Università della Svizzera italiana (USI), Lugano, Switzerland
Mohammad's research activity is about Mobile Information Retrieval. His main emphasis is on combination of different relevance criteria for mobile IR. Some of the relevance criteria are topical, temporal, geographical, etc. Prior to that, he has worked on Contextual Suggestion and Spoken Language Understanding.
School of Communication and Information, Rutgers University, USA
Souvick is interested in Conversational Information Retrieval, which includes but is not limited to searchbots and spoken dialogue systems. He is attempting to use deep learning and NLP techniques to create better models capable of context-aware responses while interacting with humans in information seeking platforms. He is also interested in Searching as Learning, and Social Informatics.
Maram's early research focused on IR tasks over tweets including timeline generation, question answering and real-time summarization. She also worked on the problem of predicting retrieval performance of a query over tweets. Currently, Maram's research interest shifted further towards problems related to IR evaluation with specific focus on the problem of automatic IR system evaluation.
L3S Research Center at Leibniz University Hannover, Germany
Jaspreet's research is geared primarily towards retrieval models along with a healthy dose of Data Mining and Applied Machine Learning. He studies users’ search behavior allowing him to create models and develop better search systems. Jaspreet has been fortunate to work with great researchers on new ranking algorithms, search user interfaces and evaluation metrics. He has a long-standing interest in exploratory search, neural retrieval models and interpretability of complex retrieval models.
Johanne's area of research is search engine result presentation over a audio-only communication channel without overwhelming the user with information. She is also interested in how conversations can be structured between the user and the Spoken Conversation Search System. Her focus is on the experimental design with multi method analysis as evaluation.
Xiaohui's major research interests are Multimedia search and User behavior analysis. He is willing to share ideas with others and has the ambition to cooperate with other researchers to promote the development of information retrieval together.
Assistant Professor at University of New Hampshire, Durham, NH, USA
Laura's research is on how to best utilize knowledge graphs for text-centric information retrieval. As an example for such work, she is organizing the TREC Complex Answer Retrieval track.
Jiaxin's research focuses on user behavior analysis and evaluation for web search engines. He is interested in building user models to infer users' intents, experiences, and satisfaction from their interactions with the search engine.
Hamed is focusing on modeling the core IR problems, e.g., query representation, document representation, and ranking, using (deep) neural networks. He is also interested in theoretical approaches to IR tasks.