Machine Learning Prague 2024

Stefan is a Senior Data Scientist at Dataclair, AI centre at O2 Czech Republic, since 2021, where he has been leading research efforts in applying advanced NLP and Deep Learning techniques to geospatial data. Drawing from his experience with language models and transfer learning since 2018, Stefan adeptly devises innovative solutions for diverse datasets and complex business problems. Stefan holds a M.Sc. in Economics from Stockholm University, where he specialized in empirical macroeconomics. Before shifting his focus on AI, he was working as project and product manager.

Martin Plajner is the Director of the Research and Development department in the consultancy company Logio. This department keeps the company at the technological edge by seeking novel approaches, prototyping, and defining new products. An inseparable part of the R&D team are trainees; students, who represent the company's future. Consequently, he preserves his link to academia as a researcher at the Czech Academy of Sciences - Institute of Information Theory and Automation (UTIA). These two parts provide an opportunity to combine the business and the academic world and to challenge both theoretical concepts as well as established practices.

Ludek Kopacek is a Data Science & ML Manager at Workday. Ludek leads the team focused on enhancing augmented analytics' ability to identify smart insight by integrating domain-specific Large Language models (LLM). His former experience comprises pricing optimization algorithms and ML-based sales optimization algorithms at Vendavo. He is passionate about staying up-to-date with the latest trends in ML and LLM. Not only because he is a fan of new developments, but he also brings experience in leveraging data science to drive business outcomes.

Daniel Costea is a senior software developer with more than two decades of experience and a passion for C# since its inception in 2001. He has been a frequent international speaker at over 50 conferences across Europe and the US in the past 6 years, and has organized community meetings and workshops. As a trainer, Daniel has delivered over 1200 hours of training in .NET web technologies to more than 700 students. He is also a published author of articles on .NET technologies, and was recognized as a Microsoft MVP in developer technologies in 2019.

Tun Shwe is the VP of Data at Quix, where he leads data strategy and developer relations. He is focused on helping companies imagine and execute their strategic data vision with stream processing at the forefront. He was previously a Head of Data and Data Engineer at high growth startups and has spent his career leading T-shaped teams in developing analytics platforms and data-intensive AI applications. In his spare time, Tun goes surfing, plays guitar and tends to his analogue cameras.

Tomas Neubauer is a co-founder and CTO at Quix, where he works as the technical authority for the engineering team and is responsible for the direction of the company across the full technical stack. He was previously technical lead at McLaren, where he led the architectural uplift of the real-time telemetry acquisition platform for the Formula 1 racing team.

Biostatistician (by training) turned into time series forecaster at Google. Currently untangling knots at protein backbones at Masaryk University and training llamas and other LLM creatures at Mediaboard (ex-Monitora a.s.). When not coding in R & Python, I'm sharing tips with over 40K @python_tips followers and trying to keep the ML community buzzing in (ML meetups Brno, PyLadies data course in Prague). Just a tech geek at heart and a big believer in AI's promise.

Over the past three years, David has been a pivotal member of Mediaboard, a leading Czech media monitoring company. He has been instrumental in spearheading innovative projects, focusing primarily on Natural Language Processing. His work involves developing cutting-edge techniques for data extraction, text summarization and clustering, significantly enhancing the company's media analysis capabilities. He holds a degree in physics and mathematical modeling from Charles University in Prague.

Idrees is a computational scientist with a degree in Mechatronics Engineering. Having 5 years of experience in research and development in simulation domain, he recently started his new research venture named Turing-Lab for developing ML based numerical solutions. At Turing Lab, he is researching on developing and implementing scalable Machine learning based framework for solving complex problems in computational science ranging from design space exploration to inverse physics problems. He is a C++ nerd and a strong advocate of FOSS who loves building open source tools in his free time.

