Avishek Anand

Avishek Anand

Assistant Professor of Information Retrieval

Leibniz Universität Hannover

Biography

Avishek Anand is an Assistant Professor in the Leibniz University of Hannover. His research aims to develop intelligent and transparent machine learning approaches to help humans find relevant information. His research broadly falls in the intersection of Machine learning on Web and information retrieval. Specifically, he is interested in scalable and interpretable representation learning methods for text and graphs. He holds a PhD in computer science from the Max Planck Insitute for Informatics, Saarbrücken. His research is supported by Amazon research awards and Schufa Gmbh. He has been a visiting scholar in Amazon Search.

Interests

  • Interpretability of learning systems
  • Information Retrieval
  • Representation learning for graphs
  • Scalable representation learning

Education

  • PhD in Information Retrieval, 2013

    Max Planck Insitute for Computer Science, Saarland University

  • MSc in Computer Science, 2009

    Saarland University

  • BTech in Computer Science, 2005

    Indian Institute for Information Technology

Projects

Interpretable Machine Learning

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.

Large Scale Machine Learning

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.

Information Retrieval

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.

Recent & Upcoming Talks

Question Answering over Curated and Open Web Sources

Question Answering over Curated and Open Web Sources

Question Answering over Curated and Open Web Sources

Recent Posts

Recent Publications

Boilerplate Removal using a Neural Sequence Labeling Model

Characterization and classification of semantic image-text relations

Conversational Search - A Report from Dagstuhl Seminar 19461

Model agnostic interpretability of rankers via intent modelling

Question Answering over Curated and Open Web Sources

Valid Explanations for Learning to Rank Models

Conversational Search (Dagstuhl Seminar 19461)

Experience

 
 
 
 
 

Assistant Professor

Leibniz Universität Hannover

Jul 2017 – Present Hannover
Information Retrieval and Machine Learning.
 
 
 
 
 

Post-doctoral researcher

L3S Research Center

Feb 2014 – Jul 2017 Hannover
 
 
 
 
 

Doctoral researcher

Max Planck Institut für Informatik

Feb 2009 – Jan 2014 Saarbrücken
 
 
 
 
 

Software Development Engineer

Microsoft India Research and Development Center

May 2005 – Mar 2007 Hyderabad

Contact

  • +49 0511 762 17795
  • Appelstraße 4, Hannover, Niedersachsen 30169
  • Enter Building and take the stairs to Floor 2. My office is the first one on the left.
  • Monday 10:00 to 13:00
    Wednesday 09:00 to 10:00
  • Book an appointment
  • DM Me