Dr Tirtharaj Dash

Tirtharaj will join us in October 2023 to develop artificial intelligence and deep learning methods for omics data. Despite the vast amounts of omics data that have been collected and made available in public databases, the underlying molecular mechanisms often remain poorly understood. Models built on vast amounts of data may generalise beyond these individual experiments, allowing us to advance our understanding of fundamental biological concepts.

Biography

Tirtharaj Dash is a Research Associate in the SBLab, CRUK Cambridge Institute, University of Cambridge, UK. Before joining the SBLab, Tirtharaj worked as a Postdoctoral Scholar at the Department of Pediatrics and CSE, University of California, San Diego, for a year starting October 2022. His research areas of interest are Deep Learning, Neuro-Symbolic AI, Graph Representation Learning, Machine Learning and Computational Biology. He completed his PhD in Computer Science at BITS Pilani, India, in 2022. He has won the Institute’s Best PhD Thesis Award for the year 2022 for his thesis entitled “Inclusion of Symbolic Domain-Knowledge into Deep Neural Networks”. He holds an MTech degree in Computer Science and a BTech degree in Information Technology. He is a Silver Medalist for his academic performance during his master's and bachelor's studies. Tirtharaj has published his research findings in journals and conferences of international repute, such as Scientific Reports, PNAS, Machine Learning Journal, AAAI, WACV, ILP, etc., some of which have owned the Best Paper awards at the conferences. He is a regular reviewer for major publication venues such as various IEEE and ACM Transactions, and an academic editor of PLOS One. He regularly serves as a PC member for international conferences such as IJCAI, ECAI, AAAI, DASFAA, and IJCNN. He is a regular member of the ACM.

Homepage: https://tirtharajdash.github.io/

Research positions

Research Associate (Oct 2023 - now)
Cancer Research UK Cambridge Institute, University of Cambridge, UK

Postdoctoral Scholar (Oct 2022 - Sep 2023)
Department of Pediatrics and CSE, University of California, San Diego, USA

Qualifications

• PhD in Computer Science, Birla Institute of Technology and Science, Pilani, India, Jul 2022
• M.Tech in Computer Science and Engineering, Veer Surendra Sai University of Technology, Burla, India, Jun 2014
• B.Tech in Information Technology, National Institute of Science and Technology, Berhampur, India, Jul 2012

Honours and awards (selected)

• Best PhD Thesis Award from BITS Pilani, India, 2023
• Best Short Paper Award from the ACM in ACMSE conference, 2022
• ICML 2021 Workshop on Computational Biology Fellowship, 2021
• AWSAR Award 2019 from DST, Govt. of India, 2020
• Best Student Research Paper Award from the Machine Learning Journal in ILP, 2018

Professional activities (selected)

• Academic editor: PLOS One
• Reviewer: IEEE TIE, IEEE CYB, NEPL
• Programme committee member: IJCAI, ECAI, AAAI, IJCNN, ILP

Key publications

• Srinivasan A, Baskar A, Dash T, Shah D, Composition of relational features with an application to explaining black-box predictors, Machine Learning, 2023. [URL]
• Dash T, Chitlangia S, Ahuja A, Srinivasan A, A review of some techniques for inclusion of domain-knowledge into deep neural networks, Scientific Reports, 2022. [URL]
• Dash T, Srinivasan A, Baskar A, Inclusion of domain-knowledge into GNNs using mode-directed inverse entailment, Machine Learning, 2022. [URL]
• Olier I, Orhobor OI, Dash T, Davis A, Soldatova LN, Vanschoren J, King RD, Transformational machine learning: Learning how to learn from many related scientific problems, Proceedings of the National Academy of Sciences, 2021. [URL]
• Dash T, Srinivasan A, Vig L, Incorporating symbolic domain knowledge into graph neural networks, Machine Learning, 2021. [URL]