Machine Learning Prague 2022

Gilles Puy has been a research scientist at valeo.ai since 2019, working mainly on 3D perception for automotive applications, assisted and autonomous driving. Before, he was a researcher at Technicolor R&I (2016-2019), and a postdoc at INRIA (2014-2016). He obtained his PhD in signal/image processing from EPFL in 2014.

Dr. Thomas Wiecki is a PyMC author that holds a Ph.D. on computational cognitive neuroscience from Brown University. He is a former VP of data science and head of research at Quantopian Inc: building a team of data scientists to build a hedge fund from a pool of 300k crowd researchers. Thomas is also a recognized public speaker with keynotes at the Open Data Science Conference (ODSC) & TACC as well as talks at Strata Hadoop & AI, Newsweek AI conference, and various PyData conferences around the world 

He runs a data science podcast, blogs about Bayesian statistics, and is an avid Twitter personality. 

He’s been recognized as well as data scientist to follow of the year 2015, and ODSC Open Source award 2018.

Ashley is a data science research engineer at Seldon, where he works on developing production-ready tools for drift, adversarial and outlier detection. Prior to joining Seldon, he spent a number of years as a Research Fellow at The Alan Turing Institute. Here, he explored the use of machine learning for tackling aerospace engineering problems, with a focus on explainability and uncertainty quantification. Ashley also completed a PhD at the University of Cambridge, and is a keen proponent of open-source software, regularly contributing to a number of libraries as well as mentoring for programs such as Google Summer of Code.

Yauhen is a Kaggle competitions Grandmaster with a total of 9 gold medals in classic ML, NLP and CV competitions. He holds a Master’s Degree in Applied Data Analysis from the Belarusian State University. Yauhen has 7 years of experience in Data Science having worked in the Banking, Gaming and eCommerce industries. At H2O.ai his focus area is Deep Learning and Computer Vision, in particular. Yauhen has developed Computer Vision AutoML functionality for H2O.ai’s Driverless AI.

Pieter Luitjens has a Bachelor of Science in Physics and Mathematics and a Bachelor of Engineering from the University of Western Australia, as well as a Masters from the University of Toronto. He worked on software for Mercedes-Benz and developed the first deep learning algorithms for traffic sign recognition deployed in cars made by one of the most prestigious car manufacturers in the world. He has over 10 years of engineering experience, with code deployed in multi-billion dollar industrial projects. Pieter specializes in ML edge deployment & model optimization for resource-constrained environments.

Christina is a Digital Ethics and Compliance Consultant at PwC Czech Republic where she works on responsible AI, data governance, and digital transformation projects. Previously Christina researched law and technology design at the Technical University in Munich, consulted UK public authorities on responsible and ethical data-driven innovation at The Alan Turing Institute in London, and worked with international research consortia to implement privacy- and ethics-by-design practices in the creation of cutting edge technologies at Trilateral Research. She has experience working with diverse technologies, including machine learning, civil drones, OSINT, blockchain, and self-sovereign identity. She holds two Master degrees in International and European Law from the University of Zurich and the Catholic University of Leuven (KU Leuven) and spent time working at the European Commission on international trade disputes.

Timo Leitritz is a Computer Vision Researcher at Fraunhofer Institute for Manufacturing Engineering and Automation IPA in Germany, focusing on worker assistance in industrial applications using AI. Before working at Fraunhofer IPA he graduated at the Karlsruhe Institute of Technology with a Master’s Degree in Mechatronics and Information Technology, gaining interdisciplinary knowledge in the fields of Robotics, Computer Vision and Deep Learning. Together with industrial partners he investigates new ways of improving user experience in manufacturing environments with the help of human activity recognition.

Sachin is a Machine Learning Research Engineer at ArangoDB whose aim is to build Intelligent products using thorough research and engineering in the area of Graph Machine Learning. He completed his Masters’s degree in Computer Science with a specialization in Intelligent Systems. He is an AI Enthusiast who has conducted research in the areas of Computer Vision, NLP, and Graph Neural Networks at DFKI (German Research Centre for AI) during his academic career. Sachin also worked on building Machine Learning pipelines at Define Media Gmbh where he worked as a Machine Learning Engineer and Scientist.

