Suren Sritharan

I am a Master's student at the Technical University of Munich, where I'm studying Computer Science with a focus on Machine Learning and Computer vision. Prior to that, I was a research assistant at the Sri Lanka Technological Campus, where I work on computer vision-related research. I also volunteered at the University of Peradeniya: COVID Research Group which focuses on combatting the issues caused by the pandemic, through AI and computer vision. I completed my Bachelor's degree at the University of Peradeniya with a B.Sc specializing in Computer Engineering. Apart from research, I am also interested in competitive programming, and I love travelling.

Throughout my undergraduate studies, I was fortunate to be advised by many fantastic researchers. Most recently, I have been working with Prof. Janaka Ekanayake and Prof. Samath Dharmaratne on the potential of AI for COVID-19 related applications. Previously, for my final year research project, I worked with Prof. Roshan Ragel, Dr. Roshan Godaliyadda, Dr. Parakrama Ekanayake, and Dr. Vijitha Herath on image quality enhancement under low/high exposure conditions. During my internship at Nokia Bell Labs, I had the privilege of working with Prof. Haris Gačanin. I have been collaborating remotely since, and I completed a project on the application of machine learning models for dynamic wireless networks.

Email  /  Github  /  Google Scholar  /  Linkedin  /  CV

• [Oct, 21] I began my Master's in Informatik at the Technical University of Munich.
• [Jun, 21] Helped organize CodeMania v2 - An introductory algorithmic programming competition for students of SLTC.
• [May, 21] Our paper on an optical physics based CNN approach for IID got accepted for ICIP, 2021.
• [Nov, 20] Our preprint on the potential of AI for COVID-19 is on medRxiv.
• [Nov, 20] Our paper on the application of machine learning models for wireless networks got accepted for IEEE Access.
• [Aug, 20] I joined Sri Lanka Technological Campus as a research assistant.
• [Jul, 20] Completed my Bachelor's degree at the Faculty of Engineering, University of Peradeniya.
• [Jun, 20] Our paper on low light image enhancement got accepted for Mercon 2020.
• [Jun, 20] Our abstract on foreground estimation in dynamic background conditions got accepted for SLTC irc, 2020.
• [Dec, 19] Represented Sri Lanka at the Seeds for the Future workshop held in China.
• [Feb, 19] I will be working at Nokia Bell Labs, Belgium as a research intern until August 2019.

I'm interested in machine learning, computer vision, and their application in other domains. Most of my current research focuses on image quality enhancement, in the presence of varying illumination and noise. Besides, I am also working on a cross-domain research in the intersection of computer vision and community medicine which focuses on quantifying the risk associated with congested areas during pandemics. Before that, I was involved in an application-oriented machine learning research for wireless communication. I have explored a broad area of research topics around machine learning and vision during my undergraduate period, and some of my publications are mentioned below.

A CNN model to solve the IID problem trained in an unspervised manner using physics-based parameters derived from an image.

Review of the use of AI techniques for spatio-temporal modeling, forecasting, and impact modeling on diverse populations as it relates to COVID-19 and its potential for future applications.

Study of the practical limitations of learning models in a dynamic wireless environment.

Low light image enhancement utilizing paired and unpaired dataset using cyclic consistency.

Foreground estimation through background cancellation in dynamic background conditions based on classical signal processing techniques in spatio-temporal domain.

Sleep apnea identification in infants through a video feed.

Credits to Jon Barron.
Last updated June 2021.