Google Scholar Link: https://scholar.google.com/citations?hl=en&user=mozeNIsAAAAJ
Journals
Anjana M.P., Arun K.S., Manu Madhavan, Transformer-based models for uncovering genetic mutations in cancerous and non-cancerous genomes, Gene, 2025 https://doi.org/10.1016/j.gene.2025.149460
Chinju John, Jayakrushna Sahoo, Irish K. Sajan, Manu Madhavan, Oommen K. Mathew, CNN-BLSTM based deep learning framework for eukaryotic kinome classification: An explainability based approach, Computational Biology and Chemistry, 2024, 108169, ISSN 1476-9271, https://doi.org/10.1016/j.compbiolchem.2024.108169.
Chinju John, Jayakrushna Sahoo, Manu Madhavan and Oommen K Mathew, Convolutional Neural Networks: A Promising Deep Learning Architecture for Biological Sequence Analysis, Current Bioinformatics (2023), http://dx.doi.org/10.2174/1574893618666230320103421
Manu Madhavan, Gopakumar G, "DBNLDA: Deep Belief Network based representation learning for lncRNA-disease association prediction." Applied Intelligence (2021): 1-11. DOI: 10.1007/s10489-021-02675-x
Manu Madhavan, Gopakumar G, 2021. Long Non-coding RNAs in Heart Failure: A Deep Belief Network based Cluster Analysis, Current Bioinformatics, 16-1, DOI: 10.2174/1574893616666210528162945
Madhavan, M, Gopalakrishnan G. 2018. An Effective Sequence Structure Representation for Long Non-Coding RNA Identification and Cancer Association using Machine Learning Methods. ACM Applied Computing Review. 18(3):49-58, DOI: https://doi.org/10.1145/3284971.3284976
Satheesh, R., Chakkungal, N., Rajan, S., Madhavan, M., & Alhelou, H. H. (2022). Identification of Oscillatory Modes in Power System Using Deep Learning Approach. IEEE Access, 10, 16556-16565.
Book Chapter
Krutarth, Katharotiya, and Manu Madhavan. "Region-Based Random Color Highlighting in Artistic Style Transfer Using CNN." Advances in Electrical and Computer Technologies. Springer, Singapore, 2022. 81-90
Manu Madhavan, Reshma Stephen, Gopakumar G. 2020. Prediction of lncRNA Cancer association using Topic Models on Graph,Advances in Machine Learning and Computational Intelligence. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-5243-4_28
Conferences
P. K. V and M. Madhavan, "Beyond Primary Sequences: Assessing Secondary Structure Contributions in Protein Classification," 2025 3rd International Conference on Artificial Intelligence and Machine Learning Applications Theme: Healthcare and Internet of Things (AIMLA), Namakkal, India, 2025, pp. 1-6, doi: 10.1109/AIMLA63829.2025.11040958.
Dhanya P, Arun Cyril, Manu Madhavan, Interpretable Textual Data Classification on Transformer Models, ICCCT 2025
Hiba, Deepak, Manu Madhavan, Sinith, WAV2VEC-BASED INTELLIGENT MUSIC RECOMMENDATION FROM TEXT EMOTIONS, International Conference on Control, Communication and Computing 2025
Amrita Kumari and Manu Madhavan, “Graph Representation of Multi-omic Data for Improved Breast Cancer Subtype Prediction” in Second International Conference on Advanced Computing and Systems (AdcomSys), Kolkata, Springer
Agarwal A, Madhavan M, Fine-Tuning Code Models for Bug Severity Prediction: A Comparative Study with GraphCodeBERT and LoRA, International Conference on Data Science and Applications, 2025
Resmi, Manu Madhavan, Nimmy J S, Identifying Disease Cluster from Blood Donor Data using EDA and Graph Modelling, ICCIDE 2024
Akshay S, Manu Madhavan, Comparison of Explainability of Text Classification Models of Malayalam, Proceedings of International Conference on FOSS in Computational Intelligence and Language Technologies, ICFOSS, Thiruvanathapuram, Mar 2024.
Manu Madhavan, Dr. Jeena Kleenankandy, “Teaching NLP in the era of LLMs”, ACM India COMPUTE 2024, IIT Gandhi Nagar, Dec 2024.
Resmi Pillai, Manu Madhavan, Nimmi, “Identifying Disease Clusters from Blood Donor Data using EDA and Graph Modelling “, 6th International Conference on Computational Intelligence & Data Engineering (ICCIDE - 2024), India, 2024.
Gopikrishnan CP, Manu Madhavan, Denoising Autoencoder based Long non-coding RNA-Disease Association Prediction, in The International conference on Machine Learning and Data Engineering (ICMLDE-22), September 7-8, 2022, UPES, Dehradun, India.
Ragupathi, Anjali, Siddharth Shanmuganathan, and Manu Madhavan. "Compressive Performers in Language Modelling." Proceedings of The Fourth International Conference on Natural Language and Speech Processing (ICNLSP 2021). 2021.
C. M. Sreeshma, M. Manu and G. GopaKumar, "Identification of Long Non-coding RNA from inherent features using Machine Learning Techniques," 2018 International Conference on Bioinformatics and Systems Biology (BSB), 2018, pp. 97-102, doi: 10.1109/BSB.2018.8770699.
Manu Madhavan and Gopakumar G. 2018. A tf-idf based topic model for identifying lncRNAs from genomic background. In Proceedings of the 33rd Annual ACM Symposium on Applied Computing (SAC '18). Association for Computing Machinery, New York, NY, USA, 40–46. DOI:https://doi.org/10.1145/3167132.3167133
Manu Madhavan, Robert Jesuraj, Reghu Raj P C, " Design of Scalable Natural Language Report Management System", in short proceedings of Int. Conf. on NLP (ICON) , Delhi, 2013. [ Selected for upload on TDIL-DC portal].
Manu Madhavan, Mujeeb Rehman O, Dr. P. C Reghu Raj, “Computing Prosodic Patterns for Malayalam”, in the proceedings of National Conference on Indian Language Computing, CUSAT, India, 2013. Also published in CSI Digital Resource Center http://csidl.org/xmlui/handle/123456789/543
Manu Madhavan, Dr. P. C Reghu Raj, “Application of Karaka Relations in Natural Language Generation”, in the proceedings of National Conference on Indian Language Computing, CUSAT, India, 2012.
Articles