Jakub is a researcher at Seznam.cz with current focus on improving web search relevance ranking. As a Ph.D. candidate at Institute of Formal and Applied Linguistics at Charles University in Prague, he developed several state-of-the-art systems for grammatical error correction. He also created a large and diverse grammatical error correction corpus for Czech.

Petr is the head of speech research at The Mama AI. During over ten years at IBM he built speech recognition and speaker diarization engines which currently power IBM Watson speech services. He holds several US patents. His background is in acoustic modeling using neural networks which he studied at IDIAP, LIMSI and CTU Prague. Petr's current goal at Mama AI is to build human-like expressive voice synthesis which can adapt to fit individual customer's desires.

Jan Maly leads the Data Science Team at STRV. He is passionate about AI and its potential to transform business. He has been in charge of multiple data-driven projects involving Machine Learning and Advanced Data Analytics. He enjoys solving business challenges through better data understanding and problem formulation. He got his master's degree in Artificial Intelligence at the Faculty of Electrical Engineering, Czech Technical University. Currently, he is on a quest to help STRV develop its platform for Data Science.

Jan has also recently become a father. Besides work and parenthood, he is an avid traveler and swimmer who enjoys sci-fi and fantasy.

Petr Baudis is a co-founder and CTO of Rossum who co-invented Rossum's unique AI engine and currently oversees its overall R&D and product development. Before, Petr led several AI research and deep learning projects, such as investigating deep neural models or publishing one of the main predecessors to DeepMind's AlphaGo.  Petr's past exploits include working with Linus Torvalds as one of the founding developers of Git and leading many other open source projects.

Milan Sulc leads the machine learning research in Rossum AI Labs, focusing on problems related to document understanding and information extraction. He holds a Ph.D. from the Visual Recognition Group at CTU in Prague and worked with Toyota, Google, Electrolux and Xerox Research on applied research projects including fine-grained image classification, object detection and monocular 3D detection, image retrieval, and domain adaptation. Milan won several ML competitions, was awarded university prizes for his theses and the Prize of Josef Hlávka for the best students and graduates, and has been supervising successful theses and projects of his students.

Having an economic & statistical background (Master degree in Management Science at WU Wien), Frederick Bednar has also gathered technical experience as a “data aficionado” for about two decades now. At EBCONT, he works as a Data Analytics and Data Science Consultant and is responsible for projects especially in Data Science, ML/DL, NLP & NER, but also BI consulting and IoT projects.

Julian Erdödy is considered an expert in the design of Deep Learning Models for smart applications in security as well as retail industries. Before joining EBCONT, he co-founded and led a Startup in Vienna for more than five years that successfully developed and deployed a computer vision engine creating situational knowledge from image and video data.

Starting from Software Development & Engineering as well as Data Analytics, Clifford Bednar has evolved his interest in various Machine Learning & Deep Learning techniques. He is now successfully combining his experience at EBCONT in different projects.

Jan Rus graduated in Computer Graphics at the Faculty of Applied Sciences, University of West Bohemia, Pilsen where he also worked as a Scientific Researcher for 5 years. For data compression research, he received the Best Suitable Commercial Application award in 2010.
After leaving academia, Jan became a founding member of the research team at Emplifi (formerly Socialbakers), where he currently works as a Senior Researcher.
At Emplifi, Jan is 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.
When not working for Emplifi, Jan cooperates with various startups helping them to solve data-related problems. In his free time, Jan enjoys movies and virtual reality.

Peter Jung got his master’s degree in artificial intelligence at the Faculty of Electrical Engineering, Czech Technical University in Prague. In that time, he was working in Heureka as a Python engineer and helped them with the first bigger machine learning project as a part of his diploma thesis. Currently he continues as a part-time PhD student at the same university and at Emplifi, he works as a Junior Researcher, where his main responsibility is to deliver natural language processing and computer vision oriented solutions. At Emplifi, he also hosts an advanced Python education group where people gather monthly and share their knowledge.
When he isn’t training models, he’s training Tobias, the chihuahua. He likes to travel and would like to speak French at some time.

