Aankit Das

About

Aankit Das is a Machine Learning Researcher and Engineer working at the intersection of scientific computing and AI systems. His work focuses on developing foundation models for time-series and multimodal data, as well as applying machine learning to cosmology, including CMB map cleaning and power spectrum estimation. Previously, he was a Data Scientist at SEI Investments Company, applying ML techniques to large-scale financial data. His interests span deep learning, optimization, representation learning, and scientific machine learning, with an emphasis on rapid prototyping, experimental design, and model interpretability.

Employment

• The University of Texas at Dallas Machine Learning Researcher
  2025 - Present
• SEI (United States) Data Scientist
  2021 - Present
• University of Calcutta Researcher
  2020 - 2021

Education

• The University of Texas at Dallas Masters
  2023 - 2025
• University of Calcutta Bachelor of Technology
  2016 - 2020

Projects & Funding

Projects & funding information is unavailable.

Publications (4)

• FlowerPhenoNet: Automated Flower Detection from Multi-View Image Sequences Using Deep Neural Networks for Temporal Plant Phenotyping Analysis
  Remote Sensing 2022 DOI: 10.3390/rs14246252
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• A Hybrid Meta-Heuristic Feature Selection Method for Identification of Indian Spoken Languages From Audio Signals
  IEEE Access 2020 DOI: 10.1109/ACCESS.2020.3028241
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• Hybrid Feature Selection Method Based on Harmony Search and Naked Mole-Rat Algorithms for Spoken Language Identification From Audio Signals
  IEEE Access 2020 DOI: 10.1109/ACCESS.2020.3028121
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• FlowerPhenoNet: Automated Flower Detection from Multi-view Image Sequences using Deep Neural Networks for Temporal Plant Phenotyping Analysis
  DOI: 10.20944/preprints202210.0477.v1
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