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プロフィール詳細
プロジェクトを作成
★★★★★
☆☆☆☆☆
Tirtharaj D.に依頼
India

AI for Science Expert | Deep Learning, Neurosymbolic AI, Computational Biology & Drug Discovery.

プロフィール概要
専門分野
サービス
Data & AI Predictive Modeling, Statistical Analysis, Algorithm Design-Non ML, Algorithm Design-ML, Data Visualization, Big Data Analytics, Text Mining & Analytics, Data Mining, Data Cleaning, Data Processing, Data Insights
職務経験

Assistant Professor, Grade-I

BITS Pilani, Goa Campus

12月 2025 - 現在

Postdoctoral Research Associate

University of Cambridge

10月 2023 - 12月 2025

Postdoctoral Scholar

University of California, San Diego

10月 2022 - 9月 2023

Assistant Professor, Grade-II

BITS Pilani, Goa Campus

8月 2015 - 8月 2022

Assistant Professor

National Institute of Science and Technology

6月 2014 - 8月 2015

学歴

Doctor of Philosophy (Ph.D.) (Computer Science)

Birla Institute of Technology & Science Pilani

1月 2017 - 7月 2022

Master of Technology (Computer Science and Engineering)

Veer Surendra Sai University of Technology

8月 2012 - 6月 2014

Bachelor of Technology (Information Technology)

