JAKUB MACINA
HUMAN-CENTRIC AI (FOR) LEARNING

Jakub Macina

AI & ML Researcher, Engineer, Educator, Entrepreneur and Speaker.

PhD at ETH Zurich, machine learning (ML) and natural language processing (NLP) for more effective human-AI collaboration.

▶ Experience

Experience in software engineering, machine learning research, education and e-commerce. Jakub is Forbes 30 under 30 in the category of Science and Education.

Research-oriented approach: with publications in top-tier conferences such as EMNLP, ACL, RecSys, and NeurIPS. Received ETH AI Center Fellowship (<4% acceptance rate) and research grants in value over 100 000 CHF. Advised by Prof. Mrinmaya Sachan and Prof. Manu Kapur.

Applied research: as a machine learning engineer and senior staff machine learning engineer in one of the fastest-growing startups in Europe (which was acquired by Bloomreach in 2021). Responsible for building large-scale machine learning training and inference pipelines from scratch for a product recommender system platform used by hundreds of clients.

Teaching: I have taught courses on machine learning, large language models, and natural language processing in education at ETH Zurich. I have also given talks at various conferences and meetups.

Leadership: Both at the university and professionally, I successfully managed a team of six data scientists and advised more than 12 Master's and Bachelor's theses at ETH Zurich.

Entrepreneurship and Product management: I have led projects and defined product requirements that have been successfully launched at scale. Co-founded a startup in a health-tech space with a seed investment, was a member of Entprepreneur First cohort in Berlin.

Large-scale infrastructure architecture: experience designing and implementing training and inference pipelines at scale, with the ability to handle thousands of requests per second using Kubernetes in Google Cloud Platform.

Open-source development: I have contributed to open-source projects such as Discourse discussion platform (also with Google Summer of Code), and I have developed a few projects myself.

▶ Research

Artificial Intelligence, Machine Learning, Natural Language Processing, all combined with Human Computer Interaction.

Understanding the reasoning and pedagogical capabilities of generative large language models (LLMs such as GPT, T5, Flan-T5, BART, LLAMA).

Neural Language Generation and Dialogue Systems, focus on Pedagogical Alignment and Fine-tuning of LLMs for Tutoring.

Reasoning and Math Word Problem Solving.

Evaluation of Large Language Models.

Question Answering and Question Generation.

Recommender Systems and Personalization.

▶Talks

2024 Battle: Human vs. AI, Forbes Business Fest, Bratislava
2023 LLMs for Tutoring: Socratic Questioning and Scaffolding, AI in Education, AI+X Summit 2023, Zurich
2023 Talkshow about AI, Podcast by Forbes Slovakia
2022 Personalized Learning, ETH AI Center Doctoral Symposium, ETH Zurich
2019 Deep Learning for Recommender Systems, Vienna Deep Learning Meetup, Vienna
2018 Realtime personalized embedding, Python Conference (PyCon), Bratislava
2018 Improving Search at Discourse, Google Developer Group (GDG), Zurich
2018 Introduction to Natural Language Processing, Data Science Club by Exponea, Bratislava
2018 Embedding-based recommendations, Google Launchpad, Warsaw

Teaching

2024 Large Language Models, ETH Zurich
2022 Artificial Intelligence in Education, Head TA, ETH Zurich
2021 Artificial Intelligence in Education, ETH Zurich
2019 Text-based Information Retrieval, Slovak University of Technology
2019 Artificial Intelligence, Slovak University of Technology
2018 Text-based Information Retrieval, Slovak University of Technology

▶Publications