Nino Antulov-Fantulin is head of research at Aisot Technologies AG, ETH-Zurich Spin-off and a privatdozent at ETH-Zurich. Currently, he works on research and development of novel financial machine learning systems for asset management.
Previously, he was a senior researcher at ETH Zurich, where he worked at the intersection of complex systems, finance, and machine learning. Results from his research were covered by New Scientist, American Physical Society, ACM TechNew, and others. He acts as a reviewer for IEEE, ACM, Nature Communications, Nature Scientific Reports, ICML, ICLR, ECML-PKDD, and NeurIPS.
He obtained a habilitation degree (Doctor habilitatus) from ETH Zurich in 2023 with a dissertation thesis: “Structure, dynamics and predictability in techno-socio-economic systems”. Nino got his Ph.D. in 2015 from the Faculty of Electrical Engineering and Computing, University of Zagreb, where he worked in the interdisciplinary field of complex systems combining tools from computational statistical physics, mathematics, and theoretical computer science. Besides ETH Zurich, he worked at the Rudjer Boskovic Institute, Faculty of Electrical Engineering and Computing, University of Zagreb, as a visiting scientist at the Robert Koch Institute (Berlin) & Courant Institute of Mathematical Sciences (New York) and as Supervisor & Panel member of PhD Program in Data Science, Scuola Normale Superiore, Pisa.
Deep Forecasting for Sequential Data in Finance with LSTMs & Transformers
In this talk, the speaker will present the common challenges of applying machine learning in Finance.
Focus will be on machine learning for sequential decision making with different types of neural networks.
Finally, the speaker will focus on the applications of Transformers and Large Language Models in Finance.