 

Radovan Kavicky joined Datacamp among its first employees (historically 1st Data Science Instructor from CEE region & is still historically the only one worldwide who have made successful transition from regular student to instructor and employee after being #1 worldwide @ Datacamp platform for nearly a year, back in 2017).

Radovan is Data Science Polyglot (R, Python, Julia ++more) and Data Science Veteran with over 10 years of experience in Data Science and Applied AI/ML Consulting & extensive knowledge in the area (Data Science consulting, education & community building with successful cooperation with global leaders within our industry, like f.e. H2O.ai, Anaconda or Tableau). Radovan is also co-founder of Slovak.AI (Slovak Research Center for Artificial Intelligence) and member of various international professional societies within our Data Science & AI/ML industry, like f.e. IEEE Computer Society, CLAIRE (Confederation of Laboratories for Artificial Intelligence Research in Europe), European AI Alliance (European Commission/Futurium), TAILOR network (Trustworthy AI - Integrating Learning, Optimisation and Reasoning), UDSC (United Data Science Communities), PyData Global Network, Global Tableau #DataLeader network & The Python Software Foundation (PSF).

Radovan is also Founder of PyData Slovakia/Bratislava (#PyDataSK #PyDataBA), R <- Slovakia (#RSlovakia), Julia Users Group Slovakia (#JUGSlovakia), SK/CZ Tableau User Group (#skczTUG) & Effective Altruism Slovakia (#EASlovakia) that you are all welcome to join.

Tomáš Neubauer is cofounder and CTO at Quix, responsible for the technical direction of the company across the full technical stack, and working as a technical authority for the engineering team. He was previously technical lead at McLaren, where he led architecture uplift for Formula One racing real-time telemetry acquisition. He later led platform development outside motorsport, reusing the knowhow he gained from racing.

Javier Blanco Cordero is a Senior Data Scientist at Quix, where he helps customers getting the most out of their data science projects. He was previously a Senior Data Scientist at Orange, developing churn prediction, marketing mix modelling, propensity to purchase models and more. Javier is a masters’ lecturer and speaker, specializing in pragmatic data science and causality.

Michal is a Senior Data Scientist at O2 AICentre/Dataclair, where he works on optimising the customer lifetime value. He is a major advocate of TF-Agents and has facilitated migration to this framework with his team. He also lectures master's courses on machine learning and mathematical methods at CERGE-EI and Charles University. 

Petr's mission is to make the data scientist's life easier. He is responsible for developing the Data and Machine Learning platform in O2 AICentre/Dataclair. Currently, he's working on the implementation of a feature store. He also leads the data and machine learning engineering team. Machine learning and data is his passion. 

Until the end of 2019, he also served as a researcher for the Department of Cybernetics of the Faculty of Applied Science and as a Teacher. There he worked for more than eight years on research and development in artificial intelligence, speech technologies, natural language processing, and web technologies. 

In June 2020, he successfully defended his PhD in Artificial Intelligence.

Tomas is Data scientist at Seznam. He focuses on machine learning model's personalization. His main goal is to allow machine learning model's personalization across Seznam's ecosystem . Tomas likes climbing and running.

Adam did his master degree in Computer Science and then he focused on Visual Data Analysis while working as a researcher at visitlab, Masaryk University. Later, Adam moved from academia to Seznam where he currently helps to turn data of milions of users into Seznam's products. At Seznam, Adam moved from data analysis to data modeling.

Václav mastered AI & NLP course at FI MUNI and is now teaching machines how to recommend articles and other content to Seznam users. He's been doing it for more than three years now. Currently, he is trying to figure out how to combine multiple recommender systems and also how to use his NLP knowledge to improve recommendations in general.

Radek started as a Machine Learning Engineer at Seznam.cz four years ago and over time moved into Data Science area. His main focus in the past year was to find new models and approaches in our content recommendation system to improve user satisfaction and performance of the system.

Vit is a machine Learning Researcher at Seznam.cz since 2021. His work at Seznam.cz focuses on reinforcing the Seznam Advertizing System with Data Science and Machine Learning methods with aim to make it an efficient data centric system that provides the best experience for Seznam customers, publishers and Internet users. Vit received PhD in Electrical Engineering and Informatics in 2001 from Czech Technical University in Prague. His past career includes research positions at research labs in IBM and Honeywell.