The biggest European conference about ML, AI and Deep learning applications.
Machine Learning Prague 2022
– , 2022Tickets
We are working on the ML Prague 2022 program already!
As with every past-edition of ML Prague, you can look forward to another excellent lineup of 45 international experts in ML and AI business and academic applications in 2022. They will present advanced practical talks, hands-on workshops and other formats of interactive content to you. We are hoping to deliver the event in a hybrid format with an offline conference while also streaming the talks live to you wherever in the world you might be.
What to expect
- 1000+ Attendees
- 3 Days
- 45 Speakers
- 10 Workshops
Phenomenal Previously on ML Prague stage
Ashish KapoorPartner Research Manager, Microsoft
Ashish Kapoor leads the Aerial Robotics and Informatics group at Microsoft, Redmond. Currently, his research focuses on building intelligent and autonomous flying agents that are safe and enable applications that can positively influence our society. The research builds upon cutting edge research in machine intelligence, robotics and human-centered computation in order to enable an entire fleet of flying robots that range from micro-UAVs to commercial jetliners. Various applications scenarios include Weather Sensing, Monitoring for Precision Agriculture, Safe Cyber-Physical Systems etc. Ashish received his PhD from MIT Media Laboratory in 2006.
Hava SiegelmannProfessor and Lab director, University of Massachusetts Amherst
Dr. Siegelmann, a recognized expert in Complex Systems and Neural Networks, focuses on theoretical computational neuroscience, computation in and modeling of natural systems and their application to intelligent systems. Of particular research interest are intelligence vis-a-vis adaptive memory, advanced models of cognition, and evolving, intelligent interfaces for robotics and other intelligent systems. Her studies often involve multi-scale modeling and system level analysis of major disorders such as cancer. The creator of a new field of computer science, Super-Turing computation, Dr. Siegelmann is applying the theory to biological systems and exploring them in connection with a new generation of analog computer.
Haifeng JinSoftware engineer, Google
Haifeng is a member of the Keras team at Google and a PhD candidate in DATA Lab at Texas A&M University. His research interests are AutoML and deep learning. He is the creator and project lead of AutoKeras, which aims to make deep learning more accessible with AutoML techniques.
Tomas MikolovSenior Researcher, CIIRC CTU Prague
Tomas Mikolov has been a research scientist at Facebook AI Research since May 2014 where he lead the popular fastText project. He is joining CIIRC and the Prague ELLIS unit full-time from April 2020. Previously he has been a member of Google Brain team, where he developed and implemented efficient algorithms for computing distributed representations of words (word2vec project). He has obtained his PhD from Brno University of Technology (Czech Republic) for his work on recurrent neural network based language models (RNNLM project). His long term research goal is to develop intelligent machines capable of learning to communicate with people using natural language.
Vojta JínaPrivacy Enthusiast, Apple
Vojta is a privacy enthusiast. While at Google, he helped to create AngularJS to simplify web development and make testing easier. These days, he is on a quest to solve machine learning with user privacy in mind, building intelligent products at Apple.
Karthikeyan Natesan RamamurthyResearch Staff Member, IBM Research AI
Karthikeyan Natesan Ramamurthy is a research staff member at IBM Research. His broad interests include understanding the geometry and topology of high-dimensional data and developing theory and methods for efficiently modeling the data. He has also been intrigued by the interplay between humans, machines, and data and the societal implications of machine learning. He holds a PhD in electrical engineering from Arizona State University.
Serg MasísMachine Learning Engineer, Syngenta
Serg Masís has been at the confluence of the internet, application development, and analytics for the last two decades. Currently, he's a Climate and Agronomic Data Scientist at Syngenta, a leading agribusiness company with a mission to improve global food security. Before that role, he co-founded a search engine startup, incubated by Harvard Innovation Labs, that combined the power of cloud computing and machine learning with principles in decision-making science to expose users to new places and events efficiently. Whether it pertains to leisure activities, plant diseases, or customer lifetime value, Serg is passionate about providing the often-missing link between data and decision-making — and machine learning interpretation helps bridge this gap more robustly. His book titled "Interpretable Machine Learning with Python" is scheduled to be released in early 2021 by UK-based publisher Packt.
