Faculty

PhD, MS, University of Southern California; MTech, IIT- Madras; BEng, Anna University

Arif Ansari is an expert in the area of data mining, business intelligence, data warehousing, and intelligent systems and technologies, a field in which he has fifteen years of research experience. He has published in IEEE Transactions on Systems and Man and Cybernetics. Professor Ansari received Marshall's Golden Apple Award in 2006.

PhD, UCLA Anderson School of Management; MS & BS, Industrial Engineering, Bilkent University

Murat Bayiz is a Professor of Clinical Data Sciences and Operations at Marshall School of Business. He has more than two decades of combined management consulting and academic experience and specializes in operations strategy.

Murat teaches core and elective at Marshall School’s undergraduate, MS in GSCM, and MBA programs. In recent years he received five Golden Apple awards for teaching excellence and the Evan Thompson award for teaching and learning innovation.

Prior to joining USC, Murat was a management consultant at PRTM Management Consultants (later acquired by PwC) and Kiran Analytics and consulted with high tech companies on supply chain strategy projects.

PhD, Statistics, Stanford (advisor: Robert Tibshirani); BS, Physics, Stanford

Jacob Bien's research focuses on statistical machine learning and in particular the development of novel methods that balance flexibility and interpretability for analyzing complex data. He combines ideas from convex optimization and statistics to develop methods that are of direct use to scientists and others with large datasets. His work has been supported by an NSF CAREER award, a three-year NSF grant on high-dimensional covariance estimation, an NIH R01 grant on methods for multi-view data, and a grant from the Simons Foundation on developing new statistical methodology for oceanography. He serves as an associate editor of Biometrika and the Journal of Computational and Graphical Statistics, and he was previously an associate editor for Biostatistics. Before joining USC, he was an assistant professor at Cornell.

Feng Chen is an operations management scholar. Her research interests include process analysis, supply chain management and supply chain analytics, and experimental study of behavioral impact on operations decision making. She teaches courses of operations management and data analysis for decision making. Feng received her Ph.D. in business administration from University of Southern California.

PhD, MIT; MBA, Indian Institute of Management - Calcutta; BTech, Indian Institute of Technology - Bombay

Sriram Dasu's research has been published Queuing Systems, Operations Research, and Management Science. He has served as associate editor of Management Science and senior editor of Manufacturing and Service Operations. His research interest are healthcare operations, global health, service operations with focus on customer psychology, and supply chain management.

PhD, MS, Cornell University; BS, University of Florida

Andrew Daw is an Assistant Professor of Data Sciences and Operations in the Marshall School of Business at the University of Southern California. He studies the interactions within operations, and his research interests include service systems, stochastic models, and contagion processes. Prior to joining USC, he completed his PhD in the School of Operations Research and Information Engineering at Cornell University.

Ph.D., MIT

Kimon Drakopoulos is an Assistant Professor in the Data Sciences and Operations department at USC Marshall School of Business. His research focuses on the operations of complex networked systems, social networks, stochastic modeling, game theory and information economics. Kimon, prior to joining USC, completed his PhD at the Laboratory for Information and Decision systems at MIT focusing on the analysis and control of contagion processes on networks.

Paromita finished her PhD in June 2019. Before that she obtained a B.Stat. in 2012 and an M.Stat. in 2014 from the Indian Statistical Institute, Kolkata.

Paromita Dubey is an assistant professor in the DSO department at the USC Marshall School of Business. Her research broadly centers around developing novel statistical methods for nonEuclidean data, examples being distribution and network valued data. She is also working on addressing challenges in the analysis of dynamic time-evolving data, particularly in nonEuclidean and high dimensional settings. Aside from theoretical challenges, she enjoys collaborations involving applications in neuroscience and population genetics.

PhD, Stanford University; MBA, American University in Cairo; BS, Cairo University

Omar El Sawy's expertise is in digital business strategy in dynamic environments and business models for digital platforms. He served as Director of Research for Marshall's Institute for Communications Technology Management from 2001-2007. He is the author of over 100 papers and a seven-time winner of the Society for Information Management's Annual Academic Paper Award - most recently in 2015. He is currently Senior Editor of MIS Quarterly and on several editorial boards. He teaches in the MBA program and received the Marshall School's Evan C. Thompson Award for Teaching and Learning Innovation in 2012. He served as advisor to the United Nations Development Programme in Egypt, and as a Fulbright scholar in Finland. In 2008, he was inducted as the 45th Fellow of the Association of Information Systems for his research contributions.

