Sudeera Gunathilaka

Logo

View My GitHub Profile

Doctoral candidate @ the Tokyo Institute of Technology

Technical Skills: C, C++, Python, MATLAB, Julia, Git, CUDA

Interests: Unconventional Computing Architectures, Optimisation algorithms, Parallel / Quantum Computing, Deep / Machine learning, Compressed Sensing

Google Scholar | ORCID | Researchgate | Twitter | TokyoTech Blog
Languages: Sinhala (Native), English (Fluent), Japanese (Fluent)


Education


Work Experience

Research intern at NTT Research Physics and Informatics Laboratories

Term 1 - (June 2021 - August 2021)

Term 2 - (July 2023 - Present)

Intern @ Jij Inc. (February 2022 - March 2022)

Research Assistant @ Tokyo Institute of Technology (November 2020 - December 2021)

Student Assistant @ Shonan Institute of Technology (April 2019 - March 2020)


Scholarships


Projects

Coherent Ising machines with artificial Zeeman terms

Publication 1 Publication 2

TBA

Amplitude evolution CAC results

Coherent Compressed Sensor

Publication

TBA

MRI reconstruction

Two-Phase Quasi-Newton method with Momentum

Publication

TBA

NAQ algorithm


Talks & Posters


Publications

  1. Gunathilaka, M.D.S.H., Inui Y, Kako S, Yamamoto Y, Aonishi T. Mean-field coherent Ising machines with artificial Zeeman terms. Journal of Applied Physics. 2023;134(23):234901. [Journal of Applied Physics - IF: 2.877].
  2. Gunathilaka, M.D.S.H., Kako, S., Inui, Y. et al. Effective implementation of l0-regularised compressed sensing with chaotic-amplitude-controlled coherent Ising machines. Sci Rep 13, 16140 (2023). [Nature Scientific Reports - IF: 4.997].
  3. Inui, Y., Gunathilaka, M.D.S.H., Kako, S. et al. Control of amplitude homogeneity in coherent Ising machines with artificial Zeeman terms. Commun Phys 5, 154 (2022). [Nature Communications Physics - IF: 6.497].
  4. M. D. S. H. Gunathilaka, Mahboubi S and Ninomiya H, “Acceleration Technique of Two-Phase Quasi-Newton Method with Momentum for Optimization Problems” [2020] Thinkmind.org 59.

Positions


Awards