MACHINE LEARNING GROUP

TECHNISCHE UNIVERSITÄT KAISERSLAUTERN

Sourav Dutta

PhD Student

Bio

Sourav Dutta is a PhD candidate at the Machine Learning Group (since 2021) under the supervision of Jun.-Prof. Dr. Sophie Burkhardt at TU Kaiserslautern, Germany. He holds a Master's degree (Language Science and Technology) from Saarland University and a Bachelor's degree (Computer Science) from UIT, India. During his Master's studies, he was a research assistant at DFKI and at Saarland University where he worked on active learning and translationese classification respectively. He has also worked as a software engineer in TCS and SAP Labs.

Research interests

Sourav's main interest lies in leveraging machine learning techniques to solve complex problems in science, mainly chemical processes and natural language processing. He is specifically interested in methods involving optimal transport, normalization flows, and low-resource machine learning.

Appointments and scientific matters
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Curriculum Vitae

Education

2018-2021
Master of Science in Language Science and Technology, Saarland University, Germany
2010-2014
Bachelor of Engineering in Computer Science, UIT, India

Professional Experience

since 2021
PhD candidate - Researcher, TU Kaiserslautern, Kaiserslautern, Germany
2020-2021
Intern, Machine Translation Team, Electronic Arts (EA), Köln, Germany
2019-2020
Research Assistant, MLT group, Saarland University, Saarbrücken, Germany
2018-2020
Research Assistant, IML group, DFKI, Saarbrücken, Germany
2015-2018
Software Engineer, SAP Labs, Bangalore, India
2014-2015
Software Engineer, Tata Consultancy Services, Chennai, India

Activities and honors

2021
EACL Demo Track - Program Committee member

Key publications

  • S. Dutta*, J. Alabi*, S. Bandyopadhyay, D. Ruiter, and J. van Genabith. Unsupervised MT and Very Low Resource Supervised MT for German-Upper Sorbian.
    Proceedings of the Conference on Machine Translation, 5: 1092-1098, 2020.
  • A.G. Reddy, T. Boulton, A.N. Ullas, R. Ray, and S. Dutta. Application-independent transformation and progressive rendering of queries for constrained user input devices and data model enabling same.
    U.S. Patent 10,565,243, 2020.
(* denotes equal contribution)