Dr. Kārlis Freivalds is a senior researcher at the Institute of Electronics and Computer Science. He has graduated from the University of Latvia (Riga, Latvia) where he obtained a doctoral degree in computer science. Kārlis is the author of 30+ scientific publications and 7 patent applications. He has been involved in various scientific and industrial projects in the areas of computer vision, artificial intelligence, graph algorithms, bioinformatics and quantum computing, where he has led research work as well as software development and deployment in production. The main areas of research are artificial intelligence, computer vision, robotics and machine learning, with a recent focus on deep neural networks, where he has developed several new neural network architectures for fast sequence processing, algorithmic tasks and NP-hard problem solving. He is also an assistant professor at the Faculty of Computer Science of the University of Latvia, where he teaches programming of image processing and computer vision algorithms.
Related publications:
- Teikmanis, O., Leja, L., & Freivalds, K. Applying a Differentiable Physics Simulation to Move Objects with Fluid Streams. (2023). International Workshop on Embedded Digital Intelligence (IWoEDI’2023).
- E. Ozolins, K. Freivalds, A. Draguns, E. Gaile, R. Zakovskis, S. Kozlovics “Goal-aware neural SAT solver” 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, IEEE. https://ieeexplore.ieee.org/document/9892733
- Gatis Melkus, Karlis Cerans, Karlis Freivalds, Lelde Lace, Darta Zajakina, Juris Viksna “Analysis of Dynamics and Stability of Hybrid System Models of Gene Regulatory Networks.” The 12th International Conference on Computational Systems-Biology and Bioinformatics. 2021.
- Draguns, A., Ozoliņš, E., Šostaks, A., Apinis, M., & Freivalds, K. (2021). Residual Shuffle-Exchange Networks for Fast Processing of Long Sequences. Proceedings of the AAAI Conference on Artificial Intelligence, 35(8), 7245-7253. https://ojs.aaai.org/index.php/AAAI/article/view/16890
- Ozolinš, K. Freivalds and A. Šostaks, “Matrix Shuffle- Exchange Networks for Hard 2D Tasks,” 2021 International Joint Conference on Neural Networks (IJCNN), 2021, pp. 1-8, doi:10.1109/IJCNN52387.2021.9533919. https://ieeexplore.ieee.org/document/9533919/
- Barzine, M.P., Freivalds, K., Wright, J.C., Opmanis, M., Rituma, D., Ghavidel, F.Z., Jarnuczak, A.F., Celms, E., Čerāns, K., Jonassen, I. and Lace, L., 2020. Using Deep Learning to Extrapolate Protein Expression Measurements. Proteomics, 20(21-22), p.2000009.
- Kārlis Freivalds, Emīls Ozoliņš, and Agris Šostaks. “Neural Shuffle-Exchange Networks-Sequence Processing in O (n log n) Time.” In Advances in Neural Information Processing Systems, pp. 6626-6637. 2019.
- Karlis Martins Briedis, Karlis Freivalds. On-line Television Stream Classification by Genre. Baltic Jornal of.Modern Computing, Vol. 6 (2018), No. 3, pp. 235–246.
- Karlis Freivalds, Renars Liepins. “Improving the Neural GPU Architecture for Algorithm Learning.” The ICML workshop Neural Abstract Machines & Program Induction v2 (NAMPI 2018)
- Arturs Sprogis, Karlis Freivalds, and Elita Cirule. “Implementing a Face Recognition System for Media Companies.” In International Baltic Conference on Databases and Information Systems, pp. 328-341. Springer, Cham, 2018.
- Jans Glagoļevs, Kārlis Freivalds “Logo Detection in Images Using HOG and SIFT”, 5th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE), Riga, Latvia, 2017, pp. 1-5.
