Dean
An academician and researcher with over 26 years of experience, including 23 years in academia and 3 years in industry. Currently serving as the Dean of the School of Information Science & Technology, she specializes in Computational Biology, Machine Learning, Deep Learning and Bioinformatics. Her work spans interdisciplinary research with prestigious institutions such as CPCRI, ICAR-SBI, and NITK focusing on agricultural AI and genomics. As a researcher she has articles in peer-reviewed journals in Scopus and Springer-indexed platforms, reflecting her active contributions to the fields of AI-driven biology, computational modeling, and agricultural informatics.She holds a senior membership with IEEE and ACM, and is a lifelong member of IACSIT. Beyond her research, she actively mentors students, served as a conference convenor, and is a frequent speaker at national and international forums.
Sl.No | Qualification Level | University | Area of Specialization | Year of Completion | Awards |
---|---|---|---|---|---|
1 | Ph.D. | Kannur University | Information technology | 2016 | |
2 | MCA | Kannur University | 2004 | Ranked 2nd in Kannur University |
|
3 | MBA | Delhi University | 2000 | ||
4 | PGDCA | Mangalore University | 1993 |
Current:
Dean of School of Information SCience and Technology (15-07-2007 to Till date)
Previous
Lecturer at Kasargod Government college in contract (2004-2005)
Lecturer at College of Agriculture, Nileshwar in contract ( 2005-2006 May)
Computer Instructor at KSWDC, Kerala (1999 - 2001)
Systems Executive at NIIT, Kalkaji, New Delhi (1993 - 1996)
· PI for a Major project funded by MJES “Genomics, Proteomics and Computational approach for the detection of high efficient microbes in plastic degradation and production of biopolymers “, 2.2 Lakhs 2019-22
· Crop auto diagnoser for popular vegetable cucumber, Minor research project funded by MJES, 2023-25, 2.10 lakhs
· C. P. Mohammed Ajmal, S. Keerthana, N. Hemalatha and K. Ameer, “Development of CRISPR‑Cas9 Algorithm for Designing gRNAs for Polyploid Sugarcane”, Sugar Tech, 2024, https://doi.org/10.1007/s12355-024-01523-9 (Q2 Quartile, 1.8 Impact)
· Rithika Adapa, Raksha, N. Hemalatha, Prathamesh Pai, K. M. Sreekumar, P. K. Sajeesh, and Sainamole Kurian, “A Unified Image Repository for Cucurbits Diseases and Pests”, Springer CICS series, CCIS 2231, pp. 1–11, 2025. https://doi.org/10.1007/978-3-031-75605-4_2
· Shylaja P and Hemalatha N, "Coconut palm diseases caused by fungi, bacteria, phytoplasma and virus – an ultimatum to palms of global economy", The Seybold Report, Vol 18(7), 2023 (Scopus indexed,Q3quartile) https://seyboldreport.org/article_overview?id=MDcyMDIzMDkxNzEzMjA0MDY3
· N. Hemalatha, P. Sukhetha and R. Sukumar, "Classification of Fruits and Vegetables using Machine and Deep Learning Approach," IEEE Explore, pp. 1-4, doi: 10.1109/TQCEBT54229.2022.10041654 (Scopus Indexed)
· Hemalatha, N., Akhil, W., Vinod, R., Akhil, T. (2023). Computational Prediction of Plastic Degrading Microbes Using Random Forest. In: Shukla, P.K., Singh, K.P., Tripathi, A.K., Engelbrecht, A. (eds) Computer Vision and Robotics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-7892-0_22 (Scopus Indexed)
· Hemalatha, N., Akhil, W., Vinod, R. (2023). Computational Yield Prediction of Rice Using KNN Regression. In: Shukla, P.K., Singh, K.P., Tripathi, A.K., Engelbrecht, A. (eds) Computer Vision and Robotics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-7892-0_23, (Scopus Indexed)
· Akhil Wilson, Raji Sukumar and Hemalatha N, "Computational Model for Pepper Yield Prediction Using Support Vector Regression", In: Saroj Hiranwal and Garima Mathur (eds), Artificial Intelligence and Communication Technologies, SCRS, India, 2023, pp. 779-788. https://doi.org/10.52458/978-81-955020-5-9-73
· Raji Sukumar, Hemalatha N, Sarin S, and Rose Mary C A. 2021. Text Based Smart Answering System in Agriculture using RNN. In Proceedings of the 18th International Conference on Natural Language Processing (ICON), pages 663–669, National Institute of Technology Silchar, India. NLP Association of India (NLPAI)
