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Dr. Linas Stripinis

Department: Blockchain and Quantum Technologies Group
Position: Researcher, Project Senior Researcher

Address: Akademijos st. 4, Vilnius
E-mail:  

 Professional social profiles: researchgate  linked in  google  orcid og images  blue white shadow  

 

 

Scientific and pedagogical background

Education

  • 2009-2014 - Lithuanian University of Educational Sciences (Bachelor of Mathematics and Informatics)
  • 2014-2016 - Lithuanian University of Educational Sciences (Master of Mathematics)
  • 2016-2020 - Vilnius University Institute of Data Science and Digital Technologies (Ph.D. in Informatics)
  • In 25 February 2021 was awarded a doctoral degree by Vilnius University in the field of Informatics for the work "Improvement, development and implementation of derivative-free global optimization algorithms”. Scientific supervisor: Prof. Dr. Remigijus Paulavičius

 

Research Interests

  • Global optimization
  • Optimization methods and their implementation
  • Parallel computing
  • Numerical analysis 
  • Statistical data analysis
  • Machine learning

 

Scientific Conferences

Presentations Delivered:

  1. 2022: 13th International workshop on Data Analysis Methods for Software Systems (DAMSS), December 1-3, Druskininkai, Lithuania. A New Genetic Tourist Trip Design Algorithm for a Highly Personalised Globe-trot Traveling Experience.
  2. 2021: 31st European Conference on Operational Reaserch - Euro 2021, July 11-14, Athens, Greece. DGO: A DIRECT-type MATLAB Toolbox for Derivativefree Global Optimization.
  3. 2021: World Congress on Global Optimization - WCGO 2021, July 7-10, Athens, Greece. Implementation of the first DIRECT-type toolbox (DGO) and an extensive experimental study of DGO and various partitioning and selection techniques.
  4. 2019: The International EURO mini Conference Modelling and Simulation of Social-Behavioural Phenomena in Creative Societies, September 18–20, Vilnius, Lithuania. Importance of optimization techniques for the social sciences.
  5. 2018: 10th International workshop on Data Analysis Methods for Software Systems (DAMSS), November 29 – December 1, Druskininkai, Lithuania. Improved DIRECT-type algorithms for generally constrained global optimization problems
  6. 2018: 16th EUROPT Workshop on Advances in Continuous Optimization, July 12-13, Almeria, Spain. Improved DIRECT-type algorithm for constrained globalo ptimization problems.
  7. 2017: 9th International workshop on Data Analysis Methods for Software Systems (DAMSS), November 30 - December 2, Druskininkai, Lithuania. Improved DIRECT-type algorithms for generally constrained global optimization problems.

 

Co-authored Presentations:

  1. 2024: Genetic and Evolutionary Computation Conference Companion, GECCO '24 Companion, July 14-18, Melbourne, VIC, Australia. Hot Off the Press: Benchmarking Derivative-Free Global Optimization Algorithms under Limited Dimensions and Large Evaluation Budgets.
  2. 2023: Numerical Computations: Theory and Algorithms NUMTA 2023, 101, June 14-20, Calabria, Italy. Towards Reproducible Research in AI via Blockchain.
  3. 2017: 15th EUROPT Workshop on Advances in Continuous Optimization, July 12-14, Montreal, Canada. DIRECT-type algorithms for constrained global optimization.

 

Doctoral conferences:

  1. Annual Reporting Doctoral Conference of Informatics, October 22, 2020 Vilnius „Improvement, development and implementation of derivative-free global optimization algorithms“ (Slides)
  2. Annual Reporting Doctoral Conference of Informatics, October 30, 2019, „Vilnius „Improvement, development and implementation of derivative-free global optimization algorithms“ (Technical Report, Slides)
  3. Annual Reporting Doctoral Conference of Informatics, October 24, 2018, „Vilnius „„Improvement, development and implementation of derivative-free global optimization algorithms“ (Technical Report, Slides)
  4. Annual Reporting Doctoral Conference of Informatics, October 17, 2017,  „Improvement, development and implementation of derivative-free global optimization algorithms“ (Technical Report, Slides)

 

Scientific publications

Peer-reviewed journal publications with citation index (Impact Factor), indexed by CA WoS DB:

