Ke (Adam) Zhou is an assistant professor in School of Computer Science, University of Nottingham, and an academic consultant for Yahoo! Research. His research interests and expertise lie in web search and analytics, user engagement modeling, evaluation metrics, text mining and human computer interaction. He has published in reputable conferences and journals (SIGIR, WWW, CIKM, TOIS, PLOS ONE), and served as PC member or reviewer for SIGIR, CIKM, WSDM, ECIR, AIRS, TOIS, IP&M and TKDE. He has also won the best paper award in ECIR'15 and CHIIR'16, and best paper honorable mention in SIGIR'15.
He served as a co-organizer for NTCIR-11/12 IMine task, TREC FedWeb 2014 task, Heterogeneous Information Access (HIA) workshop at WSDM'15 & SIGIR'16, and Poster & Demo Chair at AIRS'16. Prior to joining Nottingham, he was a research scientist working in user engagement/ad quality science team in Yahoo Research. Before joining Yahoo, he was previously a research associate in Language Technology Group in University of Edinburgh, working on text mining and information retrieval from 2013. Prior to this, he has conducted his PhD research on aggregated search at the Information Retrieval Group in University of Glasgow.
If you can not access the website, check the slightly outdated website/version here: http://www.cs.nott.ac.uk/~pszkz/
I'm always interested in recruiting passionate PhD candidates who want to explore Information Retrieval, Text/Data Mining and Machine Learning.
There are fully funded PhD studentship, CSC (China Scholarships Council) funding and others.
Interested candidates should send a CV, a research proposal and academic transcripts to Dr. Ke Zhou (ke DOT zhou AT nottingham DOT ac DOT uk). Please use your name and "IR PhD Position" as your email subject (e.g. "Steve Johns: IR PhD Position").
LUO, CHENG, LIU, YIQUN, SAKAI, TETSUYA, ZHOU, KE, ZHANG, FAN, LI, XUE and MA, SHAOPING, 2017. Does Document Relevance Affect the Searcher's Perception of Time? In: Proceedings of the Tenth ACM International Conference on Web Search and Data Mining. 141-150