PhD, MS, Princeton University; BS, University of Science and Technology of China

Yingying Fan is Centennial Chair in Business Administration and Professor in Data Sciences and Operations Department at USC Marshall, Professor of Economics at USC, and an Associate Fellow of USC INET. She received her Ph.D. in Operations Research and Financial Engineering from Princeton University in 2007. She was Lecturer in the Department of Statistics at Harvard University (2007-2008). Her research interests include statistics, data science, machine learning, economics, big data and business applications, and artificial intelligence and blockchain. Her papers have been published in journals in statistics, economics, computer science, information theory, and biology.

PhD, Utah State University; MS, BS, Vilnius University

Robertas Gabrys has research interest in functional data analysis and its applications in environmental sciences, financial econometrics, and space physics; statistical computing, and actuarial mathematics. His work has been published in the Journal of the Royal Statistical Society, Journal of Multivariate Analysis, Journal of the American Statistical Association, and Austrian Journal of Statistics.

PhD, MIT; BA, Yale University

Vishal Gupta is an Assistant Professor in Data Sciences and Operations. Vishal completed his PhD in Operations Research from MIT, focusing on data-driven methods in optimization. He earned his BA in Mathematics and Philosophy from Yale University, graduating Magna Cum Laude with honors, and completed Part III of the Mathematics Tripos at the University of Cambridge with distinction as part of the Paul Mellon Graduate Fellowship. In addition, Vishal spent 4 years working in Quantitative Analytics for Barclays Capital with particular emphasis in commodities modeling, derivatives pricing and risk management. He continues to collaborate with industrial partners in electricity markets and financial service providers. Vishal's research interests focus on developing novel techniques for representing uncertainty and behavior in optimization problems. He draws heavily on state-of-the-art statistical techniques for large data sets.

PhD, Stanford University; BSc, BCom, University of Auckland

Gareth James is the Deputy Dean at Marshall. He is an expert on statistical methodology in the areas of functional data analysis and high dimensional statistics, with particular application to marketing. Professor James has published extensively and is a co-author of one of the leading books in the field. He is an elected Fellow of both the American Statistical Association and the Institute of Mathematical Statistics. Dr. James has won several research and teaching awards, including two Deans awards for Research Excellence, three Golden Apple awards for his MBA courses and the Provost’s Mentoring Award. He has also served as an Associate Editor for journals such as JASA, JRSSB and OR.

PhD Stanford University; B.Sc Sharif University of Technology<br>

Adel Javanmard is an associate professor in the department of Data Sciences and Operation, at USC Marshall School of Business. He received his PhD in Electrical Engineering from Stanford University in 2014. His research interests are broadly in the area of high-dimensional statistics, machine learning, optimization, and personal decision making. Adel is the recipient of several highly prestigious awards, including the Alfred Sloan research fellow in mathematics, IMS Tweedie New Researcher Award, NSF CAREER award, Adobe Faculty Research Award, Google Faculty Research Award and the Thomas Cover dissertation award from IEEE Society.

PhD, Princeton University; MS, BS, University of Science and Technology of China

Jinchi Lv is Kenneth King Stonier Chair in Business Administration and Professor in Data Sciences and Operations Department at USC Marshall, Professor of Mathematics at USC, and an Associate Fellow of USC Dornsife Institute for New Economic Thinking (INET). He received his Ph.D. in Mathematics from Princeton University in 2007. He was McAlister Associate Professor in Business Administration at USC (2016-2019). His research interests include statistics, machine learning, data science, business applications, and artificial intelligence and blockchain. His papers have been published in journals in statistics, economics, business, computer science, information theory, neuroscience, and biology.

