Hello There

I am Shounak Datta.
I am a Machine Learning Researcher

with Amazon.

Shounak Datta

Research Areas Publications
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About

More About Me

I am currently an Applied ML Scientist with Amazon. I hold a Ph.D. in Computer Science from the Indian Statistical Institute, Kolkata, India, an M.E. in Electronics and Telecommunication Engineering from the Jadavpur University, Kolkata, India, and a B.Tech. in Electronics and Communication Engineering from the West Bengal University of Technology, Kolkata, India. Prior to Arm, I was a Postdoctoral Associate with the Electrical and Computer Engineering Dept. of Duke University.



I have been working on machine learning, data mining and stochastic optimization for over 10 years now. My current research interests include development of self-attention based chat agents for understanding and handling customer conversations at Amazon. I am also interested in class imbalance, few-shot learning, generative models, neural architecture search, multi-objective optimization, etc.

I have supervised 20+ undergraduate and postgraduate research interns (from various notable academic institutes in India and the United States) on projects leading to papers, technical reports and dissertations since 2013.

Research Interests

  • Deep Learning
  • Vision Transformer
  • Few-shot Learning
  • Class Imbalance
  • Missing Features
  • Support Vector Machines
  • k-Nearest Neighbors
  • Neural Architecture Search
  • Multi-objective Optimization
  • Data Clustering


16

Journal Articles

6

Conference Articles

4

Preprints/Drafts

5

Lectures

Publications

See My Latest Publications.

The following is a list of my research articles including 16 journal- and 6 peer-reviewed conference-papers. For more details visit my Google Scholar page.

Journal Articles

  • Shounak Datta, Eduardo B Mariottoni, David Dov, Alessandro A Jammal, Lawrence Carin, and Felipe A Medeiros. "RetiNerveNet: Using Recursive Deep Learning to Estimate Pointwise 24-2 Visual Field Data based on Retinal Structure." Scientific Reports (Nature) (2021): 1-10.
  • Shounak Datta, Sayak Nag, and Swagatam Das. "Boosting with Lexicographic Programming: Addressing Class Imbalance without Cost Tuning." IEEE Transactions on Knowledge and Data Engineering (2019): 1-14.
  • Shounak Datta, and Swagatam Das. "Multi-Objective Support Vector Machines: Handling Class Imbalance with Pareto Optimality." IEEE Transactions on Neural Networks and Learning Systems (2018).
  • Shounak Datta, and Swagatam Das. "Near-Bayesian Support Vector Machines for imbalanced data classification with equal or unequal misclassification costs." Neural Networks 70 (2015): 39-52.
  • Shounak Datta, Debaleena Misra, and Swagatam Das. "A feature weighted penalty based dissimilarity measure for k-nearest neighbor classification with missing features." Pattern Recognition Letters 80 (2016): 231-237.
  • Shounak Datta, Supritam Bhattacharjee, and Swagatam Das. "Clustering with missing features: a penalized dissimilarity measure based approach." Machine Learning (2018): 1-39.
  • Swagatam Das, Shounak Datta, and Bidyut B. Chaudhuri. "Handling data irregularities in classification: Foundations, trends, and future challenges." Pattern Recognition 81 (2018): 674-693.
  • Sankha Subhra Mullick, Shounak Datta, and Swagatam Das. "Adaptive Learning-Based k-Nearest Neighbor Classifiers With Resilience to Class Imbalance." IEEE Transactions on Neural Networks and Learning Systems (2018).
  • Sankha Subhra Mullick, Shounak Datta, Sourish Gunesh Dhekane, and Swagatam Das. "Appropriateness of Performance Indices for Imbalanced Data Classification: An Analysis." Pattern Recognition (2020).
  • Shounak Datta, Sankha Subhra Mullick, and Swagatam Das. "Generalized mean based back-propagation of errors for ambiguity resolution." Pattern Recognition Letters 94 (2017): 22-29.
  • Shounak Datta, Abhiroop Ghosh, Krishnendu Sanyal, and Swagatam Das. "A Radial Boundary Intersection aided interior point method for multi-objective optimization." Information Sciences 377 (2017): 1-16.
  • Avisek Gupta, Shounak Datta, and Swagatam Das. "Fast Automatic Estimation of the Number of Clusters from the Minimum Inter-Center Distance for Center-Based Clustering." Pattern Recognition Letters (2018).
  • Avisek Gupta, Shounak Datta, and Swagatam Das. "Fuzzy Clustering to Identify Clusters at Different Levels of Fuzziness: An Evolutionary Multi- Objective Optimization Approach." IEEE Transactions on Cybernetics (2019).
  • Eduardo Bicalho Mariottoni, Shounak Datta, David Dov, Alessandro Adad Jammal, Samuel Berchuck, Ivan Tavares, Lawrence Carin, and Felipe Medeiros. "A Deep Learning-Based Mapping of Structure to Function in Glaucoma." Investigative Ophthalmology & Visual Science (2020).
  • Eduardo Bicalho Mariottoni, Shounak Datta, David Dov, Alessandro Adad Jammal, Samuel Berchuck, Ivan Tavares, Lawrence Carin, and Felipe Medeiros. "Artificial Intelligence Mapping of Structure to Function in Glaucoma." Translational Vision Science & Technology (2020).
  • Anwesha Banerjee, Shounak Datta, Amit Konar, and D. N. Tibarewala. "Development strategy of eye movement controlled rehabilitation aid using Electro-oculogram." International Journal of Scientific and Engineering Research 3.6 (2012): 1-6.

Conference Articles

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Email

shounak(dot)jaduniv[at]gmail(dot)com