 3

13. Design of Medical Devices Annual Conference,, January 2014. Variations. 14. Life Sciences Alley Annual Conference, Minneapolis, November 2013. Variation. 15. INFORMS Annual Meeting, Minneapolis, October 2013. (a) Predicting Failures of High Tech Innovations-in-Use: Application of Predictive Analytics to Big (b) Econometric Analysis of the Effect of Technology Innovation on Reducing Process and Outcome Variations. 16. Annual Conference of Institute of Engineering in Medicine,, September 2013. Variations. 17. Production & Operations Management Society Annual Meeting, Denver, USA, May 2013. (a) Analyzing Sources of Innovation Failures in Medical Devices: An Analytic Framework. (b) Analyzing Sources of Innovation Failures in Medical Devices: An Empirical Modeling Framework. 18. INFORMS Annual Conference, Phoenix, November 2012. Sequential Innovation in New Product Development: Product Architecture and Versioning Strategy. 19. Production & Operations Management Society Annual Meeting, Chicago, May 2012. Sources of Failures in the Medical Device Industry: An Empirical Analysis. 20. Decision Sciences Institute Annual Meeting, Boston, November 2011. Strategic Linkages of Modular Product Designs. TEACHING Instructor, Carlson School of Management, 1. SCO 3001: Introduction to Supply Chain and Operations Management Spring 2014 3 credit, Undergraduate, 96 Students, Overall rating: 5.48/6 Teaching Assistant, Carlson School of Management 2010-2013 2. Supply Chain and Operations Management (Undergraduate and MBA Level) 3. Managing Technologies in Supply Chains (Undergraduate and MBA level) 4. Quality Management and Six Sigma (MBA level) 5. Supply Chain Management (MBA Level) Guest Lecturer 6. Introduction to Big Data Analytics, School of Statistics, Fall 2014 Page 4

DOCTORAL COURSEWORK Content Courses Method Courses Research in Operations Strategy (Shah/Goldstein) Econometric Analysis I & II Management of Technology Operations (Sinha) Advanced Theory of Statistics I & II Quality Management Research (Linderman/Rungtusanatham) Advanced Statistical Methods I, II & III Behavioral Operations Research (Donohue) Advanced Optimization Theory Supply Chain and Optimization Theory (Mehrotra) Decision Analysis and Game Theory Advanced Bayesian Statistics and Hierarchical Modelling Directed Research Seminar in Statistics I & II (Time Series, Distribution theory, Machine Learning and Analytics) Cumulative GPA: 3.85/4 (Total Credits: 73 excluding thesis credits) PROFESSIONAL EXPERIENCE 1. Tata Motors, Europe and North-Africa 2005-2010 Senior Business Development Manager and Board Representative to Tata Hispano, Spain and Tata Hispano, Morocco. Posted in Zaragoza, Spain for the entire period. Responsible for annual revenue and profit targets. Project Head for Morocco Manufacturing Unit set-up, Global Sourcing from China, Turkey and Morocco, Global Bus Chassis Platform Development with target markets in the European Union, S. Korea, Latin America and North Africa. Closely involved with project planning, annual budgeting and financial management. Reported to the CEO of Tata Motors. 2. Tata Motors, India 2002-2005 Manager, Corporate Strategy and Planning. Reported to the CEO of Tata Motors. Was involved in a leading role for global mergers and acquisitions, including Tata Cummins Joint Venture for automotive engines, Tata Daewoo Commercial Vehicle take-over in S. Korea (led the due diligence team in S. Korea), Tata Marcopolo JV in Brazil and India, Tata Hispano JV and takeover in Spain and Morocco, and several other sourcing partnerships including Eaton (USA), ZF (Germany) and Alexander Dennis (UK). 3. Tata Engineering, India 1997-2000 Design Engineer, CAD and CAM team member for vehicle design, extensively worked in CATIA V5 mechanical design and ANSYS analysis engines. COMPUTER PROGRAMMING R, C/C++, Python, Perl, JavaScript and PHP LANGUAGES KNOWN English (Proficient), Spanish (Semi-proficient, can hold business conversations), Bengali (Native), Hindi and French (Basic level) HOBBY Painting. I run a blog on data analytics for predicting soccer outcomes along with Bhupinder Singh Juneja, SPSS statistical product development team, IBM. (http://ubanalytics.wordpress.com/) Page 5

REFERENCES 1. Kingshuk K. Sinha [Ph.D. Dissertation Advisor] Chair and Professor, Supply Chain and Operations Department, and Mosaic Company Professor of Corporate Responsibility Carlson School of Management 321-19th Avenue South Minneapolis, MN 55455, U. S. A. E-mail: ksinha@umn.edu Phone: (612) 624-7058 2. Enno Siemsen [Dissertation Committee Member] Associate Professor, Supply Chain and Operations Department Carlson School of Management 321-19th Avenue South Minneapolis, MN 55455, U. S. A. E-mail: siems017@umn.edu Phone: (612) 625-8905 3. Mili Mehrotra [Dissertation Committee Member] Assistant Professor, Supply Chain and Operations Department Carlson School of Management 321-19th Avenue South Minneapolis, MN 55455, U. S. A. E-mail: milim@umn.edu Phone: (612) 625-8905 4. Snigdhansu Chatterjee [Dissertation Committee Member and MS(Stat) Thesis Advisor] Associate Professor School of Statistics 224 Church Street SE Minneapolis, MN 55455, USA Email: chatterjee@stat.umn.edu Phone: (612) 625-6505 Page 6