PhD, MA, UCLA; BA, Pitzer College

Ann Majchrzak is the USC Associates' Chaired Professor of Business Administration for Marshall. She teaches and does research on digital innovation. She is a Fellow of the Association for Information Systems. She has held concurrent appointments at Esade Business School, Ramon Llull University (Barcelona, Spain) Vrije Universiteit Amsterdam, LUISS School of Business and Management (Rome, Italy) and Simon Fraser University (Vancouver Canada) in the areas of Innovation and Organization. She has a 2020 book: Unleashing the Crowd: Collaborative Solutions for Wicked Business and Societal Problems, a Marshall webinar for Covid19 & Small Businesses, and a Tommy Talk on the subject.

Inga Maslova is an applied statistician specializing in time series analysis, machine learning, wavelet techniques, functional data analysis, big data, and applications to finance, business analytics, economics, hydrology, remote sensing, precision agriculture, and climate change problems. She has taught and developed courses in statistical learning, business statistics, data analytics and visualization. To her classroom she brings her own experience from consulting for Cisco, working with the World Bank on business cycle synchronization; analyzing drone data to help farmers make better crop management decisions at Utah Water Research Lab; using statistical learning models to forecast commodity prices. In 2018 she received a Golden Apple Teaching Award for teaching excellence. Before joining USC, Inga was a faculty at American University, Washington DC. She received her BS (Summa Cum Laude) in Mathematical Statistics from Vilnius University, Lithuania; MS and PhD in Statistics from Utah State University.

Milan Miric joined the IS Group within the DSO Department in 2016. His research tries to understand basic questions about how firms can capture and create value in digital industries. In particular, his research tries to understand how the unique structural features of digital industries (network effects, low costs of innovating, non-monetary motivations) influence the process by which firms capture and create value. His work is largely empirical combining large-scale panel datasets with interviews and field work. His research work draws heavily on insights from psychology, economics, and sociology but tries to contribute to the literature on information systems and innovation.

PhD, Stanford University; MStat, BStat, Indian Statistical Institute

Gourab Mukherjee's research focuses on the development of new statistical theories and applied statistics methods for the disciplined analysis of complex data types that arises from various contemporary business and scientific problems. He has reported new phenomena and novel theoretical results in predictive inference and shrinkage methodology. He is also involved in collaborative studies in quantitative marketing and virology.

PhD, University of Southern California; MBA, University of Washington; BEng, Waseda University

Hiroshi Ochiumi is an operations management scholar. His research interests include supply chain management, design and analysis of contracts, and behavioral aspects of decision making. He teaches classes on operations management and designing spreadsheet-based business models. Prior to receiving his PhD, Professor Ochiumi worked for Hilti Japan and Goldman Sachs.

Ph.D. USC; B.S. Illnois State University

Dr. Francis Pereira received his Ph.D. in Political Economy and Public Policy from the University of Southern California. He has published over 15 articles in such prestigious journals as the Journal of Communications Networks.

PhD, MPhil, MS, New York University; BA, Cornell University

Dawn Porter is a statistician who has published in Management Science and is the coauthor of Basic Econometrics (fifth edition). Prior to joining USC, she served on the faculty at Georgetown University. Professor Porter has consulted for KPMG Consulting, Ginnie Mae, Inc., and Toys R Us.

PhD, MS, Carnegie Mellon University; MBA, Indian Institute of Management - Ahmedabad; BTech, Indian Institute of Technology - Madras

Raj Rajagopalan's research covers capacity and technology acquisition, supply chain management, and product variety and its impact on operations performance. He has published in journals such as Management Science, Production and Operations Management, and Operations Research. He served as a Department Editor at IIE Transactions, Senior Editor at Production and Operations Management, and as an Associate Editor at Management Science and Operations Research. Professor Rajagopalan has consulted for Johnson and Johnson, Fidelity Investments, and Hewlett Packard. He has taught courses in operations and supply chain management in the MBA and Executive MBA programs.

PhD, MS, Stanford University; BTech, IIT Delhi

Ramandeep S. Randhawa is an operations research scholar whose research interests include designing service systems, revenue management, stochastic modeling, and mechanism and incentive design. His work has been published in journals that include Management Science, Manufacturing and Service Operations Management, and Operations Research. Prior to joining the Marshall School, he was a faculty member at the McCombs School of Business at the University of Texas.

