Basic facts
| First name | Julius |
|---|---|
| Family name | Ruseckas |
| Date of birth | July 13, 1978 |
| Place of birth | Vilnius, Lithuania |
| Nationality | Lithuanian |
| Citizenship | Lithuanian |
| Marital status | Married, two children |
| Languages | Lithuanian (mother tongue), Russian (good), English; German (poor) |
| Home address | Lazdynėlių 16A-43, 04126 Vilnius, Lithuania |
| Work address | Oxipit, Sunrise Valley Science and Technology Park, Saulėtekio al. 15, LT-10224 Vilnius, Lithuania |
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| Homepage | https://juliusruseckas.github.io |
Employment
| Since 2023.02.01 | Data scientist at medical imaging company Oxipit. |
|---|---|
| Since 2019 | Data science researcher at Baltic Institute of Advanced Technology (BPTI). |
| 2020.09.01- 2020.11.30 |
Data scientist at imaging company EquuSight. |
| 2018.03.01- 2018.05.15 |
Data scientist at medical imaging company Oxipit. |
| 2016-2020 | Research professor at the Institute of Theoretical Physics and Astronomy, Faculty of Physics, Vilnius University. |
| 2008-2016 | Senior Researcher at the Institute of Theoretical Physics and Astronomy, Faculty of Physics, Vilnius University. |
| 2009-2011 | Postdoctoral Fellow at the Institute of Theoretical Physics and Astronomy, Faculty of Physics, Vilnius University. |
| 2007-2008 | Researcher at the Institute of Theoretical Physics and Astronomy, Faculty of Physics, Vilnius University. |
Data Science Experience
- Computer Vision using neural networks:
- drone detection using cameras,
- ship detection in satellite photos and camera photos,
- stamp detection and classification in passport images.
- Analysis of radio signals (LTE, 5G) using neural networks.
- Application of machine learning to computer network security.
- Spiking neural networks.
Skills
- Deep knowledge of
- Programming languages: Python, C
- Machine learning libraries: PyTorch, Tensorflow, Scikit-learn, XGBoost
- Other Python libraries: Numpy, Pandas, Scipy
- Knowledge and hands-on experience with machine learning algorithms: linear regression, random forest, gradient boosted trees, neural networks, k-means
- Short experience with programming languages Julia, Fortran, Perl, Ruby
Education
| 2002-2006 | PhD studies in the Institute of Theoretical Physics and Astronomy, Faculty of Physics, Vilnius University. |
|---|---|
| 2004-2005 | Marie Curie scholarship in University of Kaiserslautern. |
| 2000-2002 |
Master studies in the
Faculty of Physics of
Vilnius University. Study program: Theoretical physics and astrophysics. |
| Since 2000 | Scientific work in the Institute of Theoretical Physics and Astronomy, Faculty of Physics, Vilnius University. |
| 1996-2000 | Bachelor studies in the Faculty of Physics of Vilnius University. |
| 1985-1996 | Vilnius “Minties” Secondary School. |
Extracurricular education
- Machine Learning by Stanford University on Coursera. Certificate earned on January 15, 2018.
- Neural Networks and Deep Learning by deeplearning.ai on Coursera. Certificate earned on December 17, 2017.
- Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization by deeplearning.ai on Coursera. Certificate earned on December 20, 2017.
- Structuring Machine Learning Projects by deeplearning.ai on Coursera. Certificate earned on December 24, 2017.
- Convolutional Neural Networks by deeplearning.ai on Coursera. Certificate earned on December 30, 2017.
- Sequence Models by deeplearning.ai on Coursera. Certificate earned on February 8, 2018.
- Deep Learning, a 5-course specialization by deeplearning.ai on Coursera. Specialization Certificate earned on February 8, 2018.
- Natural Language Processing with Classification and Vector Spaces by deeplearning.ai on Coursera. Certificate earned on September 27, 2020.
- Natural Language Processing with Probabilistic Models by deeplearning.ai on Coursera. Certificate earned on October 6, 2020.
