Dr. Damayanthi Herath

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Dr. Damayanthi Herath

Senior Lecturer

BIO

Dr. Damayanthi Herath is a highly skilled academic with expertise in Computer Engineering, Machine Learning, and Computational Biology. Her research interests are in Explainable AI, Computer Vision, Machine Learning and -omics data analysis. Further, she is passionate on exploring innovative ways for education including edutainment. She is currently actively coordinating the Data Engineering and Research (DEAR) group and Computational Biology (CompBio) group at Peradeniya. She currently teaches the Artificial Intelligence related courses at the department: Data Structures and Algorithms, Machine Learning and Data Mining, Artificial Neural Networks and Fuzzy Systems, and Artificial Intelligence and coordinates the final year projects.

Being an advocate for knowledge dissemination, Dr. Damayanthi has organised a number of conference workshops and tutorials on machine learning and computational biology.

Dr. Damayanthi has secured multiple grants together with local and international collaborators. She is driven for inclusive approaches fostering innovation and for enabling diverse perspectives to tackle complex scientific challenges.

Dr. Damayanthi has supervised a number of undergraduate research students, and postgraduate students. Next to teaching, her key passion is to explore and expand the knowledge together with her research students. Her guidance has helped students conducting award winning research and pursuing higher studies at prestigious groups. Through her exceptional collaborative skills, she brings together experts from diverse disciplines, creating multidisciplinary teams that drive innovation and solve complex scientific challenges.

Dr. Damayanthi earned her B.Sc. (Hons) degree in Computer Engineering from University of Peradeniya in 2012. After serving in the industry, she joined back the department as a lecturer in the year 2015. he was a member of the Optimisation and Pattern Recognition Research Group of Melbourne School of Engineering, The University of Melbourne as a PhD candidate from 2015-2018. where she worked on computational models and methods to profile inherently diverse DNA sequencing data which encode genetic information of multiple species and organisms. Her work in PhD will assist in understanding the dynamics of microbes, their effects on our surroundings and functionalities of multiple cells under different environments. She is currently a member of IEEE.

Educational Qualifications:
  • BSc (Eng)
  • PhD, Melbourne
Awards and Honours:
  1. University Research grant 2021 from University of Peradeniya.
  2. Merit Award for research from the National Research Council, Sri Lanka, 2019.
  3. AGTA 2018 The best poster (student) prize – Nov 2018 Australiasian Genomic Technologies Association : Awarded to the best poster presented at the AGTA 2018 conference, Adelaide, Australia
  4. AGTA Travel award 2018 – Oct 2018 Australian Genomic Technologies Association :Supporting the presentation of research work at AGTA 2018, Adelaide, Australia (https://agtaconference.org/)
  5. Stawell Scholarship – Jul 2017 Melbourne school of Engineering
  6. GHC Student Scholarship – May 2017 Anita Borg Institute (ABI) : The ABI scholarship for Grace Hopper Celebration of Computing (GHC) gives the opportunity to outstanding female students and faculty to attend GHC conference, the world’s largest gathering of women technologists
  7. Melbourne International Fee Remission Scholarship – Jun 2015 University of Melbourne
  8. Melbourne International Research Scholarship – Jun 2015 The University of Melbourne
  9. Scholarship winner to attend 4th South Asian Workshop on Research Frontiers in Computing – May 2014 School of Computing, National University of Singapore
  10. First Runners up in Tech Day 2013 Blogging competition – Oct 2013 Virtusa
  11. Industrial and Financial Systems (IFS) Gold medal for Excellence in Computer Engineering May 2013 IFS : Awarded by IFS , Sri Lanka annually appreciating the student who excel in academics being the Computer Engineering field Top in Faculty of Engineering, University of Peradeniya
  12. Manel Ileperuma scholarship – Mar 2010 Alumni Association of University of Peradeniya
Subjects:
  • CO324: Network and Web Application Development (2021-S5)
  • CO544 : Machine Learning and Data Mining (2021-S7)
  • CO544: Artificial Neural Networks and Fuzzy Systems (2021-S7)
Available for Supervision:
  • Yes
  • The projects can be viewed at Here
Research projects supervised by Dr. Damayanthi Herath:
ABM for Micro Mobility in Sri Lankan Cities
ABM for Micro Mobility in Sri Lankan Cities
Automated Protein Function Prediction
Automated Protein Function Prediction
Using Computer Vision and Agent Based Modelling to Explore the Human Elephant Conflict
Using Computer Vision and Agent Based Modelling to Explore the Human Elephant Conflict
Explainable Machine Learning for Real World Resource Constrained Problems
Explainable Machine Learning for Real World Resource Constrained Problems
Identifying keywords in legal articles using ML techniques
Identifying keywords in legal articles using ML techniques
Revealing miRNA Biomarkers for Alzheimer s Disease using NGS
Revealing miRNA Biomarkers for Alzheimer s Disease using NGS
Acceleration of deep neural network based nanopore super accuracy basecalling
Acceleration of deep neural network based nanopore super accuracy basecalling
Deep Learning for Side Channel Attacks
Deep Learning for Side Channel Attacks
Investigating Onchip Sensor Based RPA Attack Vulnerabilities of Light Weight Ciphers
Investigating Onchip Sensor Based RPA Attack Vulnerabilities of Light Weight Ciphers
Large Language Models in Education
Large Language Models in Education
using machine learning in high stake settings
using machine learning in high stake settings

