Introduce myself - Lakitha Omal Harindha Wijeratne
I am a doctoral graduate student at the department of Physics working with Prof. David Lary. I currently perform experiments to calibrate environmental sensors using Big Data and Machine Learning Algorithms. Most of my time is spent on designing and building such sensor systems. As these sensor systems are currently being deployed within the DFW metroplex, I am focusing on studying and modelling air pollution using the data collected.
Our research group under Prof. Lary is evolved around Multi-scale Integrated Sensing and Simulation (MINTS) which is a multidisciplinary platform developing intelligent sensing systems. MINTS initiative is designed to provide commanders, environment officers, intelligence officers, physicians and the general public with actionable insights and situational awareness using data gained from multiple spatial and temporal data packages. And as a member I follow the same merits of public service and public awareness.
Experience with HPC
My experience with HPC is quite limited and I am hoping TRECIS will help me develop the skills to streamline, and enhance some of the systems I mentioned above using HPC.
My Workflow
Currently I am in the process of calibrating sensor systems developed at UTD using recommended reference sensors. Most of my code is written in matlab and some aspects of the code is in Python such as file monitoring. Typically I run my code on a local machine using a smaller ratio of data and once the code is tested I port it to a much more resourceful machine that can handle heavy data loads.
Challenge
Most of our target outputs (such as pm2.5) of our algorithms are heavily dependent on climate data such as temperature and pressure. And as such it’s essential we calibrate for at least 6 months (to cover for both Summer and Winter climate conditions). This meant that we had to develop a system which evolves over time. My current challenge is to design a system that can push out up to date calibrated data which evolves over time using Gaussian Process Regression (GPR) with Matlab.