The UMass Amherst College of Information and Computer Sciences’ Accomplishments in Search & Mining Award recognizes CICS doctoral students who have research achievements in the broad areas of search and text mining. This award was created by industry sponsors to acknowledge our college’s distinguished reputation in these two areas. The recipients are chosen by a CICS faculty committee.
The 2017 CICS Accomplishments in Search & Mining Awards are sponsored by Microsoft Research. This year’s award recipients are:
Since starting at the CIIR in 2014, Qingyao has been involved with 10 published papers on neural network models in IR, and presented the 10th at SIGIR this summer. He is working on applying neural network models on IR problems including non-factoid question answering, ad-hoc retrieval, and learning to rank.
Bio: Qingyao Ai is an M.S./Ph.D. student advised by Prof. W. Bruce Croft in the Center for Intelligent Information Retrieval (CIIR), College of Information and Computer Sciences, University of Massachusetts Amherst. His research mainly focuses on Information Retrieval and Machine Learning related topics. Currently he is working on applying neural network models on IR problems including non-factoid question answering, ad-hoc retrieval and learning to rank. Qingyao received a bachelor's degree from the Dept. Computer Science & Technology, Tsinghua Univeristy, and finished his undergraduate thesis project in the THUIR lab, advised by Prof. Yiqun Liu. He has interned at Microsoft Research and Google. More on Qingyao's research.
Ari has been a leader in interactive AI, including probabilistic reasoning about human edits to knowledge bases and expertise matching tasks. He also has been instrumental in developing tools addressing reviewer-paper matching for CVPR and ECCV, improving scientific peer review.
Bio: Ari Kobren is a Ph.D. student at UMass Amherst working in the Information Extraction and Synthesis Laboratory with Professor Andrew McCallum. Currently, he is working on interactive data integration--or combining multiple, heterogeneous sources of data into a single, consistent knowledge base with a human in the loop. He also works on clustering, crowdsourcing, entity resolution, information extraction and paper matching. He is broadly interested in interactive machine learning, scalable algorithms and integer programming. Ari received a B.S. in Computer Science from Tufts University and worked as a researcher at MIT Lincoln Laboratory building intelligent decision support systems for US intelligence analysts. He has interned at Google Mountain View and Google NYC. More on Ari's research.
View the list of previous recipients.