1. 주 제 : Creative Thinking in Data Mining (DM): How to Formulate the Real-world Problems into DM and Applications

2. 연 사 : 정명기교수 (Rutgers, The State University of New Jersey)

3. 내 용 : With current advances in sensor technology, various sensor signals are increasingly used in order to assess the quality of products and processes in many industries, including the automotive industry, electronics and semiconductor manufacturing, and chemical processes. This creates a tremendous capability for engineers to access valuable information from various manufacturing enterprise entities to improve their operational capabilities. Data mining and machine learning (DMML) have been used to solve several real-life problems. Appropriate formulation of real-life problems into data mining framework is essential to obtain the improved performance of the process. Also, critical and creative thinking along with good domain knowledge is important to adopt existing or develop new DMML techniques to solve the real-life problems successfully. Several real-life sponsored projects of the speaker in the area of semiconductor manufacturing, transportation, bio energy will be briefly presented to illustrate the importance of right formulation and critical thinking. The seminar will be concluded with important future research topics on process monitoring with massive sensor signals. 

4. 일 시 : 2017년 07월 18일 (화) 오후 2:00

5. 장 소 : 39동 325호

6. 문 의 : 장우진교수 (changw@snu.ac.kr)

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Dr. Myong K. (MK) Jeong is the Full Professor in the Department of Industrial and Systems Engineering, RUTCOR (Rutgers Center for Operations Research), and DIMACS (Center for Discrete Mathematics and Theoretical Computer Science) at Rutgers University. 
Currently, he is the Director of Laboratory for Data Analytics and Process Insights. He received his BS in Industrial Engineering from Han Yang University, Seoul, Korea, in 1991, MS in Industrial Engineering from Korea Advanced Institute of Science and Technology, Taejon, Korea, in 1993, MS in Statistics from Georgia Institute of Technology, Atlanta, Georgia, in 2002, and Ph.D. in Industrial and Systems Engineering from Georgia Institute of Technology, Atlanta, Georgia, in 2004. He was formerly an Assistant Professor in the Department of Industrial and Information Engineering, the University of Tennessee, Knoxville. He worked as a senior researcher from 1993 to 1999 at the Electronics and Telecommunications Research Institute (ETRI).

He has focused on developing data mining and machine learning techniques for process monitoring and improvement. The applications include various industries such as gas/oil, semiconductor, transportation, bio-energy, computing, electronics, and automobile. He has published over 90 journal papers including Technometrics, IEEE Transaction on Semiconductor Manufacturing, IEEE Transactions on Systems, Man, Cybernetics, Pattern Recognition Letters, and IIE Transaction on Quality and Reliability. He received the Freund International Scholarship and the National Science Foundation (NSF) CAREER Award in 2002 and in 2007, respectively. His research has been supported by the National Science Foundation, National Transportation Research Center, United States Department of Agriculture, Qatar National Research Fund, Electronics and Telecommunications Research Institute, and various industries. He has been a consultant for Samsung Electronics, Intel, IBM Watson Research Lab., ETRI, KISTI, and other companies. He served as the President of Data Mining Society of INFORMS (Institute for Operations Research and Management Science). He has been an Associate Editor and Advisory Board Member of various journals including IEEE Transactions on Automation Science and Engineering, International Journal of Quality, Statistics and Reliability, and International Journal of Advanced Manufacturing Technology. He is a senior member of IEEE.