Publications in reversed chronological order. Selected preprints are included.


  1. BioSys@ASPLOS
    An AI-assisted Investigation of Tumor-Associated Macrophages and their Polarization in Colorectal Cancer
    Dadlani, Ekta,  Dash, Tirtharaj, and Sahoo, Debashis
    bioRxiv Apr 2024
  2. AAAI
    Generating Novel Leads for Drug Discovery Using LLMs with Logical Feedback
    Brahmavar, Shreyas Bhat, Srinivasan, AshwinDash, Tirtharaj, Krishnan, Sowmya Ramaswamy, Vig, Lovekesh, Roy, Arijit, and Aduri, Raviprasad
    Proceedings of the AAAI Conference on Artificial Intelligence Mar 2024


  1. MLJ
    Composition of relational features with an application to explaining black-box predictors
    Srinivasan, Ashwin, Baskar, A,  Dash, Tirtharaj, and Shah, Devanshu
    Machine Learning Mar 2023
  2. ICIP
    IKD+: Reliable Low Complexity Deep Models For Retinopathy Classification
    Brahmavar, Shreyas Bhat, Rajesh, Rohit,  Dash, TirtharajVig, Lovekesh, Verlekar, Tanmay Tulsidas, Hasan, Md Mahmudul, Khan, Tariq, Meijering, Erik, and Srinivasan, Ashwin
    30th IEEE International Conference on Image Processing (ICIP) Mar 2023
  3. OSF
    NCI Datasets (n=73) for BotGNNs
    Dash, Tirtharaj
    Open Science Framework May 2023
  4. EMBC
    Domain-Specific Pretraining Improves Confidence in Whole Slide Image Classification
    Chitnis, Soham Rohit, Liu, Sidong,  Dash, Tirtharaj, Verlekar, Tanmay Tulsidas, Di Ieva, Antonio, Berkovsky, Shlomo, Vig, Lovekesh, and Srinivasan, Ashwin
    45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) May 2023
  5. WPC
    AI-assisted Emergency Healthcare using Vehicular Network and Support Vector Machine
    Senapati, Biswa Ranjan, Khilar, Pabitra MohanDash, Tirtharaj, and Swain, Rakesh Ranjan
    Wireless Personal Communications May 2023
  6. WACV
    Calibrating Deep Neural Networks Using Explicit Regularisation and Dynamic Data Pruning
    Patra, Rishabh, Hebbalaguppe, RamyaDash, TirtharajShroff, Gautam, and Vig, Lovekesh
    In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Jan 2023


  1. NeSy@IJCLR
    Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces
    Shah, Vishwa, Sharma, Aditya, Shroff, GautamVig, LovekeshDash, Tirtharaj, and Srinivasan, Ashwin
    In 16th International Workshop on Neural-Symbolic Learning and Reasoning Sep 2022
  2. PhD Thesis
    Inclusion of Symbolic Domain-Knowledge into Deep Neural Networks
    Dash, Tirtharaj
  3. Pre-print
    Vehicular Network based Emergency Data Transmission and Classification for Health Care System using Support Vector Machine
    Senapati, Biswa Ranjan, Khilar, Pabitra MohanDash, Tirtharaj, and Swain, Rakesh Ranjan
    PREPRINT (Version 1) available at Research Square 2022
  4. WIRE
    Automated Fault Diagnosis in Wireless Sensor Networks: A Comprehensive Survey
    Swain, Rakesh Ranjan,  Dash, Tirtharaj, and Khilar, Pabitra Mohan
    Wireless Personal Communications 2022
  5. AAAI
    Solving Visual Analogies Using Neural Algorithmic Reasoning (Student Abstract)
    Sonwane, Atharv, Shroff, GautamVig, LovekeshSrinivasan, Ashwin, and Dash, Tirtharaj
    Proceedings of the AAAI Conference on Artificial Intelligence Jun 2022
  6. arXiv
    Machine Learning in Sports: A Case Study on Using Explainable Models for Predicting Outcomes of Volleyball Matches
    Lalwani, Abhinav, Saraiya, Aman, Singh, Apoorv, Jain, Aditya, and Dash, Tirtharaj
    arXiv 2022
  7. ACMSE
    Superpixel-Based Knowledge Infusion in Deep Neural Networks for Image Classification
    Chhablani, Gunjan, Sharma, Abheesht, Pandey, Harshit, and Dash, Tirtharaj
    In ACM SE ’22 Apr 2022
  8. SciRep
    A review of some techniques for inclusion of domain-knowledge into deep neural networks
    Dash, Tirtharaj, Chitlangia, Sharad, Ahuja, Aditya, and Srinivasan, Ashwin
    Scientific Reports Jan 2022
  9. ILP
    Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design
    Dash, TirtharajSrinivasan, AshwinVig, Lovekesh, and Roy, Arijit
    In Inductive Logic Programming Sep 2022


