Teaching

 

Student research

Are you looking for a research topic? Get in touch!

If you are (already) thinking about Masters studies, our main (and bottomless) pool of subjects involves modeling molecular properties by electronic structure methods.
If you want to show off your modeling and problem-solving skills during job interviews (University does not prepare for life? Nonsense!), take a look at the following:

• “Real-time visualization of unstable solutions in hydrodynamic simulations” (can you image the bulk process while it unfolds? You are a 3D developer);
• “Accuracy limits of computationally modeled molecular structure” (can you determine the modeled length of a chemical bond without stating redundant digits? You are a quality assurance specialist);

…or tell us what you have in mind and we’ll discuss it!

 

Academic courses

At the moment, I supervise and teach the following courses in applications of information technology for the students of Computing Physics / Physics (bachelor) and Theoretical Physics and Astrophysics (master) programs:

• Introduction to Programming (C++),
• Numerical Methods (MATLAB),
• Parallel Computing (C++),
• Artificial Intelligence (Python).

Since the methods and applications falling under the name of “artificial intelligence” stoke my personal interest for a long time now, I do occasionally comment on those as well (see below).  In case you ever need a speaker inclined to explain rather than monger fear, let me know!

• Artificial intelligence: Path to prosperity or portent? (original title not mine, but the translation is 🙂)
  (Cafe Scientifique hosted by Open Readings 2019, 2019-02-25, in Lithuanian)
• On the successes (and occasional failures) of artificial intelligence — in the mood of April 1st:
  Good day, Lithuania (LRT, 2016-04-01, in Lithuanian)
• Vacuuming the maze and related search of the artificial intelligence
  (VU FF SMD (student science society) seminar, 2014-10-21, in Lithuanian)