Tirtharaj Dash

About

I am an Assistant Professor in the Department of Computer Science at BITS Pilani, Goa Campus. My broad areas of interest include Neurosymbolic AI, Deep Learning, and AI for Science. For more details, please visit my homepage.

Employment

• BITS Pilani, Goa Campus Assistant Professor, Grade-I
  2025 - Present
• University of Cambridge Postdoctoral Research Associate
  2023 - 2025
• University of California, San Diego Postdoctoral Scholar
  2022 - 2023
• BITS Pilani, Goa Campus Assistant Professor, Grade-II
  2015 - 2022
• National Institute of Science and Technology Assistant Professor
  2014 - 2015

Education

• Birla Institute of Technology & Science Pilani Doctor of Philosophy (Ph.D.)
  2017 - 2022
• Veer Surendra Sai University of Technology Master of Technology
  2012 - 2014
• National Institute of Science and Technology Bachelor of Technology
  2008 - 2012

Projects & Funding

Projects & funding information is unavailable.

Publications (39)

• Identifying a logical specification and a program for an LLM-based generator of lead molecules
  2025 DOI: 10.1101/2025.02.14.634875
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• A comprehensive multi-omics study reveals potential prognostic and diagnostic biomarkers for colorectal cancer
  International Journal of Biological Macromolecules 2025 DOI: 10.1016/j.ijbiomac.2025.140443
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• Predicting gene expression using millions of yeast promoters reveals cis-regulatory logic
  2025 DOI: 10.1101/2025.01.25.634853
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• Predicting gene expression using millions of yeast promoters reveals cis-regulatory logic
  Bioinformatics Advances 2024 DOI: 10.1093/bioadv/vbaf130
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• Generating Novel Leads for Drug Discovery using LLMs with Logical Feedback
  2023 DOI: 10.1101/2023.09.14.557698
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• Investigating tumor-associated macrophages and their polarization in colorectal cancer using Boolean implication networks
  2023 DOI: 10.1101/2023.08.01.551559
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• Inclusion of domain-knowledge into GNNs using mode-directed inverse entailment
  Machine Learning 2022 DOI: 10.1007/s10994-021-06090-8
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• Transformational machine learning: Learning how to learn from many related scientific problems
  Proceedings of the National Academy of Sciences 2021 DOI: 10.1073/pnas.2108013118
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• Performance evaluation of deep neural networks for forecasting time‐series with multiple structural breaks and high volatility
  CAAI Transactions on Intelligence Technology 2021 DOI: 10.1049/cit2.12002
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• Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design
  2021 DOI: 10.1101/2021.07.09.451519
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