Please note that here only contain the 'Projects' which were submitted to the projects.ce.pdn.ac.lk as Final Year Research Projects. The actual list of projects supervised by Dr. Damayanthi Herath may be longer than this.

Research Interests:
  • Data Engineering
  • Machine Learning
  • Metagenomics
  • Computational Biology
  • Edutainment
Publications:
  • Revealing MicroRNA Biomarkers for Alzheimer’s Disease Using Next Generation Sequencing Data
    Imalsha Dinuwanthi, Hasini Thilakarathna, Vidwa Sripadi, Damayanthi Herath , Roshan Ragel
    2021 10th International Conference on Information and Automation for Sustainability (ICIAfS), 2021
    doi: 10.1109/ICIAfS52090.2021.9606093
  • Transfer Learning for Accurate and Efficient Tomato Plant Disease Classification Using Leaf Images
    LA Chamli Deshan, MK Hans Thisanke, Damayanthi Herath
    2021 IEEE 16th International Conference on Industrial and Information Systems (ICIIS), 2021
    doi: 10.1109/ICIIS53135.2021.9660681
  • Chronic kidney disease prediction using machine learning methods
    2020 Moratuwa Engineering Research Conference (MERCon) - IEEE, 2020
    doi: 10.1109/MERCon50084.2020.9185249
    [ PDF ]
    #Kidney#Diseases#Machine learning#Red blood cells#Hypertension
  • Detection of Novel Biomarker Genes of Alzheimer’s Disease Using Gene Expression Data
    Shehan Perera, Kaveesha Hewage, Chamara Gunarathne, Rajitha Navarathna, Damayanthi Herath , Roshan G Ragel
    2020 Moratuwa Engineering Research Conference (MERCon), 2020
    doi: 10.1109/MERCon50084.2020.9185336
    [ PDF (Preprint) ]
    #Principal component analysis#Feature extraction#Forestry#Correlation#Support vector machines#Dementia
  • A Data Driven Binning Method to Recover More Nucleotide Sequences of Species in a Metagenome
    Kasun Vimukthi, Geeth Wimalasiri, Prabhath Bandara, Damayanthi Herath
    2020 Moratuwa Engineering Research Conference (MERCon), 2020
    doi: 10.1109/MERCon50084.2020.9185388
    #Genomics#DNA#Sequential analysis#Bioinformatics#Taxonomy#Clustering algorithms#Benchmark testing
  • miRNAFinder: A pre-microRNA classifier for plants and analysis of feature impact
    Puwasuru Ihalagedara, Sandali Lokuge, Shyaman Jayasundara, Damayanthi Herath , Indika Kahanda
    2020 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2020
    doi: 10.1109/CIBCB48159.2020.9277723
    #Feature extraction#RNA#Support vector machines#Testing#Animals#Vegetation#Random forests

Please note that here only contain the 'Publications' affiliated with the Department of Computer Engineering, which were submitted to the site. To see the full publication profile, visit the ResearchGate or Google Scholar profile.