  1. L. Stripinis, J. Kůdela, R. Paulavičius. (2024). Benchmarking Derivative-Free Global Optimization Algorithms Under Limited Dimensions and Large Evaluation Budgets. IEEE Transactions on Evolutionary Computation, ISSN: 1941-0026, Online first, 19 pages, DOI: 10.1109/TEVC.2024.3379756
  2. L. Stripinis, R. Paulavičius. (2024). Review and Computational Study on Practicality of Derivative-Free DIRECT-Type Methods. Informatica, ISSN: 0868-4952, Online first, 34 pages, DOI: 10.15388/24-INFOR548
  3. E. Filatovas, L. Stripinis, F. Orts, R. Paulavičius. (2024). Advancing Research Reproducibility in Machine Learning through Blockchain Technology. Informatica, ISSN: 0868-4952, vol. 35, no. 2, pp. 227-253, DOI: 10.15388/24-INFOR553
  4. L. Stripinis, R. Paulavičius. (2024). Lipschitz-inspired HALRECT algorithm for derivative-free global optimization. Journal of Global Optimization, ISSN: 1573-2916, vol. 88, no. 1, pp. 139-169. DOI: 10.1007/s10898-023-01296-7
  5. M. Marcozzi, E. Filatovas, L. Stripinis, R. Paulavičius. (2024). Data-Driven Consensus Protocol Classification using Machine Learning. Mathematics, vol. 12, no. 2, article 221, 18 pages. DOI: 10.3390/math12020221
  6. L. Stripinis, R. Paulavičius. (2024). An empirical study of various candidate selection and partitioning techniques in the DIRECT framework, Journal of Global Optimization, ISSN: 1573-2916, vol. 88, no. 3, pp. 723-753. DOI: 10.1007/s10898-022-01185-5
  7. R. Paulavičius, L. Stripinis, S. Sutavičiutė, D. Kočegarov, E. Filatovas. (2023). A novel greedy genetic algorithm-based personalized travel recommendation system. Expert Systems with Applications, ISSN: 0957-4174, article 120580, 35 pages. DOI: 10.1016/j.eswa.2023.120580
  8. L. Stripinis, R. Paulavičius. (2023). Novel Algorithm for Linearly Constrained Derivative Free Global Optimization of Lipschitz Functions. Mathematics, ISSN: 2227-7390, vol. 11, no. 13, article 2920, 19 pages. DOI: 10.3390/math11132920
  9. L. Stripinis, R. Paulavičius. (2022). DIRECTGO: A new DIRECT-type MATLAB toolbox for derivative-free global optimization. ACM Transactions on Mathematical Software, ISSN: 0098-3500, vol. 48, no. 4, article 41, 46 pages. DOI: 10.1145/3559755
  10. L. Stripinis, R. Paulavičius. (2022). Experimental study of excessive local refinement reduction techniques for global optimization DIRECT-type algorithms. Mathematics, ISSN: 2227-7390, vol. 10, no. 20, article 3760, 18 pages. DOI: 10.3390/math10203760
  11. L. Stripinis, R. Paulavičius. (2021). A new DIRECT-GLh algorithm for global optimization with hidden constraints. Optimization Letters, ISSN: 1862-4480, vol. 15, no. 1, pp. 1865-1884. DOI: 10.1007/s11590-021-01726-z   
  12. L. Stripinis, L. G. Casado, J. Žilinskas, R. Paulavičius. (2021). On MATLAB experience in accelerating DIRECT-GLce algorithm for constrained global optimization through dynamic data structures and parallelization. Applied Mathematics and Computation, ISSN: 0096-3003, vol. 390, no. 1, article 125596, 17 pages. DOI: 10.1016/j.amc.2020.125596
  13. L. Stripinis, R. Paulavičius, J. Žilinskas. (2019). Penalty functions and two-step selection procedure based DIRECT-type algorithm for constrained global optimization. Structural and Multidisciplinary Optimization, ISSN 1615-1488, vol. 59, no. 6, pp. 2155-2175. DOI: 10.1007/s00158-018-2181-2
  14. L. Stripinis, R. Paulavičius, J. Žilinskas. (2018). Improved scheme for selection of potentially optimal hyper-rectangles in DIRECT. Optimization Letters, ISSN 1862-4472, vol. 12, no. 7, pp. 1699-1712. DOI: 10.1007/s11590-017-1228-4

 

Other peer-reviewed publications:

  1. L. Stripinis, J. Kůdela, R. Paulavicius. (2024). Hot Off the Press: Benchmarking Derivative-Free Global Optimization Algorithms under Limited Dimensions and Large Evaluation Budgets. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '24 Companion). Association for Computing Machinery, New York, NY, USA, 57–58. DOI: 10.1145/3638530.3664072
  2. E. Filatovas, L. Stripinis, F. Orts, R. Paulavičius. (2024). Towards Reproducible Research in Machine Learning via Blockchain. In: Sergeyev, Y.D., Kvasov, D.E. (eds.), Numerical Computations: Theory and Algorithms, Fourth International Conference NUMTA 2023, LNCS, Springer, Cham. (in press) Link.

 

Publications with VU Institute of Data Science and Digital Technologies & Institute of Mathematics and Informatics affiliation

Books

L. Stripinis, R. Paulavičius. (2023). Derivative-free DIRECT-type Global Optimization: Applications and Software. SpringerBriefs in Optimization. X, 122 p. ISBN: 978-3-031-46539-0, DOI: 10.1007/978-3-031-46537-6.

Expert activity

Reviewer in the following scientific journals: 

Scientific projects

2023-2027 "Development and validation of quantum machine learning methods using pre-built datasets". Supported by Lithuania Ministry of Education, Science and Sport. 

2021-2024 "Resolving research reproducibility problems in Artificial Intelligence using Blockchain Technologies". Supported by Lithuanian State Science and Studies Foundation. (Nr. S-MIP-21-53)

2017-2020 “Development and applications of bilevel optimization algorithms". Supported by Lithuanian State Science and Studies Foundation. (No. P‐MIP‐17‐60)

Honors and awards