  1. PNAS
    Transformational machine learning: Learning how to learn from many related scientific problems
    Olier, Ivan, Orhobor, Oghenejokpeme I.,  Dash, Tirtharaj, Davis, Andy M., Soldatova, Larisa N., Vanschoren, Joaquin, and King, Ross D.
    Proceedings of the National Academy of Sciences 2021
    Using Program Synthesis and Inductive Logic Programming to solve Bongard Problems
    Sonwane, Atharv, Chitlangia, Sharad,  Dash, TirtharajVig, LovekeshShroff, Gautam, and Srinivasan, Ashwin
    In 10th International Workshop on Approaches and Applications of Inductive Programming (AAIP) 2021
  3. ICANN
    Empirical Study of Data-Free Iterative Knowledge Distillation
    Shah, Het, Vaswani, Ashwin,  Dash, Tirtharaj, Hebblaguppe, Ramya, and Srinivasan, Ashwin
    In Artificial Neural Networks and Machine Learning – ICANN 2021
  4. arXiv
    How to Tell Deep Neural Networks What We Know: A Review of Methods for Inclusion of Domain-Knowledge
    Dash, T., Chitlangia, S., Ahuja, A., and Srinivasan, A.
    arXiv 2021
  5. MLJ
    Inclusion of domain-knowledge into GNNs using mode-directed inverse entailment
    Dash, TirtharajSrinivasan, Ashwin, and Baskar, A.
    Machine Learning Nov 2021
  6. arXiv
    Incorporating domain knowledge into deep neural networks
    Dash, T., Chitlangia, S., Ahuja, A., and Srinivasan, A.
    arXiv 2021
  7. MLJ
    Incorporating symbolic domain knowledge into graph neural networks
    Dash, T.Srinivasan, A., and Vig, L.
    Machine Learning Jul 2021
  8. SemEval
    LRG at SemEval-2021 Task 4: Improving Reading Comprehension with Abstract Words using Augmentation, Linguistic Features and Voting
    Sharma, A., Pandey, H., Chhablani, G., Bhartia, Y., and Dash, T.
    In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021) Aug 2021
  9. CIT
    Performance evaluation of deep neural networks for forecasting time-series with multiple structural breaks and high volatility
    Kaushik, Rohit, Jain, Shikhar, Jain, Siddhant, and Dash, T.
    CAAI Transactions on Intelligence Technology 2021


  1. arXiv
    Constructing and evaluating an explainable model for COVID-19 diagnosis from chest X-rays
    Khincha, R., Krishnan, S.,  Dash, T.Vig, L., and Srinivasan, A.
    arXiv 2020
    CovidDiagnosis: Deep Diagnosis of COVID-19 Patients Using Chest X-Rays
    Mahajan, K., Sharma, M., Vig, L., Khincha, R., Krishnan, S., Niranjan, A.,  Dash, T.Srinivasan, A., and Shroff, G.
    In Thoracic Image Analysis 2020
    A Case Study of Transfer of Lesion-Knowledge
    Krishnan, S., Khincha, R., Vig, L.Dash, T., and Srinivasan, A.
    In Interpretable and Annotation-Efficient Learning for Medical Image Computing 2020
  4. ESANN
    An Empirical Study of Iterative Knowledge Distillation for Neural Network Compression
    Yalburgi, S.,  Dash, T.Hebbalaguppe, R., Hegde, S., and Srinivasan, A.
    In European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN’20) 2020
  5. IETNet
    Lightweight approach to automated fault diagnosis in WSNs
    Swain, R. R.,  Dash, T., and Khilar, P. M.
    IET Networks 2020


  1. AdHocNet
    A complete diagnosis of faulty sensor modules in a wireless sensor network
    Swain, R. R.,  Dash, T., and Khilar, P. M.
    Ad Hoc Networks 2019
  2. ExSy
    A comprehensive study on evolutionary algorithm-based multilayer perceptron for real-world data classification under uncertainty
    Dash, T., and Behera, H. S.
    Expert Systems 2019
  3. JAIHC
    Neural network based automated detection of link failures in wireless sensor networks and extension to a study on the detection of disjoint nodes
    Swain, R. R., Khilar, P. M., and Dash, T.
    J. Ambient Intell. Humaniz. Comput. 2019
  4. ICANN
    Discrete Stochastic Search and Its Application to Feature-Selection for Deep Relational Machines
    Dash, T.Srinivasan, A., Joshi, R. S., and Baskar, A.
    In Artificial Neural Networks and Machine Learning - ICANN 2019: Deep Learning - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings, Part II 2019
  5. ICCI
    Investigation of RBF Kernelized ANFIS for Fault Diagnosis in Wireless Sensor Networks
    Swain, R. R.,  Dash, T., and Khilar, P. M.
    In Computational Intelligence: Theories, Applications and Future Directions - Volume II 2019


