Personal information

United States

Biography

Arghya is a highly experienced researcher in the field of machine learning, artificial intelligence, and its applications in complex domains. With 7+ years of research experience, he is a fast learner and problem solver, always in pursuit of novel solutions using advanced skills in machine learning and AI. He is well-versed in state-of-the-art machine learning, deep learning, probabilistic modeling, data processing, analytics, and statistics. Arghya has published research papers in reputed journals and conferences in the field of machine learning, healthcare informatics, and toxicology.

His strong communication skills and leadership abilities have resulted in successful collaborations with clinicians and epidemiologists at leading medical institutions, such as WUSTL Med School, and hospitals, such as BJC Healthcare network, USVA.

Arghya's areas of expertise include knowledge discovery, predictive modeling using classical methods and deep learning, natural language processing, graph convolution use cases, recommender systems, insight generation, causal modeling, representation learning, fundamental deep learning research, and A/B testing. Currently, he works on large language models and its robustness and evaluation at Amazon Alexa AI.

Activities

Employment (3)

Amazon Inc.: Seattle, WA, US

ML/AI Research Scientist
Employment
Source: Self-asserted source
Arghya Datta

Washington University in St Louis: St Louis, MO, US

2016-08-15 to 2021-08-19 | Graduate Research Assistant (Computer science and Engineering)
Employment
Source: Self-asserted source
Arghya Datta

Infosys Ltd: Bangalore, Karnataka, IN

2015-05-11 to 2016-03-12 | System Test Engineer
Employment
Source: Self-asserted source
Arghya Datta

Education and qualifications (3)

Washington University in St Louis: St Louis, MO, US

PhD (Computer Science and Engineering)
Education
Source: Self-asserted source
Arghya Datta

Washington University in St Louis: St Louis, MO, US

MS in Computer Science (Computer Science and Engineering)
Qualification
Source: Self-asserted source
Arghya Datta

West Bengal State University: Kolkata, West Bengal, IN

2011-07-11 to 2015-07-10 | Bachelors of Technology (Electronics and telecommunications)
Education
Source: Self-asserted source
Arghya Datta

Professional activities (2)

Washington University in St Louis: St Louis, MO, US

2016-08-14 | Full tuition and stipend sponsorship via University grant (Computer Science and Engineering)
Distinction
Source: Self-asserted source
Arghya Datta

Veterans hospital, Saint Louis: Saint louis, MO, US

2015-08-10 to 2016-07-12 | Research Scholar (without compensation)
Invited position
Source: Self-asserted source
Arghya Datta

Works (8)

Measuring and Mitigating Local Instability in Deep Neural Networks

Findings of ACL 2023
2023 | Conference paper
Contributors: Arghya Datta; Subhrangshu Nandi; Jingcheng Xu; Greg Ver Steeg; He Xie; Anoop Kumar; Aram Galstyan
Source: Self-asserted source
Arghya Datta

Machine Learning in Complex Scientific Domains: Hospitalization Records, Drug Interactions, Predictive Modeling and Fairness for Class Imbalanced Data

2021 | Dissertation or Thesis
Source: Self-asserted source
Arghya Datta

Cal-Net: Jointly Learning Classification and Calibration On Imbalanced Binary Classification Tasks

2021 International Joint Conference on Neural Networks (IJCNN)
2021-07-18 | Conference paper
Source: Self-asserted source
Arghya Datta

Machine learning liver-injuring drug interactions with non-steroidal anti-inflammatory drugs (NSAIDs) from a retrospective electronic health record (EHR) cohort

PLOS Computational Biology
2021-07-06 | Journal article
Contributors: Arghya Datta; Andrey Rzhetsky; Noah R. Flynn; Dustyn A. Barnette; Keith F. Woeltje; Grover P. Miller; S. Joshua Swamidass
Source: check_circle
Crossref

'Black Box' to 'Conversational' Machine Learning: Ondansetron Reduces Risk of Hospital-Acquired Venous Thromboembolism.

IEEE journal of biomedical and health informatics
2021-06 | Journal article
Contributors: Datta A; Matlock MK; Le Dang N; Moulin T; Woeltje KF; Yanik EL; Joshua Swamidass S
Source: Self-asserted source
Arghya Datta via Europe PubMed Central
grade
Preferred source (of 2)‎

Fair-Net: A Network Architecture For Reducing Performance Disparity Between Identifiable Sub-Populations

2021-06-01 | Preprint
Source: Self-asserted source
Arghya Datta

Meloxicam methyl group determines enzyme specificity for thiazole bioactivation compared to sudoxicam

Toxicology Letters
2020-11-27 | Journal article
Source: Self-asserted source
Arghya Datta

Deep learning long-range information in undirected graphs with wave networks

2019 International Joint Conference on Neural Networks (IJCNN)
Journal article
Source: Self-asserted source
Arghya Datta

Peer review (30 reviews for 8 publications/grants)

Review activity for Applied sciences. (7)
Review activity for BioMedInformatics. (4)
Review activity for Diagnostics. (1)
Review activity for Electronics. (7)
Review activity for Healthcare. (3)
Review activity for International journal of environmental research and public health (1)
Review activity for Mathematics. (4)
Review activity for Sensors. (3)