• Presently serving as Dean of School of Information Science and Technology
• Coordinator of MSME at AIMIT
• Served as Dean of IT(Academics) for 3 years
• Served as IIC coordinator of AIMIT for one year
• Served as Bioinformatics coordinator from 2013 -2016

Current:

Dean of School of Information SCience and Technology 

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)

•     Ongoing project on "Mechanistic Insights into Plant Growth-Promoting Activities of Trichoderma harzianum from the Jasmine Rhizosphere" with Dr Raghavendra Rao, Professor, St Agnes college  
•    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 
• Completed project with CPCRI, Kasargod for a project in developing deep learning tool for insect identification of white flies in coconut (Dr Sujithra, Principal Scientist, CPCRI)
• Completed project for Development of CRISPR- Cas9 algorithm for designing gRNAs with ICAR - Sugarcane Breeding Institute, Coimbatore (Dr. R. Manimekalai, Principal Scientist (Biotechnology)) (Got a Springer Journal paper as part of the project)
• Ongoing project on biological evaluation of some new heterocyclic compounds with NITK, Suratkal (Dr Arun, Professor, Dept of Chemistry) (Journal paper on process)
• Ongoing project with JSS College Mysore on “Developing computational prediction tool for identifying peptide which can be antimicrobial, antidiabetic and antitoxic” (Got 2 copyrights as part of the project)
• Ongoing project with CPCRI on developing “Computational model for detecting different stages of Tender coconut” (Journal paper in process)
• Ongoing project of Sigatoka (Patent applied)

Reshma Martiz, Hemalatha N, Ameer Suhail et al. (2025) Identification and 3D modeling of bioactive peptides from Lactobacillus brevis RAMULAB49 protein hydrolysate with in silico ERK1 phosphorylation inhibition activity targeting diabetic nephropathy. PLoS One 20(9): e0331192. https://doi.org/10.1371/ journal.pone.0331192

Hemalatha, N., Mohan, R., Sreekumar, K.M., Angel (2025). Innovative Approach to Cucumber Disease Prediction: Leveraging Roboflow for Annotating and Training. In: Bansal, J.C., Saha, S., Coello, C.A.C., Rathore, H. (eds) Advances in Data-Driven Computing and Intelligent Systems. ADCIS 2024. Lecture Notes in Networks and Systems, vol 1333. Springer, Singapore. https://doi.org/10.1007/978-981-96-4536-7_43  

K. P. Gangaraj, M. K. Rajesh, Ashok Kumar Jangam, V. H. Prathibha, S. V. Ramesh, Ginny Antony, Jasmin Habeeb, K. T. K. Amritha, K. S. Muralikrishna, P. B. Rajitha & N. Hemalatha, “Decoding the coconut–Phytophthora conflict: insights from dual RNA-seq analysi”,Journal of Plant Pathology , 2025 https://doi.org/10.1007/s42161-025-02019-5 

Christina EA , Hemalatha N and Sathish Kumar Narayanan, “Modeling Coffee Price Volatility Using Time Series, Hybrid, and Deep Learning Approaches”, Cureus Journal of Computer Science (a part of Springer Nature), pp. 1-15. 2025, https://doi.org/10.7759/s44389-025-07255-5

Bharath AR , Hemalatha N and Sreekumar KM, “Interpretable Deep Learning for Banana Leaf Disease Detection Using Dense Convolutional Models”, Cureus Journal of Computer Science (a part of Springer Nature), pp. 1-10, 2025, https://doi.org/10.7759/s44389-025-08446-w

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, ttps://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

•      Bharath AR , Hemalatha N and Sreekumar KM, “Banana Leaf Disease Detection Using Deep Learning: A Review of Current Models and Techniques", Proceedings of International Conference on AI for Sustainable Future, PA College of Engineering, Kasaragod,  27th September 2025
• Christina EA , Hemalatha N and Sathish Kumar Narayanan, “Modeling Coffee Price Volatility Using Time Series, Hybrid, and Deep Learning Approaches”, Cureus Journal of Computer Science (a part of Springer Nature), pp. 1-15. 2025, https://doi.org/10.7759/s44389-025-07255-5
• Bharath AR , Hemalatha N and Sreekumar KM, “Interpretable Deep Learning for Banana Leaf Disease Detection Using Dense Convolutional Models”, Cureus Journal of Computer Science (a part of Springer Nature), pp. 1-10, 2025, https://doi.org/10.7759/s44389-025-08446-w
• Christina EA , Hemalatha N and Sathish Kumar Narayana, "nA Review of UAVs,Remote sensing and AI for Precision Agriculture in Coffee Farming", International Conference on Recent Advancements in Computing and System Design(InRACS-2025), Vadakara, 25th June 2025
• Bharath A R, Hemalatha N and Sreekumar K M, "Enhancing Banana Leaf Disease Diagnosis Using Explainable Al on a Simple Convolutional Neural Network", International Conference on Recent Advancements in Computing and System Design(InRACS-2025), Vadakara, 25th June 2025
• Shashiprabha and Hemalatha N, "A lightweight vision transformer framework for realtime quality product assessment on mobile device", Springer 2nd International Conference on Responsible Artificial Intelligence, 25-16 Dec, 2025
• 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

