Prof. Ram Akella is currently Professor and Director of the Center for Knowledge, Information Systems, and Management of Technology (KISMT) at the University of California at Silicon Valley Center/ Santa Cruz, and was Founding Director of TIM and GEMC -SUNY. His research, with colleagues at KISMT, is focused on technology enterprise profitability and growth, integrating computer science (knowledge management and services, data/text/semantic mining, search, machine learning, IT/IS) with management (innovation management and product development and learning, supply chain management, finance and strategy, marketing)
Ram commenced his academic career in the US at Harvard, and at MIT (LIDS/EECS), where he developed and implemented internationally cited novel stochastic-control algorithms for real time factory management, in collaboration with IBM and Digital. He then joined the faculty at Carnegie Mellon University in 1985 as an Associate Professor in the Business School (GSIA) and the School of Computer Science (Robotics Institute), where he developed seminal results in supply chain management (complex assembly problems with supply uncertainty and supply contracts) in collaboration with IBM, and at MIT (Leader for Manufacturing Program). Subsequently, as a faculty member and Director, at CMU, and then at UC Berkeley (Industrial Engineering and Operations Research) , and Stanford University (Management Science and Engineering) , Prof. Akella led major multi-million dollar interdisciplinary team efforts in Process Learning and Knowledge Analytics in the High Tech and Semiconductor industries. His award winning work has been implemented is dozens of facilities worldwide and altered industry practice. His research and teaching at Stanford University have been in Business Process Optimization and E-Business. The topics include options contracts and exchanges in supply chain management, enterprise software and logistics management, financial engineering and investment in design capacity management, demand management, optimal product portfolios in innovation and risk management, product and process design/development and life cycle management, Knowledge Management, IT & IS, software and business process global outsourcing and off- shoring and cost competitiveness, health and clinical informatics and management.
Professor Akella completed his B.S. in Electronics at I.I.T. Madras, and a Ph.D. in Systems/EECS at I.I.Sc. Bangalore. His doctoral and graduate students have taught at major schools such as Northwestern, Michigan (Ann Arbor), NYU, USC, Dartmouth, and the London Business School, and include Department Chairs, work at corporations such as IBM, KLA-Tencor, TSMC, ABN/AMRO, and BCG, and have gone on to become Vice Presidents of major corporations, such as AT Kearney and WK Technology Fund, and CEOs of startups including Spoke.
He has received several awards, including the IBM Postdoctoral and Faculty Awards, the AMD Research Award, and the KLA Award. He has been cited in Marquis' Who's Who, and has interacted extensively with industries, including those corporations such as AMD, TI, IBM, Digital, Hyundai, LSI Logic, HP, AT&T, KLA-Tencor, Applied Materials, Cisco, SRC, NASA, American Axle, Delphi Automotive, General Motors, Visa, and Rich Food Products, along with various Japanese and European companies. He has also lectured extensively by invitation
in Europe and the Pacific Rim including Japan, Taiwan, China, Korea, and Singapore. He is on the Technical Advisory Council of Yield Dynamics, and boards including E-Soft and UTI Ventures (Unit Trust of India is India's original Govt. mutual fund). He is a Charter member of TIE. He enjoys helping companies grow and become more profitable, and is delighted when executives give him stock as a token of their appreciation.
Professor Akella has served as an Associate Editor for Operations Research and IEEE Transactions on Semiconductor Manufacturing, and has been on the Editorial Board of Technology and Operations Review. He has also served as Guest Editor for IEEE Robotics and Automation: Special Issue on Manufacturing Systems.