About

Hi there! My name is Dovydas. I’m a PhD candidate at University College London (UCL), where I investigate machine learning hardware. Outside university, I tutor GCSE, A-level, and IBDP students in mathematics and physics. Also, I’ve recently founded a startup aimed at developing intelligent diagnostic tools that aid students’ learning—drop me an email if you’d like to try it!

Find Me

Education

PhD in Electronic Engineering (2018–Present, UCL)

I investigate how to make machine learning faster and more power-efficient. Artificial neural networks, which are incredibly popular in machine learning, have achieved amazing results over the last decade. However, conventional computers, which separate memory and computing units, are not well suited to the computations that neural networks perform. As a result, a lot of time and energy is wasted. One of the suggested alternatives is an emerging technology—memristor-based hardware. Although vastly more efficient, memristor-based implementations, compared to traditional digital computers, exhibit more variability. This could present problems.

I use experimental data and simulations to

I explain the rationale behind the research in less technical terms in the following posts:

Publications

  • D. Joksas, E. Wang, N. Barmpatsalos, W. H. Ng, A. J. Kenyon, G. A. Constantinides, and A. Mehonic, “Nonideality-aware training for accurate and robust low-power memristive neural networks,” Advanced Science, p. 2105784, 2022. doi:10.1002/advs.202105784
  • D. Joksas and A. Mehonic, “badcrossbar: A Python tool for computing and plotting currents and voltages in passive crossbar arrays,” SoftwareX, vol. 12, p. 100617, 2020. doi:10.1016/j.softx.2020.100617
  • D. Joksas, P. Freitas, Z. Chai, W. H. Ng, M. Buckwell, C. Li, W. D. Zhang, Q. Xia, A. J. Kenyon, and A. Mehonic, “Committee machines—a universal method to deal with non-idealities in memristor-based neural networks,” Nature Communications, vol. 11, no. 1, 2020. doi:10.1038/s41467-020-18098-0
  • A. Mehonic, D. Joksas, W. H. Ng, M. Buckwell, and A. J. Kenyon, “Simulation of inference accuracy using realistic RRAM devices,” Frontiers in Neuroscience, vol. 13, p. 593, 2019. doi:10.3389/fnins.2019.00593

Patent applications

  • A. Mehonic, D. Joksas, and A. Kenyon, “Physical implementation of artificial neural networks,” International Patent Application, PCT/GB2020/052166, 9 Sep. 2020.

BEng Electronic Engineering (2015–2018, UCL)

The modules that I found the most intellectually rewarding were Photonics and Communication Systems (ELEC215P), Control Systems I (ELEC3003), Numerical Methods (ELEC3030), Quantum Physics (PHAS2222), and Atomic and Molecular Physics (PHAS2224).

Publications

  • A. J. Kenyon, M. S. Munde, W. H. Ng, M. Buckwell, D. Joksas, and A. Mehonic, “The interplay between structure and function in redox-based resistance switching,” Faraday Discussions, vol. 213, pp. 151–163, 2019. doi:10.1039/C8FD00118A

Erdős Number

4

Favorite…

Movies

  1. Interstellar [2014] (YOU CAN MAKE FUN OF ME, I DON’T CARE)
  2. Once Upon a Time in the West [1968]
  3. There Will Be Blood [2007]
  4. The Truman Show [1998]
  5. Taxi Driver [1976]
  6. Trainspotting [1996]
  7. American Beauty [1999]
  8. Boogie Nights [1997]
  9. Full Metal Jacket [1987]
  10. Blue Velvet [1986]
  11. Back to the Future [1985]
  12. Reservoir Dogs [1992]
  13. The Prestige [2006]
  14. A Clockwork Orange [1971]
  15. La piel que habito [2011]
  16. The King of Comedy [1982]
  17. Barry Lyndon [1975]
  18. Goodfellas [1990]
  19. The Florida Project [2017]
  20. Moneyball [2011]

Songs (performances)

  1. Strawberry Fields Forever [The Beatles, 1967]
  2. Mr. Sandman [The Chordettes, 1954]
  3. Red Light Spells Danger [Billy Ocean, 1976]
  4. Stop! In the Name of Love [The Supremes, 1965]
  5. Lah-Di-Dah [Jake Thackray, 1991]
  6. Happens to the Heart [Leonard Cohen, 2019 (2016)]
  7. Hurricane [Bob Dylan, 1976]
  8. Eloise [Barry Ryan, 1968]
  9. Heroes and Villains [The Beach Boys, 1967]
  10. People Are People [Depeche Mode, 1984]
  11. 50 Ways to Leave Your Lover [Paul Simon, 1975]
  12. Ain’t No Mountain High Enough [Diana Ross, 1970]
  13. First We Take Manhattan [Leonard Cohen, 1986]
  14. Mr. Blue Sky [Electric Light Orchestra, 1977]
  15. Island in the Sun [Harry Belafonte, 1957]
  16. Paint It, Black [The Rolling Stones, 1966]
  17. War [Edwin Starr, 1970]
  18. She’s a Rainbow [The Rolling Stones, 1967]
  19. Starman [David Bowie, 1972]
  20. Bang Bang (My Baby Shot Me Down) [Nancy Sinatra, 1966]

Prime

57