· Anna Rini, Hemalatha N and Raji Sukumar, “Decision Tree Classification of Digital Soil, Weather, Crop Mapping and Yield Prediction using Linear Regression with region influences”, agriRXIV, Preprints for Agriculture and Allied Sciences, DOI: https://agrirxiv.org/searchdetails/?pan=20210310499
· Lidia Cleetus, Raji Sukumar A and Hemalatha N, “Computational Prediction of Disease Detection and Insect Identification using Xception model”, bioRXiv, The Preprint server of Biology, Aug, 2021, https://doi.org/10.1101/2021.08.10.455608
· Akhil Wilson, Akhil Thankachan, N Hemalatha and Lanwin Lobo, “Plaspred: computational prediction tool for identifying plastic degrading microbes”, Selected abstracts of Bioinformatics: from Algorithms to Applications 2021 Conference, BMC Bioinformatics 2021, 22(Suppl 16):591 https://doi.org/10.1186/s12859-021-04475-z
· Hemalatha N, Melcy Philip, “A novel Bioinformatics analysis for SARS CoV-2 isolated by Public Health Laboratory, USA”, Research Journal of Biotechnology, Vol. 16(5), 2020 Scopus indexed, ISSN: 0973-6263 (SCI impact factor of 0.233)
· Hemalatha N, Manasa, Kavyashree P, Anusha T.A and Rajesh M.K,Computational Prediction Tool for Leafy Cotyledon Proteins (Lec) in Oil Palms and Date Palms, IEEE Explore, pp 337-340, 2017
· N Hemalatha and N.K Narayanan., “A Support Vector Machine approach for LTP using Amino Acid composition”, Lecture Notes in Electrical Engineering, Springer, Vol 396, pp 13-23, DOI 10.1007/978-81- 322-3589-7_2, 2016.
· V. Akhil, V. Amal, N. Hemalatha and M. K. Rajesh, “A Machine Learning Approach for Prediction of Domains of DELLA Proteins, a Key Component of Gibberellic Acid Signaling in Plants”, Indian Journal of Science and Technology, vol 9(12), 2016
· Akhil, V.,Rahul C.U, Amal V, Hemalatha N and Rajesh M.K, "CnMAPKPred: A machine learning approach for predicting mitogen-activated protein kinase (MAPK) in coconut" Journal of Phytology, vol 6, 2015
· Manjula M.S, Rachana K.E, Naganeeshwaran S, Hemalatha N, Anitha K and Rajesh M.K, "PRGPred: A platform for prediction of domains of resistance gene analogue (RGA) in Arecaceae developed by using machine learning algorithms", J. BioSci. Biotechnol, vol 4(3), pp. 327-338, 2015
· M.S.Manjula, K.E.Rachana, S. Naganeeswaran, N. Hemalatha, Anitha Karun and M.K.Rajesh, “PRGPred: A platform for prediction of domains of resistance gene analogue (RGA)in Arecaceae developed using machine learning algorithms,” Journal of Bioscience and Biotechnology, vol 4(3), 2015
· Hemalatha N, Brendon V.F, Shihab M.M and Rajesh M.K, “Machine Learning Algorithm for Predicting Ethylene Responsive Transcription Factor in rice using an Ensemble Classifier,” Procedia Computer Science, vol 49, pp. 128-135, 2015
· Sreepriya P., Naganeeswaran S., Hemalatha N., Sreejisha P. and Rajesh M. K., “A Machine Learning Approach for Prediction of Gibberellic Acid Metabolic Enzymes in Monocotyledonous Plants,”Transactions on Machine Learning and Artificial Intelligence, vol 2(4), pp. 36-47, 2014
· Hemalatha N, Rajesh M.K and Narayanan N.K, “A Machine learning approach for detecting MAP kinase in the genome of Oryza sativa L. ssp. Indica,” IEEE explore, 2014
· Merin K.E, Rajesh M.K, Jamshinath T.P, Hemalatha N, Murali Gopal and George V.T ,“SVM and HMM approaches for computational prediction of σ70 promoters in Pseudomonas spp. using characteristic fourmer motifs,” Indian Journal of Agricultural Sciences, vol. 84 (1), pp. 119-123, 2014
· Anil Paul, N. Hemalatha and M.K. Rajesh, “LTTRPred: A tool for prediction of LysR-type transcriptional regulator of pyoluteorin pathway in plant growth promoting Pseudomonas spp.,” Journal of Plantation Crops, pp. 371-377, 2014
· N.Hemalatha, M.K. Rajesh,. N. K. Narayanan, “Machine Learning Approaches for Prediction of Expansin Gene Family in Indica Rice,” Agricultural Research, Springer-Verlag, vol 2(4), pp 309-318, 2013.
