Monetarist in heels

Events

7-8 June 2022

Top Women in AI

The “Perspektywy” Education Foundation, organiser of the Perspektywy Women in Tech Summit 2022, i.e., Europe’s biggest conference for women in technology, prepared a list of TOP-100 Women in AI – a list of exceptional women professionally dealing with the issue of artificial intelligence. Jagoda Kaszowska-Mojsa has been nominated by Perspektywy Women in Tech to the #Top100WomenInAI list. A compilation that aims to inspire the young generation with outstanding female role models in an area heavily dominated by men. The Excellence in AI Awards will be awarded on 7 June.

https://womenintechsummit.pl/

23-27 August 2022

7th Lindau Meeting of the Laureates of the Sveriges Riksbank Prize in Economic Sciences

The Lindau Nobel Laureate Meetings are annual scientific conferences held in Lindau, Bavaria, Germany, since 1951. Their aim is to bring together Nobel laureates and young scientists to foster scientific exchange between different generations, cultures and disciplines. Every year, Nobel Laureates convene in Lindau to meet the next generation of leading scientists: undergraduates, PhD students, and post-doc researchers from all over the world. Dr Kaszowska-Mojsa was nominated by the European Commission to take part in the meeting as a MSCA research fellow. Nobel Laureates and young scientists are joined by invited guests, supporters and friends during the meeting week.

Conferences

15-18 November 2021

Macromodels International Conference

The aim of the conference, organised every year since 1974, is to bring together scientists who work in the field of econometric modelling in order to facilitate the exchange of views and experience. Within the scope of interest are issues such as the problems of estimation, simulation, developing econometric models and their use for policy analyses. The joint work of J.Kaszowska-Mojsa, P. Włodarczyk and A. Szymańska (“Epidemic prevention and control in the DSGE model”) as well as the first results of the MACROPRU project (“Investigating new policies for financial stability that do not create inequality”) were presented during the conference.

4-6 March 2022

RCEA Conference on Developments in Economics and Finance

The Rimini Centre for Economic Analysis (RCEA), with the support of the Department of Economics of the University of Cyprus, the Tax Administration Research Centre (TARC) and the Foundation for Economic and Industrial Research - IOBE hosted the three-day online conference RCEA Conference on Recent Developments in Economics, Econometrics and Finance. Papers from all areas of Microeconomics, Macroeconomics, Finance, Econometrics and related fields, with a theory, empirical or policy focus were presented. Dr Kaszowska-Mojsa presented her paper on the macroprudential policies in the heterogeneous environment and the use of agent-based modelling in the financial oversight.

19-20 September 2022

4th IMA Conference on Big Data at the University of Oxford

Mathematical foundations of data science and its ongoing challenges are rapidly growing fields, encompassing areas such as: network science, machine learning, modelling, information theory, deep and reinforcement learning. The 4th Ima Conference on The Mathematical Challenges of Big Data brings together researchers and practitioners to highlight key developments in the state of the art and find common ground where theory and practice meet, to shape future directions and maximize impact. Dr Kaszowska-Mojsa will discuss her paper on the distributional effects of macroprudential policies and the mathematical foundations of agent-based macro model that she has been working on.

27-28 September 2022

Data-Driven Economic Agent-Based Models Workshop in Pisa

So far, economic Agent-Based Models (ABMs) have been successful tools to build theories and analyze policies while making model assumptions more realistic. A key feature that distinguishes ABMs from more aggregate economic models is that ABMs explicitly represent the dynamics of micro-components. This means that the state variables of ABMs can directly be initialized from one or multiple sources of micro-data. We believe that a more widespread use of micro datasets in initialization would yield credibility to ABMs. In the workshop, the researchers would like to answer the questions: (i) which data do we use in which models? (ii) which new techniques beyond parameter calibration are needed? (iii) why is it important to initialize ABMs with real-world data? Dr Kaszowska-Mojsa will discuss the empirical foundations of the MACROPRU model.

07 June 2022

Top 10 Women in AI

Top 10 Women in AI in Poland were distinguished at Perspektywy Women in Tech Summit 2022: Natalia Domagala (Ethical AI), Agata Foryciarz (Fighting AI Bias), Maria Ganzha (AI Researcher), Jagoda Kaszowska-Mojsa (AI for Change), Sylwana Kaźmierska (AI Promoter), Alicja Kwasniewska (AI Rising Star), Agnieszka Pilat (AI in Culture), Ula Sankowska (AI Entrepreneur), Agnieszka Słowik (AI Researcher), Ivona Tautkute-Rustecka (AI in Culture), Halina Kwasnicka (Distinguished Mentor in AI). The jury was led by Aleksandra Przegalinska, along with Dominik Batorski, Marzena Feldy, Borys Stokalski, and Katarzyna Szymielewicz. It was a lot of hard work to select only 10 from so many talented & accomplished women from the top 100 listed in https://lnkd.in/dFnhe4z6.

Books

Handbook of Financial Stress Testing

J. D. Farmer, A.Kleinnijenhuis, T. Schuermann, T.Wetzer

Stress tests are the most innovative regulatory tool to prevent and fight financial crises. Their use has fundamentally changed the modeling of financial systems, financial risk management in the public and private sector, and the policies designed to prevent and mitigate financial crises. Despite their centrality to public policy, the optimal design and use of stress tests remains highly contested. Written by an international team of leading thinkers from academia, the public sector, and the private sector, this handbook comprehensively surveys and evaluates the state of play and charts the innovations that will determine the path ahead. This guide is essential reading for researchers, practitioners, and policymakers.

Mastering Reinforcement Learning with Python

E. Bilgin

Reinforcement learning (RL) is a field of artificial intelligence (AI) used for creating self-learning autonomous agents. Building on a strong theoretical foundation, this book takes a practical approach and uses examples inspired by real-world industry problems to teach you about state-of-the-art RL.Starting with bandit problems, Markov decision processes, and dynamic programming, the book provides an in-depth review of the classical RL techniques, such as Monte Carlo methods and temporal-difference learning. Deep Q-learning, policy gradient algorithms, actor-critic methods, model-based methods, and multi-agent reinforcement learning are also explained. The key approaches behind successful RL implementations, such as domain randomization and curiosity-driven learning are presented.