National Institute of Science and Technology

8月 2008 - 8月 2012

認定資格

  • IBM Certified Database Administrator - DB2 11 DBA for z/OS

    IBM

    7月 2009 - 現在

出版物
JOURNAL ARTICLE
Tirtharaj Dash, Mohita Mahajan, Subodh Dhabalia, Angshuman Sarkar, Sukanta Mondal (2025). A comprehensive multi-omics study reveals potential prognostic and diagnostic biomarkers for colorectal cancer . International Journal of Biological Macromolecules.
Tirtharaj Dash, Susanne Bornelöv, Thomas Lengauer (2024). Predicting gene expression using millions of yeast promoters reveals cis-regulatory logic . Bioinformatics Advances.
Inclusion of domain-knowledge into GNNs using mode-directed inverse entailment <head> <META HTTP-EQUIV="Refresh" CONTENT="0;URL=/servlet/useragent"> </head> . Machine Learning.
Tirtharaj Dash, Ivan Olier, Oghenejokpeme I. Orhobor, Andy M. Davis, Larisa N. Soldatova, Joaquin Vanschoren, Ross D. King(2021). Transformational machine learning: Learning how to learn from many related scientific problems . Proceedings of the National Academy of Sciences. 118. (49). Proceedings of the National Academy of Sciences
Performance evaluation of deep neural networks for forecasting time‐series with multiple structural breaks and high volatility <head> <META HTTP-EQUIV="Refresh" CONTENT="0;URL=/servlet/useragent"> </head> . CAAI Transactions on Intelligence Technology.
Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig (2021). Incorporating symbolic domain knowledge into graph neural networks . Machine Learning.
Tirtharaj Dash, Rakesh Ranjan Swain, Pabitra Mohan Khilar(2020). Lightweight approach to automated fault diagnosis in WSNs . IET Networks. 9. (3). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 110--119. Institution of Engineering and Technology ({IET})
Tirtharaj Dash, Sahith N. Dambekodi, Preetham N. Reddy, Ajith Abraham(2020). Adversarial neural networks for playing hide-and-search board game Scotland Yard . Neural Computing and Applications. 32. (8). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 3149--3164. Springer Science and Business Media {LLC}
Tirtharaj Dash, Rakesh Ranjan Swain, Pabitra Mohan Khilar(2020). Multifault diagnosis in WSN using a hybrid metaheuristic trained neural network . Digital Communications and Networks. 6. (1). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 86--100. Elsevier {BV}
Tirtharaj Dash, Rakesh Ranjan Swain, Pabitra Mohan Khilar(2019). A complete diagnosis of faulty sensor modules in a wireless sensor network . Ad Hoc Networks. 93. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 101924. Elsevier {BV}
Tirtharaj Dash, Rakesh Ranjan Swain, Pabitra Mohan Khilar(2019). Neural network based automated detection of link failures in wireless sensor networks and extension to a study on the detection of disjoint nodes . Journal of Ambient Intelligence and Humanized Computing. 10. (2). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 593--610. Springer Nature
Tirtharaj Dash, Himansu Sekhar Behera (2019). A comprehensive study on evolutionary algorithm‐based multilayer perceptron for real‐world data classification under uncertainty . Expert Systems.
Tirtharaj Dash, Rakesh Ranjan Swain, Pabitra Mohan Khilar(2018). Fault diagnosis and its prediction in wireless sensor networks using regressional learning to achieve fault tolerance . International Journal of Communication Systems. 31. (14). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString e3769. Wiley
Swain, R.R., Khilar, P.M., Dash, T.(2018). Multifault diagnosis in WSN using a hybrid metaheuristic trained neural network . Digital Communications and Networks.
Dash, T., Dambekodi, S.N., Reddy, P.N., Abraham, A.(2018). Adversarial neural networks for playing hide-and-search board game Scotland Yard . Neural Computing and Applications.
Tirtharaj Dash, Rakesh Ranjan Swain, Pabitra Mohan Khilar (2017). An effective graph‐theoretic approach towards simultaneous detection of fault(s) and cut(s) in wireless sensor networks . International Journal of Communication Systems.
Dash, T.(2017). A study on intrusion detection using neural networks trained with evolutionary algorithms . Soft Computing. 21. (10). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 2687-2700.
Pai, P.P., Dash, T., Mondal, S.(2017). Sequence-based discrimination of protein-RNA interacting residues using a probabilistic approach . Journal of Theoretical Biology. 418. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 77-83.
Dash, T.(2015). Automatic navigation of wall following mobile robot using Adaptive Resonance Theory of Type-1 . Biologically Inspired Cognitive Architectures. 12. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 1-8.
Dash, T., Sahu, P.K.(2015). Gradient gravitational search: An efficient metaheuristic algorithm for global optimization . Journal of Computational Chemistry. 36. (14). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 1060-1068.
Dash, Tirtharaj, Tanistha Nayak, Subhagata Chattopadhyay, and Fethi A. Rabhi. "A Fingerprint Verification Tool Using Adaptive Resonance Theory Nets." American Journal of Biomedical Engineering 3, no. 2 (2013): 31-40 .
Dash, Tirtharaj(2013). Time efficient approach to offline hand written character recognition using associative memory net. arXiv preprint arXiv:1306.4592.
PREPRINT
Tirtharaj Dash, Ashwin Srinivasan, A Baskar, Sanjay Kumar Dey, Mainak Banerjee (2025). Identifying a logical specification and a program for an LLM-based generator of lead molecules .
Tirtharaj Dash, Susanne Bornel&#246;v (2025). Predicting gene expression using millions of yeast promoters reveals cis-regulatory logic .
Tirtharaj Dash, Shreyas Bhat Brahmavar, Ashwin Srinivasan, Sowmya R Krishnan, Lovekesh Vig, Arijit Roy, Raviprasad Aduri (2023). Generating Novel Leads for Drug Discovery using LLMs with Logical Feedback .
Tirtharaj Dash, Ekta Dadlani, Debashis Sahoo (2023). Investigating tumor-associated macrophages and their polarization in colorectal cancer using Boolean implication networks .
OTHER
Tirtharaj Dash, Ashwin Srinivasan, Lovekesh Vig, Arijit Roy(2021). Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design . Cold Spring Harbor Laboratory
Tirtharaj Dash, Soundarya Krishnan, Rishab Khincha, Lovekesh Vig, Ashwin Srinivasan(2020). A Case Study of Transfer of Lesion-Knowledge . Cold Spring Harbor Laboratory
BOOK CHAPTER
Tirtharaj Dash, Ashwin Srinivasan, Ramprasad S. Joshi, A. Baskar (2019). Discrete Stochastic Search and Its Application to Feature-Selection for Deep Relational Machines .
Iyer, S., Chaturvedi, S., Dash, T.(2019). Image captioning-based image search engine: An alternative to retrieval by metadata . Advances in Intelligent Systems and Computing. 817. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 181-191.
BOOK
Saladi, P.S.M., Dash, T.(2019). Genetic algorithm-based oversampling technique to learn from imbalanced data . Advances in Intelligent Systems and Computing. 816. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 387-397.
Swain, R.R., Dash, T., Khilar, P.M.(2019). Investigation of RBF Kernelized ANFIS for Fault Diagnosis in Wireless Sensor Networks . Advances in Intelligent Systems and Computing. 799. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 253-264.
Dash, T., Srinivasan, A., Vig, L., Orhobor, O.I., King, R.D.(2018). Large-Scale Assessment of Deep Relational Machines . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11105 LNAI. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 22-37.
Saboo, A., Sharma, A., Dash, T.(2017). GASOM: Genetic algorithm assisted architecture learning in self organizing maps . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10634 LNCS. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 230-239.
Dash, T., Nayak, S.K., Behera, H.S.(2015). Hybrid gravitational search and particle swarm based fuzzy MLP for medical data classification . Smart Innovation, Systems and Technologies. 31. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 35-43.
Mohanty, R., Dash, T., Khan, B., Dash, S.P.(2014). An experimental study of a novel move-to-front-or-middle (MFM) list update algorithm . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8321. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 187-197.
CONFERENCE PAPER
Reddy, P.N., Dambekodi, S.N., Dash, T.(2017). Towards continuous monitoring of environment under uncertainty: A fuzzy granular decision tree approach . CEUR Workshop Proceedings. 1819.
Nayak, T., Dash, T., Rao, D.C., Sahu, P.K.(2016). Evolutionary neural networks versus adaptive resonance theory net for breast cancer diagnosis . ACM International Conference Proceeding Series. 25-26-August-2016.
Dash, T., Nayak, T., Swain, R.R.(2015). Controlling wall following robot navigation based on gravitational search and feed forward neural network . ACM International Conference Proceeding Series. 26-27-February-2015. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 196-200.
Dash, T., Soumya, R.S., Nayak, T., Mishra, G.(2015). Neural network approach to control wall-following robot navigation . Proceedings of 2014 IEEE International Conference on Advanced Communication, Control and Computing Technologies, ICACCCT 2014. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 1072-1076.
Nayak, J., Sahoo, N., Swain, J.R., Dash, T., Behera, H.S.(2014). GA based polynomial neural network for data classification . Proceedings - 2014 13th International Conference on Information Technology, ICIT 2014. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 234-239.