Phil Rogers received a B.S. in Mathematics from Rensselaer Polytechnic Institute and both an M.S. and Ph.D. in Operations Research from the University of California at Berkeley, with minors in Statistics and Mathematical Economics. During a 33-year career at Exxon Corporation, Phil developed many sophisticated mathematical models that were used to optimize a wide variety of the Corporation's business operations. He then joined the University of Houston, where he taught courses in statistics, business modeling and decision making and was awarded a university-wide teaching excellence award. Following a year-and-a-half stay at Arizona State University, where he taught business modeling and optimization, Phil joined the Marshall School of Business, where he coordinates the undergraduate core statistics course and teaches in the MBA program.

PhD, MS, Stanford University; BA, UC-Berkeley

Paat Rusmevichientong's research focuses on large-scale stochastic optimization problems, with applications to market systems, supply chains, and revenue management. His research has been published in Management Science, Operations Research, and Mathematics of Operations Research. He received the INFORMS George B. Dantzig Dissertation award in 2003 and the NSF CAREER award in 2008. Prior to joining USC, he was a faculty member in the School of Operations Research and Information Engineering at Cornell University, where he was voted Professor of the Year in 2009 and 2011.

PhD, Statistics, Stanford University (advisor: Emmanuel Candès); MS, Physics of Complex Systems, Politecnico di Torino (Italy); BS, Engineering Physics, Politecnico di Torino.

Matteo Sesia is an assistant professor in the department of Data Sciences and Operation, at the USC Marshall School of Business. His research is focused on developing data science methods combining the power of machine learning algorithms with the reliability of rigorous statistical guarantees. While pursuing this goal, he enjoys dividing his time between theoretical, methodological, computational, and applied work. His doctoral research earned the Jerome H. Friedman Applied Statistics Dissertation Award from the Stanford Statistics Department in 2020.

PhD, MS, Utah State University; MS, BS: Lebanese American University

Abbass Sharif’s specialty is in the field of statistical computing and data visualization. Professor Sharif has developed and published new multivariate visualization techniques for functional data and currently he is developing visualization techniques to study brain activity data collected via the near-infrared spectroscopy (NIRS) technology. Professor Sharif teaches statistics courses that range from introductory statistics to data analysis for decision-making through to advanced modern statistical learning techniques.

Peng is interested in developing quantitative methodologies for the betterment of society. His current research focuses on optimization in matching markets, with applications in school choice, public housing, and online marketplaces. His research on school choice has won multiple awards, including the ACM SIGecom Doctoral Dissertation Award, the INFORMS Public Sector Operations Best Paper Competition, and the INFORMS Doing Good with Good Operations OR Student Paper Competition. Prior to joining USC, he completed a PhD in operations research at MIT, and was a post-doctoral researcher at Microsoft Research.

PhD, MA, University of Southern California; BA, University of Michigan

Douglas Shook specializes in the design, implementation and management of information technology, with particular focus on data management, data modeling, and information technology architecture. His academic research centers on the interaction of organizational structure and the effective use of computer-mediated information and communication systems. He has published in Organizational Science and the Journal of Management Studies. Professor Shook received the Excellence in Teaching Award from the Marshall Business Student Government in 2003-2004, the "Teaching Has No Boundaries" award from USC for 2001-2002, Marshall's Golden Apple Award in 1996, 1999, 2001, 2005, and 2009.

PhD, MIT; BS, Cornell University

Somya Singhvi is an assistant professor in Data Sciences and Operations. Somya received his Ph.D. in Operations Research from MIT, focusing on improving the design of digital agri-platforms and markets. He earned his BS in Operations Research & Information Engineering from Cornell University, graduating Magna Cum Laude with honors. Before joining USC, he was a postdoctoral fellow at the Center for Global Development.

Somya’s work uses a combination of field-based research and analytics to improve the design of digital platforms in developing and emerging markets. He continues to collaborate with government organizations and industry partners to drive impact in practice.

PhD, University of British Columbia; MS, BS, University of Zagreb

Greys Sošić holds a PhD from the University of British Columbia, and a master's and a bachelor's degree from the University of Zagreb, Croatia. Her research interests include supply chain management, sustainability, competition and cooperation in supply chains, with emphasis on coalition stability. Her work has been published in Management Science, Operations Research, M&SOM, and POMS. Greys is an Associate Editor for Operations Research, IIE Transactions, and POMS. She has received Dean's Awards for Research Excellence and IISE Transactions Design & Manufacturing Best Paper Award. She has been teaching courses on supply chain management, sustainability, and sourcing.

