Avishek Anand is an Associate Professor in the Web Information Systems (WIS) at the Software Technology department at Delft University of Technology (TU Delft). His research aims to develop intelligent and transparent machine learning approaches to help humans find relevant information. Specifically, he is interested in Explainable Information Retrieval. He holds a PhD in computer science from the Max Planck Insitute for Informatics, Saarbrücken. Previously, he was an Assistant professor in Information Retrieval in Lebniz University Hannover. His research is supported by Amazon research awards, Schufa Gmbh, BMBF, and EU Horizon 2020. He is also a member of the L3S Research Center and a visiting scholar in Amazon Search.
PhD in Information Retrieval, 2013
MPI Informatik & Saarland University
MSc in Computer Science, 2009
Saarland University
BTech in Computer Science, 2005
Indian Institute for Information Technology
Predictive models are all pervasive with usage in search engines, recommender systems, health, legal and financial domains. But for the most part they are used as black boxes which output a prediction, score or rankings without understanding partially or even completely how different features influence the model prediction.
Machine learning models are progressively becoming complex and training datasets are getting larger by the data. Embeddings models are trained over Web scale collections of text and graphs, language models are learnt over millions or billions of sentences.
My main focus in information retrieval is currently investigating neural models for ranking models for document retrieval and open-domain question answering. I also work extensively on temporal information retrieval and enrichment of textual knowledge sources like Wikipedia.