Grace Lin

Grace Lin

Past Awards

George E. Kimball Medal: Winner(s)
2020 - Winner(s)

Grace Lin is vice president, director of the Big Data Research Center, and chair professor in the Department of Business Administration at Asia University in Taichung, Taiwan since 2016. She recently founded the United Financial Intelligence Corp. (UFI) to support digital transformation and care quality improvement of aging care organizations. From 2011 to 2016, Dr. Lin was the founder and VP of the Data Analytics Technology and Applications (DATA) Institute and VP for the Advanced Research Institute (ARI) at the Institute for Information Industry (III). At III, she initiated key industry-government R&D programs including Smart Living and Smart Commerce Strategy Plan, Big Data Analytics, Smart Healthcare, Smart Tourism, FinTech, and Smart Agriculture. Previously, Dr. Lin worked for IBM US for more than 16 years as the Global Sense-and-Respond Value-Net Leader and CTO & director for Innovation and Emerging Solutions at IBM Global Business Services, and as a research staff member, manager, and senior manager at the IBM T.J. Watson Research Center. She was an elected member of the IBM Academy of Technology, an IBM Distinguished Engineer, and Relationship Manager for IBM's Integrated Supply Chain.

Her background and experience have positioned Dr. Lin at the intersection of technology, innovation, business consulting, and management as well as the intersection of academia and industry. Referred to by Forrester as one of the six supply chain gurus, Dr. Lin has published more than 80 technical papers, book chapters, and articles, and co-authored 10 U.S. patents and nine Taiwan patents. In 2006, she was named an INFORMS Fellow.

Dr. Lin's service to INFORMS and the profession has been substantial. She has been twice elected INFORMS VP Practice and VP International Activities, she has chaired the INFORMS Fellow Selection Committee and several INFORMS and IEEE conferences. Additionally, she has been active in the Edelman Award Competition, having served multiple years as judge and as a member of the selection committee. Active in WORMS, she has been a strong supporter of women in O.R. Passionate about bridging the gap between academia and industry, she has served on a number of university advisory boards. She has also served on National Science Foundation panels in the U.S., Canada, and Ireland, and editorial boards including Manufacturing & Service Operations Management (M&SOM)Operations ResearchINFORMS Journal on Applied Analytics, and Service Science. She is a frequent keynote speaker at global conferences and industry events.

Dr Lin's awards include the INFORMS Franz Edelman Award, IBM Outstanding Technical Achievement Award, IBM Corporate Logistics Award, IBM Research Division Award, IIE Doctoral Dissertation Award, the Purdue Outstanding Industrial Engineer Award, and the Distinguished Alumni Award from the School of Science, National Tsing Hua University, Hsin-Ju, Taiwan.

For exemplary and distinguished service to INFORMS and the profession of operations research, management science, and analytics, the Institute for Operations Research and the Management Sciences expresses its sincere appreciation to Grace Lin by awarding her the 2020 George E. Kimball Medal.

Volunteer Service Award: Winner(s)

INFORMS Elected Fellows: Awardee(s)

Franz Edelman Award: Winner(s)
Winning material: Extended-Enterprise Supply-Chain Management at IBM Personal Systems Group and Other Divisions
1999 - Winner(s)

This award was given to IBM in recognition of their global supply chain re-engineering effort to improve customer responsiveness with minimal inventory. To support this effort, a supply chain analysis tool, called the Asset Management Tool, was developed and implemented. This tool consists of an optimization engine, a simulator, and a series of data extraction modules. It has been used by IBM to study a wide range of global issues. Benefits generated by the program include $750M in material cost savings and price protection. The model was instrumental in improving the performance of the Personal Systems Group. It has also been implemented in several other IBMS activities as well as some of their customers.

Access the winning project’s companion paper