Or Herman-SaffarSenior Data Scientist, Dell
Or Herman-Saffar is Senior Data Scientist at Dell. As part of her role, she designed various data science projects, from exploratory data analysis to application of machine learning models. Focus mainly on the following domains: feature engineering, time-series analysis, classification models. Or holds an MSc in biomedical engineering, where her research focused on breast cancer detection using breath signals and machine learning algorithms, and a BS in biomedical engineering specializing in signal processing.
Matthieu CordPrincipal scientist, Valeo
Matthieu Cord is a Full Professor at the Computer Science Laboratory (LIP6) of Sorbonne University, Paris, since 2006. He is also a part-time Principal scientist at the Valeo.ai research laboratory. He is a laureate of a chair of research and teaching in artificial intelligence from the national French government program on AI 2020 entitled VISA-DEEP: Towards visual reasoning in deep learning. He is an honorary member of the Institut Universitaire de France (junior 2009) and served from 2015 to 2018 as an AI expert at CNRS and French National Research Agency. His research expertise includes computer vision, machine learning, and artificial intelligence. He is the author of more than 150 international scientific publications on deep learning, computer vision, and multimodal vision and language understanding.
Uri EliabayevAI Consultant, Founder, Machine and Deep Learning Israel
Uri Eliabayev is a business consultant in the field of AI. Uri has worked with many consulting companies and organizations and helped them to choose and implement the best AI solution for their needs. Moreover, Uri has found the biggest AI community in Israel called “Machine and Deep Learning Israel”.
Kirill MaiantsevSenior Data Scientist, Broadcom
Kirill Maiantsev is a Senior Data Scientist at Broadcom working on their AIOps solutions. Kirill and the AIOps machine learning team are focused on building intelligent automation systems that are self-healing with minimal human intervention.
Kirill completed PhD program in Mathematics and Computer Science from the Lomonosov Moscow State University. The focus of his study was on differential equations, dynamical systems, and optimal control.
During his professional career Kirill gathered much experience in machine learning and quantitative finance developing algorithmic trading strategies. Since 2019 Kirill is with Broadcom where he is primarily focused on the anomaly detection in time series data problems.
Nik VostrosablinMachine Learning Engineer, MSD IT
Nik Vostrosablin is the Python/Machine Learning Engineer at MSD Artificial Intelligence group. In this group he works mostly on projects related with computational and molecular biology.
Prior to joining MSD Nik was mostly working in academic science in different universities (Moscow State University, Palacky University in Olomouc, Denmark Technical University).
He holds a master degree in Physics with honors from Lomonosov Moscow State University and currently finalizing his PhD in quantum physics.
Jeremy JonasSenior Product Manager, McKinsey & Company
Jeremy Jonas oversees ‘KNOW’ Profiles and Expertise Search, the most-used product family at McKinsey & Company, with over 3 million internal profile views annually. These applications show professional profiles and help teams find appropriate colleagues for specific needs, much like an internal LinkedIn.
Working with the Firm’s Prague-based Data Science team, Jeremy oversees the development of innovative ML-driven approaches to enhancing Profiles. This includes suggesting topics of expertise to add to profiles, now being extended into recommending colleagues to the Firm’s many Practices for leadership roles.
He is also overseeing experimentation with feedback-focused chatbots, leading so far to 10x higher feedback rates than any approach previously used with the product family.
Felipe ViannaData Science Specialist, McKinsey & Company
Felipe is a Data Scientist engaging with McKinsey internal teams to develop Machine Learning components to their products. He is mainly involved in NLP and retrieval projects, including the development of models for Expert Profiling. Being an engineer, he also takes care of full production deployment and scalability of the models developed.
