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About
Sachini Herath
I am a PhD student in School of Computing Science at Simon Fraser University supervised by Prof. Yasutaka Furukawa. My research interests lie in Computer Vision, Machine Learning and Robotics, with a particular focus on indoor localization and tracking via multi-modal data fusion. During my PhD, I have done research internships at Facebook Reality Labs, Apple (TDG) and Samsung Research (SAIC-Montreal).
I obtained MSc in Computing Science from Simon Fraser University supervised by Prof. Furukawa and BSc in Computer Science and Engineering from University of Moratuwa.
- Google Scholar
- GitHub
- sherath-atmark-sfu .ca
- sachini.mc-atmark-gmail.com
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General chair of Women in Computer Vision (WiCV) workshop at CVPR 2024
June. 2024 Seattle, USA
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Co-organizing Women in Computer Vision (WiCV) workshop at CVPR 2023
June. 2023 Vancouver, Canada
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Poster presentation at 2023 CRA-W Grad Cohort for Women
April 2023 San Francisco, CA
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Technology Investigation Intern
Jan. 2023- April 2023
Apple Technology Development GroupSunnyvale, CA
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Presented my Research at ACM CAN-CWiC 2022
October 2022 Toronto, ON
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Presented NILoc at CVPR 2022
October 2022 Toronto, ON
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Talent Bursary Recipient for Amii AI week 2022
May 2022 Edmonton, Alberta
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Started PhD in Computing Science
Jan. 2020 - Present
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Completed M.Sc. in Computing Science
Jan. 2018- Nov. 2019
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Graduate Research Assistant
May. 2018- Dec 2019
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Attended ICCV 2019
Sept. 2019 Seoul, South Korea
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Project Mentor: Invent the Future (AI4ALL - SFU) - Robotics and Sensing team.
July 2019 website
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Workshop Leader in Try/Catch 2019, Data Science Workshop.
May 2019 website
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Attended 2019 CRA-W Grad Cohort for Women
April 2019 Chicago, USA
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Program Mentor: Invent the Future (AI4ALL - SFU)
July 2018
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Attended CVPR 2018
June. 2018 Salt Lake City, USA
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Lecturer (In Contract)
Oct. 2016- Dec 2017
Department of Computer Science and Engineering, University of Moratuwa. -
Junior Consultant
Apr. 2016- Sept. 2016
Department of Computer Science and Engineering, University of Moratuwa. -
Co-Founder of PreviewVR
Apr. 2016- Dec. 2016
Startup focusing on content generation for VR applications . -
Completed B.Sc.(Hons) in Computer Science and Engineering
2011-2016
First Class Honours
Dean's list in all semesters
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Google Summer of Code Intern at Drupal CMS.
2014 project: Linked Data Tool
Tool connecting Drupal8 with Linked Data Sources and CKEditor plugin for inline content mappingMentor: Stéphane Corlosquet
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Attended 5th South-asia workshop on research frontiers organized by School of Computing, NUS.
May. 2015 Singapore website
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Co-Founder of Audinary
2014-2015
Startup with a video based language learning platform -
Software Engineering intern at Adroitlogic Pvt. Ltd.
Oct. 2014-Apr. 2015 website
Awarded Migara Ranatunga Trust Award for University Undergraduates for Industrial Training Projects 2015/2016 by the Institute of Engineers, Sri Lanka. -
Google Summer of Code Intern at Drupal CMS.
2014 project: RDF UI
Module to allow Drupal content structure to be mapped and annotated with Schema.org vocabulary seamlesslyMentor: Stéphane Corlosquet
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Completed GCE Advanced Level in Physical Science Stream
1997-2010
Musaeus CollegeNational Rank : 8
Musaeus College: Best University Entrant 2010
Musaeus College: Marie Musaeus Higgins Award for Outstanding performance in Physical Science Stream-2010
Research
Research
Neural Inertial Localization
This paper proposes the inertial localization problem, the task of estimating the absolute location from a sequence of inertial sensor measurements. We developed a solution, dubbed neural inertial localization NILoc which 1) uses a neural inertial navigation technique to turn inertial sensor history to a sequence of velocity vectors; then 2) employs a transformer-based neural architecture to find the device location from the sequence of velocities.