· N.Hemalatha, M.K. Rajesh,. N. K. Narayanan, “Computational approach for the prediction of ERF and DREB proteins in indica rice using SVM,” ORYZA, An International Journal on Rice, vol. 49(4), pp. 239-245, 2013.
· N.Hemalatha, M.K. Rajesh,. N. K. Narayanan, “An integrative system for Prediction of NAC proteins in rice using different feature extraction methods,” International Journal on Soft Computing (IJSCC), Vol.4(1), pp 9-21,2013
· N.Hemalatha, M.K. Rajesh,. N. K. Narayanan, “Genome-wide Analysis of Putative Erf and Dreb Gene Families in Indica Rice (o. Sativa l. Subsp. Indica),” International Journal of Machine Learning and Computing (IJMLC), Vol. 2(5), pp. 556-559, ISSN 2010-3700, 2011
N.Hemalatha, M.K. Rajesh,. N. K. Narayanan, “Genome-Wide Analysis and Identification of Genes Related to Expansion Gene Family in Indica Rice” – Int. J. Bioinformatics Research and Applications, Vol. 7, No. 2, pp162-167, 2011
Raji Sukumar, Hemalatha N, Sarin S, and Rose Mary C A. 2021. Text Based Smart Answering System in Agriculture using RNN. In Proceedings of the 18th International Conference on Natural Language Processing (ICON), pages 663–669, National Institute of Technology Silchar, India. NLP Association of India (NLPAI).
Vrinda.K, Nanditha K M and Hemalatha N, “Bioinformatics Analysis Biodegradation of Plastic using Microorganisms”, Presented at SACAIM International conference, Nov, 2019
Gangaraj.K, Rajesh.M.K, Hemalatha N, Melcy Philip, Vrinda.K,” Computational prediction model for NLP protein in Phytophthora palmivora”, Presented at SACAIM International conference, Nov, 2019
Hemalatha N, Athul K P and Navneeth R, “Detection of Skin Cancer Using Deep CNN”, Presented at SACAIM International conference, Nov, 2019
Hemalatha N, Asha Nair and Anusha T A, “Identification of Plant disease in leaves, using Deep Neural Networks”, Presented at SACAIM International conference, Nov, 2019
Hemalatha N, Sneha G and Anusha T A, “Detection of Plant Leaf disease using Machine Learning Algorithms”, Presented at SACAIM International conference, Nov, 2019
Avani S, Karthika H and Hemalatha N, “Application of ANNin Human diseases and Agriculture”, Presented at SACAIM International conference, Nov, 2019
Hemalatha N, Anusha T A, Rajesh M K and N K Narayanan, “LTP Prediction based on Amino acid Compositions using Machine Learning Algorithms,”, International Conference on Artificial Intelligence and Machine Learning (IAIM2019 )
Hemalatha N and Sinchana, “Protein function prediction using Support Vector Machine,” National seminar on Emerging Technologies in Computer science & Information Technology, 2015.