Filip DousekSenior Director of Augmented Analytics, Workday
Filip was the CEO at Stories.bi (Gartner Cool Vendor, acquired by Workday). Now he leads augmented analytics development at Workday. Previously an SAP Solution Architect, analytics pioneer and published author (Flock Without Birds).
Filip PlešingerArtificial Intelligence and Medical Technologies, Institue of Scientific Instruments of the Czech Academy of Sciences
He received the M.Sc. degree (2003) and the Ph.D. degree (2008) at the Brno Univesity of Technology. He worked in a company Evektor (2006-2012); then he moved to the Institute of Scientific Instruments of the Czech Academy of Sciences in 2012, where he works until now. He received several international awards (Boston, USA, 2014; Nice, France, 2015; Rennés, France, 2017) for cardiology-related algorithms and software. From 2020 until now, he is the head of the scientific group "Artificial Intelligence and Medical Technologies" at Medical Signals department, Institute of Scientific Instruments of the CAS, v.v.i.
Tomas PevnyConsulting Scientist, Avast
Tomas has received his PhD in 2008 in University of Binghamton, SUNY, USA, where he has pioneered the use of Machine Learning techniques in Steganography and Steganalysis, for which he was awarded by IEEE Signal Processing Society. After one year post-doc in Grenoble, France, he has returned to Artificial Intelligence Center at Czech Technical University, where he has extended his interests to machine learning problems in Cybersecurity. He was closely working with Cognitive Security startup acquired in 2013 by Cisco systems Inc. Since September 2019 he is with Avast and with Artificial Intelligence Center at CTU.
Radovan ParrákProduct owner & ModelOps, Credo
Rado is a seasoned data scientist with a background in quantitative finance. After graduating as a financial economist at Maastricht University, he worked as a number cruncher in data science and quantitative finance departments at banks across Europe. More than ten years later and with dozens of models under his belt, the sheer pain of productionalising them into model-driven applications turned him into a devotee of ModelOps - an emerging field focused on governance and lifecycle of model-driven applications. Rado currently heads the development of Credo Software's ModelOps platform 'YQ'.
Petr SchwarzCTO and co-founder, Phonexia
Petr Schwarz, PhD, is the CTO and co-founder of Phonexia. He helped to build the well-known research group Speech@FIT at Brno University of Technology, Czech Republic, worked as a researcher at Oregon Graduate Institute in Portland, OR, USA, and founded Phonexia in 2006. He participated in the development of multiple speaker recognition and language identification systems evaluated by the United States National Institute of Standards and Technology. Petr was also a team member on several Johns Hopkins University summer research workshops in the field of human language processing, and he is the co-author of several open source software projects. He has worked on several European, USA, and Czech research projects, and is the author or co-author of dozens of impactful research articles.
Krzysztof RojekCTO, byteLAKE
Krzysztof is CTO at byteLAKE and associate professor at the Czestochowa University of Technology, Poland. He links byteLAKE’s business with the research and academic world. Krzysztof is a huge fan and a promoter of the ideas that can start their life in the research space and eventually land in the practical, real-life business applications. He gained his PhD+DSc degrees in Computer Science (Parallel Computing, GPGPU, self-adaptable codes, AI applications).
Adam BlažekCEO and co-founder, Iterait
Adam is a CEO and co-founder of Iterait, a company delivering computer vision AI solutions. As a leader of a research team at IBM and Cognexa, he gained experience primarily in healthcare-oriented projects. Adam has been publishing articles in scientific journals since his university studies at Charles University, where he graduated in Artificial Intelligence & Theoretical Computer Science. He received multiple awards for his Diploma thesis by the faculty’s Dean or in IT SPY competition.
Silvestr StankoML Analytics Team Lead, Qminers
Silvestr Stanko is a Machine Learning Analyst and Team Lead at Qminers, where he mostly focuses on time-series regression in the financial markets. Silvestr has previously worked for a large logistics company, where he led and completed multiple ML and analytical projects, with topics ranging from Natural Language Processing to Operations Research.
