Work Experience

• Indian Institute of Technology, Hyderabad | Research Assistant Apr’20 – Present
  Lab 1055 | Guide: Prof. Vineeth N Balasubramanian
  • Working as a member of the Machine Learning & Vision group (Lab1055) broadly on building machine learning algorithms which are robust to domain shift under limited supervision settings.

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• Amazon Science, Hyderabad | Applied Scientist Intern Jan’22 – Jun'22
  Last Mile Team | Guides: Saket Maheshwary, Saurabh Sohoney
  • Worked in the Last Mile team at Amazon as an Applied Scientist on a project titled "Alleviating the Annotation Bottleneck by Learning from Multiple Sources of Weak Supervision"
  • My internship work was submitted to an internal machine learning conference.

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• Preferred Networks, Tokyo | Research Intern Jul’19 – Sept'19
  Sports Team | Guides: Alexis Vallet, Daichi Suzuo
  • Proposed a novel approach for player performance evaluation in football by incorporating the spatial context of all the players on the field.

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• International Institute of Information Technology, Hyderabad | Research Assistant Jul’18 – Jun’19
  CVIT | Guide: Prof. C. V. Jawahar
  
  • Worked on problems at the intersection of Computer Vision, Machine Learning & Sports Analytics.

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• Samsung Research, Bangalore | Summer Intern May’18 – Jul’18
  Vision Intelligence Group | Guides: Rabbani Patan, Gaurav Kumar Jain
  
  • Developed a novel approach for Scene Based Content Recommendation by borrowing ideas from Word2Vec.
  • Internship offered as a result of winning in the Bixby Hackathon conducted by Samsung Research, Bangalore at IIT (ISM) Dhanbad.

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• Indian Statistical Institute, Kolkata | Winter Intern Nov’17 – Dec’17
  Machine Intelligence Unit | Guide: Prof. Ashish Ghosh
  
  • Proposed a novel outlier detection framework using the projection principles of stacked auto-encoders and probabilistic neural networks.
  • Paper accepted in Pattern Recognition journal.

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• Samsung Research, Bangalore | Summer Intern May’17 – Jul’17
  Web Team | Guide: Amit Sarkar
  
  • Worked on an Abstractive Text Summarization scheme for generating link previews of websites for the Samsung Mobile Browser.
  • Formulated a model based on Attention Based Encoder-Decoder RNN for summarization and trained and tested it on the Insight BBC Dataset.