Lasith Dissanayake

Materials Science & Engineering Graduate

Interested in utilizing Machine Learning and Computational Modeling to solve complex materials science challenges

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Lasith Dissanayake

Educational Background

B.Sc. Eng. Hons. in Materials Science & Engineering, University of Moratuwa.

University of Moratuwa

B.Sc. Eng. Hons. in Materials Science & Engineering (2021 - 2025, July)
CGPA - 3.55 (with 4 Dean's List Performances)
Focused on integrating Machine Learning and Materials Modelling with Materials Science and Engineering.

Kingswood College Kandy

2005 - 2018
GCE O/L Examination - 8A, 1B (English Medium)
GCE A/L Examination - 2A, 1B (Sinhala Medium)

Working in materials lab

Experience

Temporary Instructor

08/2025 - Present

Department of Materials Science and Engineering, University of Moratuwa

  • Facilitated practical sessions and laboratory experiments
  • Assisted academic staff with contribution for ongoing projects

R&D Department - Intern

11/2023 - 05/2024

Michelin Lanka (Pvt) Ltd - Casting Product Division

  • Experienced in Casting Manufacturing Practices and Procedures
  • Developed an automated email system to alert for out-of-specification issues in spectrometers
  • Conducted a time series analysis for BOM optimization

Extra-Curricular Activities

Extra-Curricular

Web Manager

2023, September - 2025, July

Society of Materials Engineering Students

Director of Public Relations Pillar

2022 - 2023

Mora Esports Community

Volunteer Work

International Service Director

2021 - 2022

Rotaract Club of Kandy

Treasurer

2020 - 2021

Rotaract Club of Kandy

Skills & Qualifications

Skills

Teamwork Problem-Solving Communication Skills 2D Drawings (AutoCAD) 3D Modeling (Solid Edge, Solidworks) 3D Animations (Blender) Programming (Python) Machine Learning

Qualifications

Supervised Machine Learning (Stanford Online)
Neural Networks and Deep Learning (DeepLearning.ai)
Skill Certificate - Python (HackerRank)
Lean Six Sigma Black Belt (Udemy)

Projects & Research

Fish embryo acute toxicity image analysis
Ongoing Research

Image Analysis for Fish Embryo Acute Toxicity (FET) Tests

2026 (Ongoing)

Developing an image analysis pipeline using ImageNet, ResNet, SAM, and YOLO models to analyze embryo images at 24h, 48h, and 72h. Test samples are repeated across composition ratios (1:1, 1:2, 2:1) and concentration levels (e.g., 225 ppm:225 ppm, 450 ppm:450 ppm, 900 ppm:900 ppm) to compare toxicity-induced damage and growth deviations against control experiments.

Computer Vision ImageNet/ResNet SAM YOLO
CZTS photovoltaic optimization project

Machine Learning Based Optimization of CZTS Photovoltaic Parameters

2025

Related six photovoltaic output parameters (including short-circuit current density and open-circuit voltage) with selected input variables using machine learning. Built non-linear empirical equations for each output, validated them against SCAPS-1D simulations, and derived a second-degree bandgap equation as a function of Cu, Zn, and Sn compositional ratios.

Machine Learning Photovoltaics CZTS SCAPS-1D
Automated email alert system for spectroscopy

Automated Email System

2024 (Internship)

Built an automated monitoring and alerting system for spectroscopy outputs in the Furnace Laboratory. The solution retrieves composition results directly and sends immediate email notifications to responsible departments when samples are out of specification limits.

MS Excel VBA Automation Email Alerts
Corrosion protection simulation for offshore platform

Design a Corrosion Protection System for Offshore Substation Platform

2024

Designed and evaluated multiple cathodic protection configurations for offshore substation platform legs using COMSOL Multiphysics simulations. Recommended the most suitable design based on simulation results.

COMSOL Corrosion Protection Cathodic Protection Offshore Engineering
Time-since-death estimation using diffusion model

Investigating a Diffusion-Based Approach for Time-Since-Death Estimation

2023

Developed and validated an equation for estimating post-mortem interval (PMI) using potassium ion concentration and diffusion theory. Implemented a Python program that predicts time-since-death from the required input parameters.

Forensic Modeling Diffusion Theory Python PMI Estimation

Let's Connect

Ready to collaborate on innovative materials science projects?

Email

lasithdissanayake.official@gmail.com

LinkedIn

linkedin.com/in/lasith-dissanayake

Portfolio Website

https://lasith-mse.netlify.app/