Research interests:

                                                

Coding: Python   C   C++   Matlab  

Codecs: JPEG   J2k   AVC/H.264   VVC/VTM-8.2   AVQT  

Deep learning: Pytorch   Tensorflow   keras   Image/video compression   End-to-end compression  

Extras: Unity   Online MP game developement   IoT  

2022-Sept expected Ph.D.

     🚩 Electrical and Computer Engineering, UC Davis, CA.

2020 M.Sc.

     🚩 Electrical and Computer Engineering, UC Davis, CA.

2016 B.Sc.

     🚩 Electronics and Telecommmunication, University of Moratuwa, Sri Lanka.

May 2022 - Present: PhD Intern, Apple Inc. Cupertino, CA.

• 🚩 Display and Color Team

Sept 2017 - Present: Gradute Student Researcher, University of California-Davis. Davis, CA.

• 🚩 Designed light-weight encoders for joint image compression & classification using variational auto-encoders (VAE)
• 🚩 Developed image-classification-guided ROI prediction and coding modules based on saliency maps
• 🚩 Improved rate-classification performance of image codec with hierarchical grouping based on Linear Discriminative Representations

June 2020 - Sept 2020: AI R&D Intern, InterDigital AI Labs, CA.

• 🚩 Developed a rate-multi-task end-to-end optimized framework for visual machine tasks
• 🚩 Prepared Anchor Generations for MPEG-VCM 2020

Sept 2016 - Aug 2017: Lecturer, University of Moratuwa, Sri Lanka.

• 🚩 Taught Basic Electronics and MATLAB
• 🚩 Prepared lecture notes and supervised lab sessions

Nov 2014 - March 2015: Software Engineer Intern, CodeGen Pvt. Ltd., Sri Lanka.

• 🚩 Developed a Face recognition system with 93% accuracy using Harr wavelet features for the company-use with Visual studio and OpenCV

2022: End-to-End Image Classification and Compression with variational autoencoders

Chamain, L.D., Qi, S. and Ding, Z.

IEEE Internet of Things Journal (JIoT)

2021: An End-to-End Learning Architecture for Efficient Image Encoding and Deep Learning.

Chamain, L.D., Qi, S. and Ding, Z.

European Signal Processing Conference (EUSIPCO)

2021: End-to-end optimized image compression for machines, a study.

Chamain, L.D., Racap ́e, F., B ́egaint, J., Pushparaja, A. and Feltman, S

Data Compression Conference (DCC)

2020: Improving Deep Learning Classification of JPEG2000 Images Over Bandlimited Networks.

Chamain, L.D. and Ding, Z

International Conference on Acoustics, Speech and Signal Processing (ICASSP)

2020: Eigenvalue based detection of a signal in colored noise: Finite and asymptotic analyses.

Chamain, L.D., Dharmawansa, P., Atapattu, S. and Tellambura, C.

IEEE Transactions on Information Theory

2019: Quannet: Joint image compression and classification over channels with limited bandwidth.

Chamain, L.D., Cheung, S.C.S. and Ding, Z.

IEEE International Conference on Multimedia and Expo (ICME)

2019: Detection of a signal in colored noise: A random matrix theory based analysis.

Chamain, L.D., Dharmawansa, P., Atapattu, S. and Tellambura, C.

IEEE Global Communications Conference (GLOBECOM)

2022: Learned video compression framework for multiple machine tasks

    Reuses features end-to-end optimized for a primary task for secondary tasks

2022: Learned video compression and connectors for multiple machine tasks

    Reuses features with connectors for end-to-end optimized for a primary task for secondary tasks

2019: (provisional) Quannet-Joint image compression and classification over channels with limited bandwidth.

    Learns quantization tabels for JPEG 2000

• 🥷🏿 2021-22: Served as a Reviewer for IEEE Wireless Communication Letters
• 🥷🏿 2020: Served as an Editorial Board Member of the CINEC Student Research Symposium Proceedings.
• 🚩 2019: Received Spring Travel grant, UC Davis, CA
• 🚩 2016: Awardee of Travel grant, National Science Foundation, Sri Lanka
• 🚩 2010: Awardee of C.R. Kulathilaka Memorial scholarship Award for highest Combined maths results of the country, Sri Lanka
• 🚩 2007-2015: Awardee of Dialog Merit scholarship for best results of the district.