- Natural Language Processing with Sequence Models by deeplearning.ai on Coursera. Certificate earned on October 10, 2020.
- Natural Language Processing with Attention Models by deeplearning.ai on Coursera. Certificate earned on October 19, 2020.
- Natural Language Processing, a 4-course specialization by deeplearning.ai on Coursera. Specialization Certificate earned on October 19, 2020.
- Build Basic Generative Adversarial Networks (GANs) by deeplearning.ai on Coursera. Certificate earned on October 26, 2020.
- Build Better Generative Adversarial Networks (GANs) by deeplearning.ai on Coursera. Certificate earned on November 10, 2020.
- Apply Generative Adversarial Networks (GANs) by deeplearning.ai on Coursera. Certificate earned on November 22, 2020.
- Generative Adversarial Networks (GANs), a 3-course specialization by deeplearning.ai on Coursera. Specialization Certificate earned on November 22, 2020.
Prizes and Awards
| 2018 | Adolfas Jucys Prize for Theoretical Physics of the Lithuanian Academy of Sciences |
|---|---|
| 2010 | Vilnius University Rector's award for young scientist |
| 2008 | Lithuanian State Prize |
| 2007 | Lithuanian Society of Young Researchers award for the best PhD thesis in 2006 |
| 2002 | Lithuanian Academy of Science award for the best student research work |
| 1996 | Participation in the International Olympiad of Junior Physicists. Honorary Diploma |
Research Projects
Research Project Quantum and Nonlinear Optics with Rydberg-State Atoms (2016-2018) supported by the Lithuanian Research Council (Lithuanian-Latvian-Taiwan scientific collaboration programme). Project leader – J. Ruseckas.
Supervision of Postdoctoral Fellowships
- Postdoctoral Fellowship by Dr. Hamid Reza Hamedi Light-matter interaction next to plasmonic nanostructures, supported by the Lithuanian Research Council and supervised by J. Ruseckas, 2022-2024.
- Postdoctoral Fellowship by Dr. Aleksejus Kononovičius Physical modeling of order-book and opinion dynamics, supported by the Lithuanian Research Council and supervised by J. Ruseckas, 2017-2020.
Supervision of PhD Students
Rytis Kazakevičius PhD studies Complex non-linear systems affected by colored and non-Gaussian noise, supervised by J. Ruseckas, 2013-2017.
Supervision of Master Students
- Diploma work by Lina Saveikytė Propagation of light in the medium of ultra-cold atomic gasses, supervised by J. Ruseckas, 2018.
- Diploma work by Georgij Bagašvili Creation of very narrow potential barriers for ultra-cold atoms using light-induced gauge potentials, supervised by J. Ruseckas, 2015.
Plenary and Invited Talks at International Conferences
- Invited talk at the conference Synthetic Topological Quantum Matter, (Beijing, People's Republic of China, 1-8 August 2016).
- Plenary talk at the conference International Conference on Statistical Physics SigmaPhi 2014, (Rhodes, Greece, 7-11 July 2014).
- Invited talk at the conference 3rd International Workshop on Statistical Mechanics and Dynamical Systems (Turunç/Marmaris, Turkey, 27 August - 2 September 2012).
- Invited talk at the conference International Workshop on Quantum Gases in Synthetic Gauge Fields (Tsinghua university, Beijing, People's Republic of China, 23-28 August 2010).
Expert Activities
Refereeing of the manuscript submitted to the journals indexed in Web of Science
- Physical Review Letters
- Physical Review A
- Scientific Reports
- EPL
- Physica A
- Journal of Physics B
- European Physical Journal D
- Optics Communications
- Physics Letters A
- PLOS One
Participation in the Defence Committees
- Member of the PhD Defence Committee by Artyom Plyushch (2018, Vilnius University, supervisor dr. Jan Macutkevič).
- Member of the PhD Defence Committee by Vladimir Chorošajev (2017, Vilnius University, supervisor prof. Darius Abramavičius).