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Dilanga Abeyrathna, Ph.D.

Ph.D. in IT

AI Developer / ML Engineer / Data Engineer

      Resume       Academic CV

About Me

I am a Ph.D candidate with a proven track record of research and development of groundbreaking AI/ML solutions and algorithms to tackle intricate challenges across diverse domains over 7 years.

Experience

Graduate Research Assistant

University of Nebraska - Omaha

  • My main duties are conducting research and development for collaborators and publishing scholarly research articles. Apart from that, mentoring graduate-level, undergraduate-level, and high-school-level students, and conducting workshops are some of the other main duties.

    • Graduate Teaching Assistant

    University of Nebraska - Omaha

  • Course: CSCI 4970 - Undergraduate - Computer Science Capstone
  • Duties: Acted as a project manager role for 30 undergraduate capstone projects with real clients, task tracking, implementation progress tracking, attending client meetings, attending weekly progress meetings, grading and evaluation.

    • AI Developer - Intern

    GUARDIAN RFID, Maple Grove, MN

  • Contributed to the correction officers, by machine learning model building, testing, and deployment tasks using PyTorch, Flask/FastAPIs, Dockers, CI/CD testing, and maintenance.

    • Instructor

    University of Nebraska - Omaha

  • Course: CIST 1300 - Introduction to Web Development
  • Conducted Lectures, lab sessions, grade assignments, proctor and grade exams, and other duties as assigned by the course in charge.

    • Graduate Teaching Assistant

    University of Nebraska - Omaha

  • Course: CIST 1620 - Introduction to Computer Science II (JAVA programming)
  • Duties: Conducted lab sessions, graded assignments, proctored and graded exams outside of scheduled class hours, and other duties as assigned by the supervisor.

    • Instructor

    Techademy, University of Nebraska - Omaha

  • Course: Artificial Intelligence and Intro to Machine Learning
  • Duties: Conducted virtual sessions to high-school students

    • Graduate Teaching Assistant

    University of Nebraska - Omaha

  • Course: CIST 1400 - Introduction to Computer Science I (JAVA programming)
  • Duties: Conducted lab sessions, graded assignments, proctored and graded exams outside of scheduled class hours, and other duties as assigned by the supervisor.

    • Graduate Research Assistant

    University of Nebraska - Omaha

  • My main duties were conducting research and development for collaborators and publishing scholarly research articles. Apart from that, mentoring graduate-level, undergraduate-level, and high-school-level students, and conducting workshops were some of the other main duties.

    • Instructor

    University of Peradeniya, Sri Lanka

  • Courses: Digital Image processing using MATLAB, Artificial Intelligence and Expert Systems, Operating System Concepts, Object Oriented Programming (JAVA), Data Structures and Database Management Systems, Server-Side Web Programming.
  • Duties: Mainly created exam papers, marked tutorials, quizzes, exam papers, and invigilated exams in the above-mentioned theory/practical courses.

    • Software Engineer

    hSenid Mobiles Solution, Sri Lanka

  • I contributed to the e-Local Government project, by developing Android RESTful Client mobile application and Server-side RESTful web services. I also played a key role in the testing team of an ongoing Airtel (Sri Lanka) chat application project.

    • Education

    Ph.D. in Information Technology

    Jan 2019 - May 2024

    University of Nebraska at Omaha

  • Concentration : Artificial Intelligence, GPA 3.81
  • Dissertation : Self-Supervised Representation Learning on Multi-Label Classification

    • Master of Computer Science

    Aug 2016 - Dec 2018

    University of Nebraska at Omaha

  • Concentration : Database and Knowledge Engineering, GPA 3.70
  • Thesis : Multi-Label Classification Using Higher-Order Label Clusters

    • Bachelor of Science in Computer Science

    Jul 2009 - Jan 2014

  • Major : Computer Science, Statistics and Mathematics, GPA 3.75
  • Thesis : Performance Comparison of Emerging HEVC Standard with H.264/AVC and frame interpola- tion based Error Correction Technique for HEVC decoder.

    • Projects

    Kaggle - Health Data Analysis and Visualization

    Performed data cleaning, transformations, feature selection, exploratory data analysis (EDA), and Visualization on Kaggle tabular dataset (∼10,000)

    Created descriptive dashboard visualizations for the data and deployed on StreamLit. (Python | StreamLit | Plotly | SQL | Pandas)

    StreamLit deployment

    Adaptive course syllabus design with LLMs

    Multi-LLM agent based customizable course syllabus designer and content generator for newly appointed Faculty.

