DAC welcomes new faculty Jiepu Jiang and Anuj Karpatne

The Discovery Analytics Center continually brings together computer scientists, engineers, and statisticians to meet the research and workforce needs of today’s data-driven society. This fall, DAC welcomes two new faculty to bolster its strengths in information retrieval, data mining, human-computer interaction, and information science.

The two new faculty members are Jiepu Jiang and Anuj Karpatne, both assistant professors in the Department of Computer Science.

Jiepu Jiang joins Virginia Tech from the University of Massachusetts Amherst, where he worked with James Allan on researching information retrieval techniques at the Center for Intelligent Information Retrieval. He also taught a graduate level course on information retrieval.

In 2016, he earned a Ph.D. in library and information science from the University of Pittsburgh. His dissertation was entitled “Ephemeral Relevance and User Activities in a Search Session.”

Presently, Jiang is working toward another doctoral degree in computer science from the University of Massachusetts.

Jiang said he is committed to helping people quickly find and use information. His current research agenda is to study sociotechnical issues between human and various AI systems, particularly search engines, conversational systems, and exploratory text analytics systems. He is also teaching a graduate course on Information Storage and Retrieval at Virginia Tech this fall.

Jiang has been regularly published in leading information retrieval and data mining conferences such as SIGIR, WSDM, and CIKM. In 2017, he received the best student paper award from the ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR) for his work on understanding dynamics of search result judgments in information retrieval.

“I feel greatly fortunate to join DAC, a highly vibrant, diverse, and interdisciplinary group working on cutting-edge data analytics problems,” Jiang said.

Anuj Karpatne received his Ph.D. from the University of Minnesota with Vipin Kumar in September 2017. Following graduation, he was a postdoc with Kumar until joining Virginia Tech in August 2018.

His research explores how data mining and machine learning methods can accelerate scientific discovery and address some of the major challenges facing our society. A primary focus of Karpatne’s research is to advance the paradigm of theory-guided data science, where machine learning methods are deeply integrated with scientific knowledge (or theories) that underlie real-world phenomena in physical and life sciences. An overarching goal of this paradigm is to develop generalizable and physically consistent machine learning methods that can augment current gaps in our understanding of physical processes by effectively using physics and data. Karpatne’s prior research builds the foundations of this paradigm and explores its applications at the intersection of food, energy, and water.

He is teaching an advanced topics course on Machine Learning Meets Physics this semester, which is aligned with his research interests.

Karpatne said he is excited to be a part of DAC to work on inter-disciplinary problems at the intersection of data science and scientific problems. “DAC provides an ideal setup to fully explore the power of data science methods in accelerating scientific discovery,” said Karpatne. He is looking forward to collaborate with DAC students and researchers who are interested in solving real-world problems in physical and life sciences by pursuing novel research in data science.

Karpatne is also a coauthor of the textbook “Introduction to Data Mining (2nd edition),” published by Pearson.

“Virginia Tech is leading the way in big data research and education,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering in the Department of Computer Science and DAC director. “Adding faculty like Jiepu and Anuj, experts in their respective fields, not only enhances DAC’s research capabilities but offers tremendous educational opportunities to our students as they are exposed to cross-cutting areas.”

The Discovery Analytics Center has become a well-recognized force among the analytics community within the commonwealth and beyond, and fosters multi-stakeholder collaborations with fellow universities, leading industry affiliates, government agencies, and nonprofit organizations. Officially housed within the Computer Science Department, faculty and graduate students represent computer science, statistics, electrical and computer engineering, and math.