PhD, Carnegie Mellon University; MBA, University of Delhi; BEng, University of Madras

Ashok Srinivasan's research interests include supply-chain management, nonprofit management, and productivity analysis. His research has appeared in Management Science, Operations Research, European Journal of Operational Research, and Managerial and Decision Economics, including "Leadership and Competition in Network Supply Chains," with P. Majumder, that appeared in Management Science in June 2008.

PhD, Cornell University; BA, Yale University

Mika is an assistant professor in the Department of Data Sciences and Operations at the USC Marshall School of Business. Her research focuses on developing efficient and provably good algorithms for revenue management and resource allocation problems. She is especially interested in problems with applications in online marketplaces, delivery systems, and the sharing economy. She obtained her PhD at the Cornell School of Operations Research and Information Engineering under the supervision of Huseyin Topaloglu. Prior to her PhD, Mika spent two years working in operations and management consulting at Analytics Operations Eng., Inc.

Tianshu Sun's research conducted in collaboration with leading private and public sector platforms addresses how firms can use large-scale field experiments in conjunction with big data to improve business decisions. His current research focuses on understanding 1) how digital platforms can use IT-enabled and data-driven interventions to influence social sharing among individuals, and 2) how organizations can leverage mobile and Internet of Things to integrate individuals' online and offline experience. Tianshu has worked closely with a variety of organizations including Facebook and Alibaba. Many findings from these studies have been implemented by collaborating organizations. Tianshu has given over 70 talks at top universities and international conferences, and has research papers published in Management Science, Information Systems Research, and Journal of Health Economics. Tianshu's research has received 9 Best Paper Awards (ICIS,CIST,WITS,INFORMS), and has been supported by grants from Adobe and Marketing Science Institute.

PhD, University of Pennsylvania; BS, Peking University

Wenguang Sun is a statistician whose research interests include large-scale multiple testing, high-dimensional inference, statistical decision theory, and causal inference. His research has been published in leading statistical journals including Journal of the American Statistical Association and Journal of the Royal Statistical Society, Series B. Professor has won several research awards including the ENAR Distinguished Student Paper Award and Saul Winegrad Dissertation Award from University of Pennsylvania. He received a grant from the National Science Foundation on large-scale multiple testing. Prior to joining USC, he was a faculty member at the Department of Statistics at North Carolina State University.

PhD, Princeton University; BS, University of Toronto

Xin Tong's current research interests focus on asymmetric statistical learning, addressing challenges in the Neyman-Pearson classification paradigm, data distortion, sampling bias, asymmetric groups in classification and clustering, and partial knowledge in clustering and community detection. He has published papers in journals that include Science Advances, Journal of American Statistical Association, Journal of the Royal Statistical Society: Series B and the Journal of Machine Learning Research. Professor Tong's research has been partially supported by US NSF and NIH.

NICK VYAS, BS, MBA, Ed.D, University of Southern California

Dr. Nick Vyas, a practitioner in operations management and organizational excellence through the application of Blended Quality Management, AI, ML, RPA, Blockchain, and Data Analytics received his Doctor of Education from USC with his published dissertation on Conceptualization of Higher Education Excellence System (HEES): Use of Advance Data Analytics and Blended Quality Management. A Subject Matter Expert in End-to-End Global Supply Chain Management (GSCM), Vyas has led business transformation for fortune 100 companies. As USC CGSCM’s Executive Director/ Co-founder, Director of MS GSCM and as an Assistant Professor, he was presented with the Golden Apple Award for teaching excellence and recognized as a “Supply Chain Leader” for the APICS Excellence Awards. As a thought leader, he speaks at conferences on global trade, disruptive technology and GSCM. Vyas serves to make GSCM education accessible through the Gift of Knowledge scholarship at USC MS GSCM program and Supply Chain Professionals without Borders. Working closely with students, Vyas consulted for over 25 global operations across various sectors. He integrated technology and directed teams that both optimized speed-to-market and managed cost/quality.