Abstract: 

With the introduction of new types of devices in our everyday lives (e.g. smart phones, smart watches, smart glasses, etc.), the interfaces over which information retrieval and natural language processing systems are used are becoming increasingly smaller, which limits the interactions users may have. Searching over devices with such small interfaces is not easy as it requires more effort to type and interact with such systems. Hence, building IR systems that can reduce the interactions needed with the device, while providing correct and unbiased information is highly critical.

Several research challenges in the field of natural language processing and information retrieval fields need to be tackled while designing the next generation information retrieval and access systems. In the first part of this talk, I will focus on the problems that need to be solved in designing such systems that can reduce the user effort needed, as well as the progress that we have made in these areas. In the second part of the talk, I will emphasize the importance of detecting online misinformation and bias and describe some of the work we have done to tackle these issues.

Bio: 

Emine Yilmaz is a Professor and Turing Fellow at University College London, Department of Computer Science. She also works as an Amazon Scholar for Amazon.

Her research interests lie in the areas of information retrieval, natural language processing and applications of machine learning, probability and statistics. She is a recipient of the Early Career Fellowship from the Engineering and Physical Sciences Research Council (EPSRC). To date, she has received approximately £1.5 million of external funding from funding agencies including European Union, EPSRC, Google, Elsevier and Bloomberg. She has served in various senior roles, including co-editor-in-chief for the Information Retrieval Journal, a member of the editorial board for the AI Journal and an elected member of the executive committee for ACM SIGIR.

Prof Yilmaz was the recipient of the Karen Sparck Jones 2015 Award for her contributions to information retrieval research. She is also one of the recipients of the Google Faculty Research Award in 2015 and the Bloomberg Data Science Research Award in 2018.