The School of Computing has added to its talented staff with the appointment of Shoaib Jameel, a Lecturer based at the Medway Campus. As well as teaching on the Computing programmes, Shoaib will be an active member of the Data Science Group, continuing his research in probabilistic topic models, Bayesian nonparametric statistics, vector space embeddings, natural language processing, optimization, and information retrieval.
Shoaib Jameel gained his Bachelor’s degree in Computer Science and Engineering in India, then completed his PhD programme in the Department of Systems Engineering and Engineering Management at the Chinese University of Hong Kong in 2014.
After his PhD, he worked at Cardiff University as a postdoctoral researcher on vector space embeddings for flexible reasoning with structured knowledge. Shoaib has collaborated with researchers from both industry and academia, for example, Microsoft Research, Carnegie Mellon University, NTT Communications (Japan), Noah’s Ark Labs (Hong Kong) and the Institute of Infocomm (Singapore). Shoaib has consistently published in several highly selective conferences and journals, such as SIGIR, TOIS, CIKM, ECAI and AAAI. He has also served as a programme committee member for several top-tier conferences and has reviewed for leading journals. His works have been funded by the Hong Kong Government and Microsoft Research Asia.
He said; “I am really excited to start a new role in the University of Kent. The staff at Medway are so friendly and I enjoy working with them. I want to make notable contributions in both teaching and research at Kent. I am passionate about information retrieval and web search. Web search is always challenging due to the huge amounts of data that is available online. Indexing and searching for relevant information on such massive collections of data is a serious task. The aim of my research is to propose novel scalable computational models for retrieval and relevance ranking. My vision is to see web search engines robust enough to handle spamming and bias against a particular person or community. I also aim to incorporate social network data into retrieval ranking problems.”