  1. arXiv
    A study on the use of boundary equilibrium gan for approximate frontalization of unconstrained faces to aid in surveillance
    Zulfikar, W., Santy, S., Dambekodi, S., and Dash, T.
    arXiv 2018
  2. NCAA
    Adversarial neural networks for playing hide-and-search board game Scotland Yard
    Dash, T., Dambekodi, S. N., Reddy, P. N., and Abraham, A.
    Neural Computing and Applications 2018
  3. IJCS
    Fault diagnosis and its prediction in wireless sensor networks using regressional learning to achieve fault tolerance
    Swain, R. R., Khilar, P. M., and Dash, T.
    International Journal of Communication Systems 2018
  4. DCAN
    Multifault diagnosis in WSN using a hybrid metaheuristic trained neural network
    Swain, R. R., Khilar, P. M., and Dash, T.
    Digital Communications and Networks 2018
  5. Large-Scale Assessment of Deep Relational Machines
    Dash, T.Srinivasan, A.Vig, L., Orhobor, O.I., and King, R.D.
    In Inductive Logic Programming - 28th International Conference, ILP 2018, Ferrara, Italy, September 2-4, 2018, Proceedings Sep 2018


  1. JTB
    Sequence-based discrimination of protein-RNA interacting residues using a probabilistic approach
    Pai, P. P.,  Dash, T., and Mondal, S.
    Journal of Theoretical Biology 2017
  2. IJCS
    An effective graph-theoretic approach towards simultaneous detection of fault(s) and cut(s) in wireless sensor networks
    Swain, R. R.,  Dash, T., and Khilar, P. M.
    International Journal of Communication Systems 2017
  3. SOCO
    A study on intrusion detection using neural networks trained with evolutionary algorithms
    Dash, T.
    Soft Computing 2017
  4. SocProS
    Image Captioning-Based Image Search Engine: An Alternative to Retrieval by Metadata
    Iyer, S., Chaturvedi, S., and Dash, T.
    In Soft Computing for Problem Solving - SocProS 2017, Volume 2, Bhubaneswar, India, December 23-24, 2017 2017
  5. SocProS
    Genetic Algorithm-Based Oversampling Technique to Learn from Imbalanced Data
    Saladi, P. S. M., and Dash, T.
    In Soft Computing for Problem Solving - SocProS 2017, Volume 1, Bhubaneswar, India, December 23-24, 2017 2017
    GASOM: Genetic Algorithm Assisted Architecture Learning in Self Organizing Maps
    Saboo, A., Sharma, A., and Dash, T.
    In Neural Information Processing - 24th International Conference, ICONIP 2017, Guangzhou, China, November 14-18, 2017, Proceedings, Part I 2017
    Towards Continuous Monitoring of Environment under Uncertainty: A Fuzzy Granular Decision Tree Approach
    Reddy, P. N., Dambekodi, S. N., and Dash, T.
    In Joint Proceedings of the 3rd Modelling Symposium (ModSym), Developmental Aspects of Intelligent Adaptive Systems (DIAS), and Educational Data Mining Practices in Indian Academia (EDUDM) co-located with 10th Innovations in Software Engineering (ISEC 2017), Jaipur, India, February 5, 2017 2017


  1. ICIA
    Evolutionary Neural Networks versus Adaptive Resonance Theory Net for Breast Cancer Diagnosis
    Nayak, T.,  Dash, T., Rao, D. C., and Sahu, P. K.
    In Proceedings of the International Conference on Informatics and Analytics, ICIA 2016, Pondicherry, India, August 25-26, 2016 2016


  1. BICA
    Automatic navigation of wall following mobile robot using Adaptive Resonance Theory of Type-1
    Dash, T.
    Biologically Inspired Cognitive Architectures 2015
  2. JCC
    Gradient gravitational search: An efficient metaheuristic algorithm for global optimization
    Dash, T., and Sahu, P. K.
    J. Comput. Chem. 2015
  3. PerMIn
    Controlling Wall Following Robot Navigation Based on Gravitational Search and Feed Forward Neural Network
    Dash, T., Nayak, T., and Swain, R. R.
    In Proceedings of the 2nd International Conference on Perception and Machine Intelligence, Kolkata, West Bengal, India, February 26-27, 2015 2015
    Hybrid Gravitational Search and Particle Swarm Based Fuzzy MLP for Medical Data Classification
    Dash, T., Nayak, S. Kumar, and Behera, H. S.
    In Computational Intelligence in Data Mining - Volume 1 2015


  1. ICIT
    GA Based Polynomial Neural Network for Data Classification
    Nayak, J., Sahoo, N., Swain, J. R.,  Dash, T., and Behera, H. S.
    In 2014 International Conference on Information Technology, ICIT 2014, Bhubaneswar, India, December 22-24, 2014 2014
  2. ICAA
    An Experimental Study of a Novel Move-to-Front-or-Middle (MFM) List Update Algorithm
    Mohanty, R.,  Dash, T., Khan, B., and Dash, S. P.
    In Applied Algorithms - First International Conference, ICAA 2014, Kolkata, India, January 13-15, 2014. Proceedings 2014