    Leveraged multiple LLM agents to evaluate and enhance course outlines and lesson plans by refining the prompts. (Langchain, Huggingface, ChatGPT API, MongoDB)

    GitHub

    LLM-based Bio-material info crawler

    A web API with custom Large Language Models (LLM) for effective retrieval of relevant information from unstructured text collections of bio-material research articles.

    Used RAG techniques to boost the accuracy and mitigate the hallucinations. (Langchain, Huggingface, ChatGPT, Docker, Flask)

    GitHub

    Customer Churn Prediction

    The primary goal of this project is to build a classification model to predict the churn probability of a customer accounts. The main dataset used for modeling gives information about the customers of United Communication and certain attributes that model their interactions.

    Github

    Presentation

    HelloGaze - A Distortion Correction App for AMD

    HelloGaze is a software application designed for Windows operating systems, developed using C#.NET and Visual Studio. It incorporates the Tobii Eye Tracking Pro SDK to monitor eye movements and implement adaptive distortion correction specifically tailored for individuals suffering from AMD. This initiative is a collaborative effort with the Byers Eye Institute at Stanford University with University of Nebraska Omaha.

    Youtube video

    Patient Data Management System

    Developed a web-based Patient Data Management System which collects patient details in to centralized database for data analytics.

    Github

    Chess-end-game

    Developed a Chess-end-game application using C#.NET as a mini project using Artificial Intelligence techniques.

    Github

    Semi-Join simulation

    Developed GUI-based distributed Semi-Join simulation for simple SQL ad-hoc queries using C#.NET.

    Github

    The Elbow method

    Implemented a mathematical model of the Elbow method to determine the ambiguous natural number of clusters for a dataset.

    Github

    Publications

    Journals (Peer-reviewed)

  • V. Bommanapally, D. Abeyrathna, M. Ashaduzzaman, M. Subramaniam, and P. Chundi. Super Resolution based Methodology for Self-Supervised Segmentation of Microscopy Images. Frontiers in Microbiology, Systems Microbiology, 2024.

  • D. Abeyrathna, S. Rauniyar, R.K. Sani, and P.C. Huang. A Morphological Post-Processing Approach for Overlapped Segmentation of Bacterial Cell Images. Machine Learning and Knowledge Extraction (IMDP), 4(4), 1024-1041, 2022.

  • D. Abeyrathna, M. Ashaduzzaman, M. Malshe, J. Kalimuthu, V. Gadhamshetty, P. Chundi and M. Subramaniam. An AI-Based Approach for Detecting Cells and Microbial Byproducts in Low Volume Scanning Electron Microscope Images of Biofilms. Frontiers in Microbiology, Systems Microbiology, 2022.

  • A. D. Chakravarthy, D. Abeyrathna, M. Subramaniam, P. Chundi, and V. Gadhamshetty. Semantic Image Segmentation Using Scant Pixel Annotations. Machine Learning and Knowledge Extraction (IMDP), 4(3), 621-640, 2022.

  • M. B. Dissanayake and D. Abeyrathna. Performance comparison of HEVC and H.264/AVC standards in broadcasting environments. Journal of Information Processing Systems, 11(3), 2015.

    • Conferences (Peer-reviewed)

  • D. Abeyrathna, T. Life, S. Rauniyar, S. Ragi, R. Sani and P. Chundi. Segmentation of Bacterial Cells in Biofilms Using an Overlapped Ellipse Fitting Technique. In 2021 International Conference on Bioinformatics and Biomedicine (BIBM), pages 3548-3554. IEEE, 2021.

  • D. Abeyrathna, M. Subramaniam, P. Chundi, M. Hasanreisoglu, S. Halim, P. Ozdal, and Q. Nguyen. Directed Fine Tuning Using Feature Clustering for Instance Segmentation of Toxoplasmosis Fundus Images. In 20th International Conference on Bioinformatics and Bio-engineering (BIBE). IEEE, 2020.

  • D. Abeyrathna, P.C. Huang, and X. Zhong. Anomaly Proposal-Based Fire Detection for Cyber-Physical Systems. In 6th Annual International Conference on Computational Science and Computational Intelligence (CSCI'19), pages 1203-1207. IEEE, 2019.