I’ve been working over a decade in the field of Machine Learning, tackling challenges in areas such as medical diagnosis, cybersecurity, and various industries. Presently, I hold the position of Data Scientist at Humble Buildings, a Dutch company dedicated to technical monitoring of buildings. My current project revolves around exploring the capabilities of Large Language Models (LLMs). The primary objective is to revolutionize how our users, many of whom are non-technical individuals, interact with information. Throughout my job, I have accumulated some insights and lessons, and I look forward to sharing both the do's and don'ts with the audience.

Lucie currently leads one of the Data Science teams in Kiwi.com that specializes in customer-centric data science solutions. Lucie's professional experience includes Data Science and ML Engineering positions across multiple industries such as health care, pharmaceuticals, commodity trading, the energy industry, and of course the exciting travel industry that Kiwi.com is a significant part of. As far apart as these fields might seem, data science and data in general is what connects them all.

AI team lead at Kiwi.com where he focuses on mathematical theory to address travel search-related problems with machine learning. In the past he graduated from Paris Cité University, France, with a PhD in probability and statistics for numerical simulators. He also has experience with applying machine learning in the fields of energy - reliability in nuclear plants - and pharmaceutical industry - identification of key features in cancer drug development. On a much lighter note, he is a huge fan of indie/punk music and loves cooking.

Oliver Eigner is a passionate researcher at the St. Pölten University of Applied Sciences in the center for artificial intelligence in Austria, who is keen on trustworthy AI, human-centered AI as well as large language models. He finished his master’s degree with distinction in Information Security at the St. Pölten University of Applied Sciences in 2016. He is also an enthusiastic lecturer of Trustworthy AI and Python programming language.

Fabian Kovac is a 30-year-old Research Assistant at the St. Pölten University of Applied Sciences in Austria with a strong focus on Reinforcement Learning as well as sensor data and time series analysis. Before finishing his bachelor’s degree with distinction in Data Science & Business Analytics at the St. Pölten University of Applied Sciences in 2022, he had a background in software engineering, where he also the honor to lead the backend team at the time. After finishing his master’s degree, Fabian is pursuing a PhD to further work towards his dream to leave his footprints in the world.

Jan Rus is a Research Team Lead at Emplifi.io, a unified CX platform for enterprises. Jan manages a team of researchers mostly responsible for the design, research, and development of core product features exploiting big data analysis and machine learning techniques. Creation of concepts and bringing them from concepts to working prototypes and implementations. Lately, the team has been working on problems such as sentiment analysis, NSFW image detection and classification, LLM-based content creation assistant, or retrieval augmented generation for product help and support.

Peter Krejzl is a Director of Research at Emplifi.io, a unified CX platform for enterprises. Peter manages the international research team working on a wide variety of machine learning solutions, from natural language processing to image analysis, anomaly detection, or conversational AI. The team helps apply machine learning to solve tasks across the whole unified CX platform including marketing, care, and commerce solutions. Peter’s main point of interest is natural language processing and applications of AI in various marketing and care tasks, with a recent focus on generative AI.

With an engineering background in Production Automation and IT, Massimiliano embarked on a career as a Data Science Consultant at Sopra Steria. He has several years of experience in implementing AI systems, focusing on the operationalization of Machine Learning models and the interpretability of Black Box algorithms. Massimiliano leverages his expertise to advance the field of Data Science, ensuring that complex models are both deployable and understandable, thereby enhancing the decision-making processes within Sopra Steria’s client projects in in the telecom sector.

After obtaining a Master's degree in physics from the Technical University in Munich, Michele decided to leave academia behind and join Sopra Steria as a Data Science Consultant in 2022. She has an in-depth knowledge about graph databases, with a specialization on telecommunication networks. She applies this knowledge in her everyday project work at Sopra Steria for one of the major network providers in Germany for whom they build a digital twin of the mobile network based on a graph database. In alignment with her background as a physicist, Michele is also responsible for coordinating quantum computing projects in the German telecom sector of Sopra Steria.