Hemalatha N and Larissa, “A Comparative Analysis on the Soft Computing Approaches for Protein Structure Prediction,” Proceedings of National Joint Conference on Innovations in Engineering & Technology (NJCIET), 2015.
Hemalatha N., Shonal.,& Renita , "Classification of lipid transfer protein by means of feature extraction with support vector machine,” In: Compendium : Symposium on Accelerating Biology Computing life, 18-20 Feb, 2014, CDAC, Pune, India, pp 150-151
Anusha T A, Hemalatha N and Rajesh M K, “ Computational Prediction of SERK proteins using SMO algorithm”, National conference on Nanomaterials for Biomedical Applicaton (NBA-2017), Yenepoya Research Centre, 2017
Jithin Mathew and Hemalatha N, “DNA Computing: A Review on Development and Application”, National conference on Nanomaterials for Biomedical Applicaton (NBA-2017), Yenepoya Research Centre, 2017
Kavyashri, Manasa, Hemalatha N and Rajesh M K,” A Machine Learning Algorithm for Predicting Wuschel Proteins”, National conference on Nanomaterials for Biomedical Applicaton (NBA-2017), Yenepoya Research Centre, 2017
Reshma Mary Martiz and Hemalatha N, “Homology Modeling of Amyloid Precursor in Alzhemiers”, National conference on Nanomaterials for Biomedical Applicaton (NBA-2017), Yenepoya Research Centre, 2017
Rohan Loy Dsouza and Hemalatha N, “Homology Modelling of Kinase Inhibitor in Cancer”, National conference on Nanomaterials for Biomedical Applicaton (NBA-2017), Yenepoya Research Centre, 2017
Supaksha M.A and Hemalatha N, “Homology Modeling of Collagen Protein in Ebola”, National conference on Nanomaterials for Biomedical Applicaton (NBA-2017)”, Yenepoya Research Centre, 2017
Rohan Loy Dsouza and Hemalatha N, “Computational Drug Model for Celiac Disease”, Bioinformatica Indica, University of Kerala, 2018
Jithin Mathew and Hemalatha N, “An interaction study of Botulinum neurotoxin with different neutralizing agents and its effect on SNAP-25 protein: A computational model”, Bioinformatica Indica, University of Kerala, 2018
Reshma Mary Martiz and Hemalatha N, “Computational Model For PSEN Using Protein-ligand Docking”, Bioinformatica Indica, University of Kerala, 2018
International Association of Computer Science and Information Technology (IACSIT) : Membership No. is 80340899 and member since 2012
IEEE Senior member : 93009616 since 2019
ACM : 7059155
SCRS : 2056100046
Attended National Level Virtual Faculty Development Programme on ”Tech-Driven Research : Leveraging AI, IoT and Collaboration for Academic Excellence“ organised by the Consortium of Higher Educational Institutions for Research and Development (CHIRD) from September 2 - 7, 2024.
Successfully completed NPTEL FDP program on Medical Image Analysis in 2023
Attended 3 days Symposium "Accelerating Biology 2023: Discovery to Delivery" at CDAC, Pune from 28th Feb to 2nd March, 2023
Mathematics for Machine Learning by NIT, Arunachal Pradesh, 25th to 30th Jan’21
Plantation Crop Genomics: An overview of current research by BioNivid Technology Pvt Ltd, 18 to 29th Jan’21
"Entrepreneurship Development Program” as part of IIC Innovation Ambassador Training Series Organized by Institution’s Innovation Council of MHRD’s Innovation Cell, AICTE held at ACS College of Engineering, Bangalore, Karnataka , 26-27 February 2020
5 Days Workshop on Outcome Based Education by IPSR solutions ltd, 22 to 26th June’20
DIGITAL TEACHING TECHNIQUES by ICT academy, 24 Aug 2020 to 29 Aug 2020
6 days STTP pgm on Machine learning and Deep learning models for medical domain applications by MIT, Manipal, 5th to 10th Oct’20
https://www.researchgate.net/profile/Hemalatha-Nambisan?ev=prf_overview
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