  • A. D. Chakravarthy, D. Abeyrathna, M. Subramaniam, P. Chundi, S. Halim, M. Hasanreisoglu, S. Yasir, and Q. Nguyen. An approach towards automatic detection of Toxoplasmosis using fundus images. In 19th International Conference on Bioinformatics and Bioengineering (BIBE), pages 710-717. IEEE, 2019.

  • D. Abeyrathna, S. Vadla, V. Bommanapally, M. Subramaniam, P. Chundi, and A. Parakh. Analyzing and predicting player performance in a quantum cryptography serious game. In International Conference on Games and Learning Alliance, pages 267276. Springer, 2018.

  • M. B. Dissanayake and D. Abeyrathna. Edge-based frame inter-polation technique for error correction at HEVC decoder. In 8th International Conference on Ubi-Media Computing (UMEDIA), pages 263-267. IEEE, 2015.

    • Abstracts and Workshops

  • M. Rahman, V. Bommanapally, D. Abeyrathna, M. Ashaduzzman, M. Tripathi, M. Zahan, M. Subramaniam, & V. Gadhamshetty. Abstract on Machine Learning-Assisted Optical Detection of Multilayer Hexagonal Boron Nitride for Enhanced Characterization and Analysis. In 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023.

  • A. Akhavanrezayat, V. Bommanapally, D. Abeyrathna, M.S. Halim, C. Or, I. Karaca, G. Uludag, N. Yavari, V. Bazojoo, A. Mobasserian, Y. Shin, M. Hasanreisoglu, P. Chundi, Q. Nguyen, and M. Subramaniam. Abstract on A novel objective method to detect the foveal center point in the rtx1TM device using artificial intelligence, Investigative Ophthalmology & Visual Science, 64(8), pp.1068-1068, 2023.

  • D. Abeyrathna, and M. B. Dissanayake. Abstract on Performance Comparison of Emerging High-Efficiency Video Coding (HEVC) and h.264/ AVC Standards was published in the proceedings of PGIS Research Congress, Post Graduate Institute of Science, University of Peradeniya, 2015.

    • Book Chapters and Patents

  • D. Abeyrathna, M. Subramaniam, and P. Chundi. An Overview of Machine Learning. In P. Chundi, V. Gadhamshetty, B. Jasthi, and C. Lushbough (Eds.) Machine Learning in 2D Materials Science (pp. 144-163). CRC Press, 2023 (ISBN 9780367678203)

  • A. Akhavanrezayat, K.J Hassan, Q.D. Nguyen, M. Subramaniam, V. Bommanapally, and D. Abeyrathna. Artificial Intelligence-Based Methods to Objectively Identify the Foveal Center in Adaptive Optics Retinal Imaging. U.S. Provisional Patent Application No. US 63/497,679. (Patent)

    • Skills

    Best Visualization - Runners Up Datapalooza 2019

    Worked as a team of three and won 2nd place for Visualization in a national level data analytics competition conducted by the Holland Computing Center at Lincoln, NE to analyze a large, rich and complex data set provided by an industry sponsor. More details

    Datapalooza 2019

    Best Presenter Award - 8th Annual CS Graduate Research Workshop 2018

    Computer Science Department - University of Nebraska at Omaha

    Presented on the topic of “Cover Coefficient Clustering based approach to enhance Multilabel classification predictive performance”.

    Best Presentation Award - CSG International Hackathon 2017

    Worked as a team of 3 to develop a mobile and web-based video streaming solution called DartaGram. Features include searching for and sharing videos (up to 1 minute in length) given a location. DartaGram uses Geo-Coordinates to pull up videos within the vicinity and Geo-Alerts users of locations with video requests. Future enhancements include live streaming support and gif thumbnails for videos. Compatible platforms - Windows Azure, Android Lollipop, Windows Tablet.

    Presentation

    Championship award of IEEE ACES coders 2012

    Member of the three members' champion team of IEEE ACES coders', which was a 12 hour algorithmic problem solving coding competition in 2012 held at the Faculty of Engineering in University of Peradeniya, Sri Lanka.

    Presentation

    IEEExtream Coding Competition 2011

    Team Team #27 participated in IEEExtream 5 coding competition and secured the place 172 out of over 1500 teams around the world

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