• 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

1. Received Prof Narayanan Memorial award for best student in Physics in BSc Mathematics during 1989-1992
2. Stood 2nd rank in Kannur Unniversity for MCA 2001-2004                                                                                                                                                                     

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

Conducted ATAL FDP from Aug 18^th to 23^rd as Coordinator titled “Techharvest: Advancing Computer Science and Agriculture Research fSustainable Agriculture"

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 28^th Feb to 2^nd March, 2023

Mathematics for Machine Learning by NIT, Arunachal Pradesh, 25^th to 30^th Jan’21

Plantation Crop Genomics: An overview of current research by BioNivid Technology Pvt Ltd, 18 to 29^th 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 26^th 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, 5^th to 10^th Oct’20

• Hemalatha, N., Mohan, R., Sreekumar, K.M., Angel (2025). Innovative Approach to Cucumber Disease Prediction: Leveraging Roboflow for Annotating and Training. In: Bansal, J.C., Saha, S., Coello, C.A.C., Rathore, H. (eds) Advances in Data-Driven Computing and Intelligent Systems. ADCIS 2024. Lecture Notes in Networks and Systems, vol 1333. Springer, Singapore. https://doi.org/10.1007/978-981-96-4536-7_43
• Hemalatha N, Akhil Wilson and Raji Sukumar, “Computational prediction model for pepper yield prediction using support vector regression”, 3^rd International Conference on Data Science and Applications (ICDSA 2022). March 26-27
• N Hemalatha, Akhil Wilson and T Akhil, “Computational Prediction of Plastic Degrading Microbes Using Random Forest”,2^nd International Conference on Computer Vision and Robotics (CVR 2022), May 21-22
• Akhil Wilson, Hemalatha N and Raji Sukumar, “Computational Yield Prediction of Rice using KNN Regression”, 2^nd International Conference on Computer Vision and Robotics (CVR 2022), May 21-22
• Akhil Wilson, Akhil Thankachan, N. Hemalatha1*, Lanwin Lobo, PlasPred: computational prediction tool for identifying plastic‑degrading microbes, BMC Bioinformatics, Vol 22(Suppl 16):591, pp 5 (Fifth International Conference “Bioinformatics: from Algorithms to Applications” (BiATA 2021))
• 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 (2017 International Conference on Signal Processing and Communication (ICSPC), Coimbatore)
• 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, 2016 (International conf on Signal, Networks, Computing and Systems, at JNU, New Delhi)
• 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, (International conf on Advances in Computing, Communication and Control, Mumbai)
• 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, DOI 0.1109/CIBCB.2014.6845513, 2014 (IEEE conference on Computaional Intelligence in Bioinformatics and Computational biology, Honululu)
• 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, “Identification and genome-wide analysis of novel tonolplast intrinsic protein (TIP) gene family in indica rice (O. sativa L.SUBSP. indica),” Proceedings of National seminar on innovative gene technologies for conservation and sustainable utilization of island biodiversity, pp 76, Andamans, 2012
• N.Hemalatha, M.K. Rajesh,. N. K. Narayanan, “Prediction of ERF and DREB Proteins Using Support Vector Machine,” Proceedings of National Conference on Advanced IT, Engineering and Management [SACAIM 2012], Mangalore, ISBN #- 978-93-5087-895-8, pp 113-117
• N.Hemalatha, M.K. Rajesh,. N. K. Narayanan, “Naïve Bayes Classifier for Classification of Expansin genes,” Proceedings of National seminar on Stochastic modeling (NSSM 2012), Kannur , Mar21-22, 2012
• N.Hemalatha, M.K. Rajesh,. N. K. Narayanan, “Identification of putative erf and tip gene families in indica,” Proceedings of National conference on computing and communication, NCCC 2011, pp 20, Kottayam, India, 2011
  N Hemalatha & N K Narayanan, “Identification of Genes Related to Expansin Gene Family in Indica Rice using Bioinformatics tools”, “Proceedings of Kerala Science Congress, Peechi, pp 485- 486, Jan 28 – 31, 2010.

https://www.researchgate.net/profile/Hemalatha-Nambisan?ev=prf_overview