CV

Zuzanna Osika

PhD Student in Applied Reinforcement Learning.

Profile

Reinforcement Learning - Multi-Objective Decision-Making - Human-AI Interactions - Water Resource Management - Public Policy Design - Climate Change Adaptation - Data Science

Profile

I am a third-year PhD student at TU Delft, working on enabling real-world application of multi-objective reinforcement learning. Specifically, I focus on real-world problems from the area of managing water resources with the use of AI, with multiple actors and objectives. Within my PhD, I work in the intersection of computer science, policy analysis, and civil engineering.
For publications, please refer to my Google Scholar.

Experience

2022-Present PhD Candidate, Technical University Delft

• Working on the practical application of multi-objective reinforcement learning (MORL) for complex problems with multiple actors (water resource management)
• Developing algorithms to assist policy-makers in utilizing MORL for complex decision-making processes

2020 - 2022 Socio-Economic Data Scientist, European Space Agency, Oxford

• Developed web-based dashboards (R Shiny) for data visualization of the space industry for ESA member states.
• Worked with econometric and causal models for estimating the impact of space investments on UN’s Sustainable Development Goals. The work has been presented at the International Astronautical Congress 2021 see abstract
• Conducted surveys among businesses within the European space industry to gather data and presented the insights to the member states

2019 - 2020 Junior Modelling Analyst, Nielsen, Warsaw

• Performed econometric modeling and data analysis on marketing campaigns’ impact on sales within the FMCG industry.
• Automated data tasks in R.

2016 - 2019 Internships & Other

• Analytics & Insights IT Trainee (6 months) at Procter & Gamble (was offered a full-time offer afterwards)

• Robotics Process Automation (RPA) Business Analyst (9 months) at Accenture

• Finance Intern (3 months) at Citi Bank

Education

2018-2020 MSc Computer Science and Econometrics, University of Warsaw, PL

• Thesis: Comparison of tree-based models’ performance in prediction of marketing campaign results using Explainable Artificial Intelligence tools working paper

2019 Exchange, University of Bologna, IT

• Exchange Student at the Department of Statistics.
• Relevant Courses: Non-parametric statistics, Methods and Tools for Official Statistics: Population and Health Statistics, Econometrics

2015 - 2018 BSc Computer Science and Econometrics, University of Warsaw, PL

• Thesis: Thesis: Tertiary Education Levels and Earnings in Poland and Some Other OECD Countries published paper

Skills

Technical & Software

Python (numpy, pytorch, pandas, gym, plotly), R (R shiny, plotly), SQL, Stata, Power BI, Adobe Illustrator, MS Office

Interpersonal

Presentation of complex concepts in an approachable way, Leadership, Organized, Creative Problem- Solving, Active Listening & Empathy, Adaptability, Analytical Thinking

Languages

• Polish (native)
• English (advanced)
• Dutch (basic) - learning