- Kārlis Freivalds, Jans Glagoļevs “A Statistical Method for Object Counting”. Proceedings of 2017 International Conference on Digital Signal Processing (ICDSP 2017) Kuala Lumpur, Malaysia
- Jevgenijs Vihrovs, Krišjānis Prūsis, Kārlis Freivalds, Pēteris Ručevskis and Valdis Krebs “A Potential Field Function for Overlapping Point Set and Graph Cluster Visualization.” International Joint Conference on Computer Vision, Imaging and Computer Graphics (pp. 136-152). Springer, 2015
- Kārlis Freivalds, Jans Glagoļevs. “Graph Compact Orthogonal Layout Algorithm.” 3rd International Symposium on Combinatorial Optimization, ISCO 2014, Springer LNCS Volume 8596, pp 255-266.
Related patents:
EP3136607A1 K.Freivalds, J.Vīksna, M.Grasmanis, E.Celms “A method and system for encoding and decoding of suffix tree and searching within encoded suffix tree”, 2015.
US8542234B2. Brendan Madden, Karlis Freivalds, Francois Bertault, Uli Foessmeier, “SYSTEM FOR ARRANGING A PLURALITY OF RELATIONAL NODES INTO GRAPHICAL LAYOUT FORM”, 24.09.2013.
Recent projects
- Smart Materials, Photonics, Technologies, and Engineering Ecosystem (MOTE) #VPP
- Artificial Intelligence in Manufacturing leading to Sustainability and Industry 5.0 (AIMS5.0) #ChipsJU
- Digitalization of Power Electronic Applications within Key Technology Value Chains (PowerizeD) #ChipsJU
Recent publications
- Karlis Freivalds, Sergejs Kozlovičs. Denoising Diffusion for Sampling SAT Solutions
- Oskars Vismanis, Janis Arents, Karlis Freivalds, Vaibhav Ahluwalia and Kaspars Ozols. 2023. "Robotic System for Post Office Package Handling" Applied Sciences 13(13 - Number) 7643 (Article Number), https://www.mdpi.com/2076-3417/13/13/7643
- Elīza Gaile, Andis Draguns, Emīls Ozoliņš, Kārlis Freivalds. Unsupervised Training for Neural TSP Solver
- Zakovskis, R., Draguns, A., Gaile, E., Ozolins, E., Freivalds, K. (2023). Gates Are Not What You Need in RNNs. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2023. Lecture Notes in Computer Science(), vol 14125. Springer, Cham. https://doi.org/10.1007/978-3-031-42505-9_27
- Kārlis Freivalds, Emīls Ozoliņš, Guntis Bārzdiņš. "Discrete Denoising Diffusion Approach to Integer Factorization" Proceedings of 32nd International Conference on Artificial Neural Networks 2023 , Lecture Notes in Computer Science (LNCS, volume 14254) Part I, pp. 123-134
- Kārlis Freivalds, Laura Leja, Oskars Teikmanis, "Learning to Move Objects with Fluid Streams in a Differentiable Simulation", ROBOT 2024 7th Iberian Robotics Conference, IEEE,
- Laura Leja, Oskars Teikmanis, Kārlis Freivalds, 2024. "Shaping Flames with Differentiable Physics Simulations" "Machine Learning and the Physical Sciences" , NeurIPS 2024
- Kārlis Freivalds, Oskars Teikmanis, Laura Leja, Rodions Saltanovs, Ralfs Āboliņš, "Learning Fluid-Directed Rigid Body Control", "Machine Learning and the Physical Sciences" at NeurIPS 2024
- Laksis Dans, Tatarinovs Aleksejs, Freivalds Kārlis “Wavelet transform based decomposition of ultrasound signals for cortical bone model evaluation” EUSIPCO 2024 32nd EUROPEAN SIGNAL PROCESSING CONFERENCE, August 26-30, 2024. LYON, FRANCE. https://eurasip.org/Proceedings/Eusipco/Eusipco2024/pdfs/0001496.pdf ISBN: 978-9-4645-9361-7