Publications:
- Neural Inertial Localization arXiv/CVPR 2022
Authors: Sachini Herath, David Caruso, Chen Liu, Yufan Chen, Yasutaka Furukawa
Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments
The paper proposes a multi-modal sensor fusion algorithm that fuses WiFi, IMU, and floorplan information to infer an accurate and dense location history in indoor environments. The algorithm uses 1) an inertial navigation algorithm to estimate a relative motion trajectory from IMU sensor data; 2) a WiFi-based localization API in industry to obtain positional constraints and geo-localize the trajectory; and 3) a convolutional neural network to refine the location history to be consistent with the floorplan.
Publications:
- Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments arXiv/ICRA 2021
Authors: Sachini Herath, Saghar Irandoust, Bowen Chen, Yiming Qian, Pyojin Kim, Yasutaka Furukawa
RoNIN: Robust Neural Inertial Navigation in the Wild
MSc. Thesis Research Project. [Website] [Code]
The research focus on data-driven inertial navigation, where the task is the estimation of positions and orientations of a moving subject from a sequence of IMU sensor measurements. We present 1) a new benchmark of IMU sensor data and ground-truth 3D trajectories under natural human motions; 2) neural inertial navigation architectures, making significant improvements for challenging motion cases; and 3) comprehensive evaluations of the competing methods and datasets.
Publications:
- RoNIN: Robust Neural Inertial Navigation in the Wild: Benchmark, Evaluations, and New Methods. arXiv/ICRA 2020
Authors: Hang Yan*, Sachini Herath*, Prof. Yasutaka Furukawa (* indicates equal contribution)
Virtual Reality Content Generation and Rendering Framework
Final year capstone project for BSc. Engineering degree. [Blog]
A content generation and rendering framework for freely navigable virtual reality environments. The environment was created using photospheres and intermediate views were generated using features from neighbouring images. Segway inspired gesture based input system was introduced for navigation.
Publications:
- Quantitative and qualitative evaluation of performance and robustness of image stitching algorithms. In International Conference on Digital Image Computing: Techniques and Applications (DICTA) IEEE. (2015)
- Real-time Gesture Prediction Using Mobile Sensor Data for VR Applications, International Journal of Machine Learning and Computing,6(3). INSPEC (2016)
- Generation of intermediate viewpoints for scalable adaptation of real world environments for virtual reality. In IEEE International Conferenceon Industrial and Information Systems (ICIIS). IEEE (2017)
- Unconstrained Segue Navigation for an Immersive Virtual Reality Experience. ENGINEER, 50(04). (2017)
Authors: Sachini Herath, Vipula Dissanayake, Sanka Rasnayaka, Sachith Seneviratne, Rajith Vidanaarachchi, Dr. Chandana Gamage
Other Publications
- Qian, Y., Yan, H., Herath, S., Kim, P., and Furukawa, Y., 2022, Single User WiFi Structure from Motion in the Wild, ICRA 2022.
- Rasoulidanesh, M., Yadav, S., Herath, S., Vaghei, Y., Payandeh, S., 2019. Deep Attention Models for Human Tracking Using RGBD. Sensors 19(4).
- Dissanayake, D., Perera, T., Elladeniya, C., Dissanayake, K., Herath, S. and Perera, I., 2018. Identifying the Learning Style of Students in MOOCs Using Video Interactions, International Journal of Information and Education Technology vol. 8, no. 3.
- Hewawalpita, Herath, S., S., Perera, I. and Meedeniya, D., 2018 Effective Learning Content Offering in MOOCs with Virtual Reality-An Exploratory Study on Learner Experience. Journal of Universal Computer Science, 24(2).
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