During my time at Charles University, I was dedicated to teaching, research, and academic work in the fields of econometrics, financial economics, and data analysis.
Below is a summary of publicly traceable activities based on available resources from Charles University and academic repositories. This list may not be complete.
Context
For me, academic experience is not just an item in my professional profile. It is the foundation upon which my current work with data, models, and AI is built: the ability to formulate a problem, rely on empirical evidence, and explain complex matters in an understandable way.
This combination creates a natural bridge between academia, econometrics, and my current Data Science / AI practice.
Overview
| Area | Publicly traceable minimum |
|---|---|
| Duration of involvement | 9 years (2009-2018) |
| Teaching | at least 2 traceable courses in IS CUNI |
| Academic theses | at least 1 supervised thesis and multiple reviewed / evaluated theses |
| Publication outputs | at least 3 records on IDEAS / RePEc |
| Main topics | econometrics, financial markets, portfolio and risk management, statistical analysis |
Teaching
| Course | Academic Year | Role | Area | Source |
|---|---|---|---|---|
| Portfolio Analysis and Risk Management (JEM092) | 2014/2015 | lecturer | portfolio management, asset pricing, risk management | IS CUNI |
| Mathematical Analysis Seminar I (JEB058) | 2013/2014 | lecturer | mathematical analysis, limits, derivatives, preparing students for the quantitative part of their studies | IS CUNI |
Note on teaching
Publicly available records show both specialized teaching in finance and risk management, as well as participation in teaching quantitative fundamentals for economics students. This corresponds well with a profile that later naturally led to econometric and data-oriented work.
Supervised and Reviewed Theses
Overview of traceable examples
| Role | Thesis | Year | Topic | Source |
|---|---|---|---|---|
| supervisor | Financial liberalization and stock market efficiency | 2015/2016 | market efficiency, financial liberalization | IS CUNI – list of theses |
| reviewer | The Housing Bubble in China | 2011/2012 | real estate market, speculative bubbles | IS CUNI |
| reviewer | Discrimination, information and cognitive effects: evidence from a field experiment in the Czech rental housing market | 2009/2010 | behavioral economics, experimental economics | IS CUNI |
| reviewer | How Rewarding Is Technical Analysis? Evidence from Central and Eastern European Stock Markets | 2010/2011 | technical analysis, capital market efficiency | IS CUNI |
| reviewer / evaluator | Household Debt in the Czech Republic: Focus on Mortgage Amount Determinants | 2016 | household debt, mortgages | DSpace CUNI |
| reviewer / evaluator | Analysis of Interdependencies among Central European Stock Markets | 2012 | stock market correlation, DCC GARCH | DSpace CUNI |
What this shows
The public sources repeatedly feature themes of financial markets, econometric modeling, structural changes, and applied data analysis. Additionally, broader economic and behavioral topics appear, indicating a scope that extends beyond narrow technical specialization.
Publications
| Year | Title | Type | Link |
|---|---|---|---|
| 2016 | Structural Distress Index: Structural Break Analysis of the Czech and Polish Stock Markets | journal article | IDEAS / RePEc |
| 2013 | Multi-Level Analysis of Dynamic Portfolio Formations: Central European Countries | working paper | IDEAS / RePEc |
| 2010 | Relationship between Czech and European developed stock markets: DCC MVGARCH analysis | working paper | IDEAS / RePEc |
Publication profile
The public profile on IDEAS / RePEc links these outputs to the Institute of Economic Studies at FSV UK. Thematically, it primarily involves the intersection of econometrics, capital market analysis, correlation structures, and portfolio modeling.
Why this section is important
Publications represent the strongest publicly verifiable layer of academic credibility. They also naturally connect to my current work with data pipelines, modeling, and AI systems, as they are built on the same foundation: formulating hypotheses, working with data, and providing defensible interpretations of results.
Transition to Current Practice
My current projects in Machine Learning, MCP architectures, and AI automation directly build upon this academic experience. In practice, I now use the same fundamental principles:
- working with data and ensuring its quality,
- modeling and evaluating results,
- explaining complex problems in a structured way,
- translating analytical insights into actionable decisions.
Thus, my academic background forms the evidence layer of my professional brand and also explains why I integrate economic thinking, data analytics, and AI implementation into a single framework.
Sources
- Charles Explorer – academic staff profile
- IDEAS / RePEc – author profile
- Publications of IES members on IDEAS / RePEc
- IS CUNI – Portfolio Analysis and Risk Management
- IS CUNI – Mathematical Analysis Seminar I
- IS CUNI – How Rewarding Is Technical Analysis?
- DSpace CUNI – Analysis of Interdependencies among Central European Stock Markets