JingJing Zhang is a doctoral candidate in the Information and Decision Sciences department at the Carlson School of Management, University of Minnesota.  She holds a Bachelor of Business Administration in Management Information Systems from the Beijing Information Technology Institute in China.  She also holds a Master of Science in Computer Information Science from Temole University in Philadelphia.  JingJing's research interest focus on personalization techniques in business applications, recommender systems and data mining.

Background: "After i finished my Bachelor degree in MIS, i enrolled in the Master's program in Computer Informatio Science to consolidate my academic foundation and to further improve my technical expertise.  I made myself exposed to a variety of theories and techniques in data mining, data compression and pattern analysis.  I took part in several research project in clustering, texture and topology patter analysis of medical images, content-based information retrieval, and time series analysis.  In collaboration with the professors from different disciplines and different universities, i contributed to several papers that appeared in interdisciplinary conferences.

Research Interest: "My research interests mainly lie in bringing principles and techniques from computer science to the design and implementation of personalized and user-friendly systems and tools.  To this end, i have pursued research, both theoretical and experimental, using computer science and social science as the dominat referent disciplines.  I plan to continue to draw on methodologies from data mining, recommender systems and human-computer interaction in developing computational solutions for emerging business issues.  I deploy multiple research methods including empirical estimation, computer simulation and surveys."

Current Research Projects: "I am currently exploring two streams of research related to my interest.  First, i am working with professors Adomavicius and Gupta to develop a simulation model of recommender system.  We look at the evolution of recommender systems and examine the effect of diverse condition on the dynamic of recommender systems and the ultimate business goals.  We hope to understand the dynamic interaction between human and computer as well as the effect of these interactions.  Second, i am working with professor Adomavicius to explore the design and development of personalized online assistant.  We design and conduct multiple experiments to examine what information is most relevant and valuable to users.  We hope to design a "zero-input" software agent that learns user's profile in real time and provides a continuous stream of recommendations that might interest user."

General Impression: "The past two years in the doctoral program in Information and Decision Sciences have been a challenging and yet very rewarding experience to me.  I am very impressed by the breadth and diversity of faculty research in IDS.  As a student, i am provided with a unique opportunity to explore all facets of Information Systems research.  I am encouraged to work closely with faculty members and faculty members are always willing to discuss new ideas and to share their expertise and experiences.  I've benefited a lot from the support and advice provided by many faculty members in the IDS department."