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. I'm also working as a working student at AstraZeneca Computation Pathology on the image analysis of tumor cells in relating computer vision metrics with optical density measurements. Prior to that, I was working as a working student at TUM, first in the Providentia++ project at the chair of Robotics, Artificial Intelligence and Embedded Systems, and then at the chair of Data Analytics and Machine Learning. I completed my Bachelor's degree at the University of Peradeniya with a B.Sc specializing in Computer Engineering.

Throughout my undergraduate studies, I was fortunate to be advised by many fantastic researchers. Soon after my bachelors, I had the opportunity to work 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 on the application of machine learning models for dynamic wireless networks.

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profile photo
  • [Apr, 23] I joined AstraZeneca Computational Pathology as a working student.
  • [Oct, 22] I joined the DAML lab at TUM as a working student.
  • [Dec, 21] I joined the Providentia++ as a working student
  • [Oct, 21] I began my Master's in Informatik at the Technical University of Munich.
  • [May, 21] Our paper on an optical physics based CNN approach for IID got accepted for ICIP, 2021.

My main research focus is in the intersection of machine learning, computer vision, and their application in other domains. I'm currently conducting research on the use of Cross Modal Transformers for 3D object detection for autonomous driving tasks. In addition, I've also been working on image analysis on tumour cells at AstraZeneca Computational Pathology Munich. I have explored a broad area of research topics around machine learning and machine perception, and some of my projects and publications are listed below.

cmtcoop CMTCoop : Cooperative Perception for 3D object detection through Cross Modal Transformers

Proposed CMTCoop : A deep multi-model multi-view feature fusion model based on cross modal Transformers for 3D object detection. Model runs at near-real time FPS, and improves mAP over the current SoTA.

baam Template-free 3D Vehicular Shape Reconstruction

Semi-supervised / self-supervised learning methodology for 3D vehicular shape reconstruction based on BAAM, to pave the way for unsupervised techniques.

mdpi Holistic Interpretation of Public Scenes Using Computer Vision and Temporal Graphs to Identify Social Distancing Violations
Gihan Jayatilaka, Jameel Hassan, Suren Sritharan, Janith Bandara Senanayaka, Harshana Weligampola, Roshan Godaliyadda, Parakrama Ekanayake, Vijitha Herath, Janaka Ekanayake, Samath Dharmaratne
Applied Sciences, 2022

Asses the COVID-spreading risk levels from CCTV camera videos based on social distance measure, contact detection, mask identification, and temporal graph network to develop spread mitigation strategies for different environments.

iid An Optical Physics inspired CNN approach for Intrinsic Image Decomposition
Harshana Weligampola, Gihan Jayatilaka, Suren Sritharan, Parakrama Ekanayake, Roshan Ragel, Vijitha Herath Roshan Godaliyadda,
IEEE International Conference on Image Processing (ICIP), 2021

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

ga_b5g Use of Artificial Intelligence on spatio-temporal data to generate insights during COVID-19 pandemic: A Review
Gihan Jayatilaka, Jameel Hassan, Umar Marikkar, Rumali Perera, Suren Sritharan, Harshana Weligampola, Mevan Ekanayake, Roshan Godaliyadda, Parakrama Ekanayake, Vijitha Herath, Dilshan Godaliyadda, Anuruddhika Rathnayake, Samath D. Dharmaratne, Janaka Ekanayake
medRxiv, 2020

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.

ga_b5g A Study on Deep Learning for Latency Constraint Applications in Beyond 5G Wireless Systems
Suren Sritharan, Harshana Weligampola, Haris Gačanin
IEEE Access, 2020

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

A Retinex Based GAN Pipeline to Utilize Paired and Unpaired Datasets for Enhancing Low Light Images
Harshana Weligampola, Gihan Jayatilaka, Suren Sritharan, Roshan Godaliyadda, Parakrama Ekanayake, Roshan Ragel, Vijitha Herath
Moratuwa Engineering Research Conference (MERCon), 2020

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

Generalizing Foreground Estimation Algorithms in Dynamic Background Conditions [ABSTRACT]
Gihan Jayatilaka*, Suren Sritharan*, Harshana Weligampola*, Dhammika Elkaduwe, Roshan Godaliyadda, Parakrama Ekanayake, Vijitha Herath Nalin Harishchandra
Sri Lanka Technological Campus International Research Conference (SLTC irc), 2020
abstract / github

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

Non-contact Infant Sleep Apnea Detection
Gihan Jayatilaka*, Harshana Weligampola*, Suren Sritharan*, Pankayaraj Pathmanathan, Roshan Ragel, Isuru Nawinne
IEEE International Conference on Industrial and Information Systems (ICIIS), 2019
preprint / github

Sleep apnea identification in infants through a video feed.

Teaching Experience
SLTC Teaching assistant @ SLTC.
Programming fundamentals (ECS100), 2020.
Internet Technologies (CCS112), 2020.
Communication Protocols (CCS201), 2021.
Programming Fundamentals with Python (ICCO2301), 2021.
UOP Volunteer Instructor @ UOP
Logic Networks (CO221), 2020.
Computer architecture (CO224), 2020.
coders_v8 Problem setter, ACES Coders v8.0, 2020
Check out the problem here
The solutions are available here
codemania_v2 Problem setter, CodeMania v2, 2021
An introductory algorithmic programming competiton for the students of SLTC.
Check out the problems on Hackerrank or Github
My preparatory webinar on algorithmic programming is on youtube

Credits to Jon Barron.
Last updated Jan 2024.