His research interests include Risk-averse Reinforcement Learning and Optimization.
Paweł RedzyńskiSoftware Engineer, dvc.org
Electronics engineer by education, a software developer by profession, deep learning enthusiast by heart. After a few years of software development, Paweł switched to work in the field of data science. He spend one-year helping Warsaw-based startup (Sports Algorithmics and Gaming) with video analysis of football trainings. Now he is somewhere in between both fields, creating tools for machine learning practitioners at Iterative.ai (creators of dvc.org). When he is not working, can be found trekking.
Aleš HorákAssociate Professor, Informatics at Masaryk University
Aleš Horák is an Associate Professor of Informatics at Masaryk University, Brno, Czech Republic. His research concentrates on natural language processing, knowledge representation and reasoning, e-lexicography and corpus linguistics.
Adam RambousekResearch Assistant, Faculty of Informatics at Masaryk University
Adam Rambousek is a Research Assistant at the Faculty of Informatics at Masaryk University, Brno. His main research topics include computational lexicography, corpus linguistics, ontologies, and semantic networks.
David VrbaData Scientist, Socialbakers
David works as a data scientist at Socialbakers. He is using Spark on daily basis for processing data on different scales from few GBs up to tens of TBs. He also does query optimizations and helps with productionalizing of various ETL pipelines. David enjoys preparing and lecturing Spark training and workshops and trained in Spark already several teams such as data engineers, analysts and researchers. David received his Ph.D. from Charles University in Prague in 2015.
Václav PavlínArchitect/Principal Software Engineer, Red Hat
Vašek is now part of the Office of the CTO team at Red Hat working on enablement of AI/ML workloads on Kubernetes where he leads a project Open Data Hub. He has extensive experience with building, deploying and managing containerized applications on OpenShift/Kubernetes. He loves open source and openness as well as meeting new people and arguing about technologies.
Francesco MurdacaSenior Software Engineer, Red Hat
Francesco is a Senior Data Scientist/Senior Software Engineer at Red Hat working in the AI Centre of Excellence and Office of the CTO. He works on Project Thoth, an open source project that develops tools that enhance day-to-day life of developers and data scientists using bots and machine learning. He is passionate about AI, space and technologies, all open source. He loves traveling and learning about new cultures.
Michal PlevaData Science Team Lead, Dataclair.ai, O2 Czech Republic
Michal is leading a team of data scientists delivering enhanced customer value through effective lifecycle management.
He has 5+ years of expertise in Telecommunications. His team utilizes various techniques of machine learning, mostly deep learning, to build prediction models of customers’ behavior employing event-based data. Currently is a Ph.D. candidate in the field of Economics connecting social network analysis with utility functions.
Petr StanislavHead of Engineering, Dataclair.ai, O2 Czech Republic
Petr‘s mission is to make the life of the data scientist a little bit easier. He is responsible for the development of the Data and Machine Learning platform in Dataclair.ai, O2 Czech Republic. He also leads the data and machine learning engineering team. Machine learning and data is his passion.
Until the end of the year 2019, he also served as a researcher for the Department of Cybernetics of the Faculty of Applied Science as was also a Teacher. There he worked for more than 8 years on research and development in artificial intelligence, speech technologies, natural language processing, and web technologies.
In June 2020, he successfully defended his Ph.D. in Artificial Intelligence.
Ivan KasanickyData Scientist, SAS
Ivan is an experienced Data Scientist with 9 years of experience. He has obtained Ph.D. degree in Probability and Mathematical Statistics from Charles University. During his career, he has work on different projects for, e.g., utility, transportation and automotive companies. He is an author of many advanced analytical models, such as predictive model for high way parking lots occupancies or renewable energy forecasting model. Ivan has joined SAS with a mission to help its customers to uncover how modern analytical and AI solutions can speed up their business. He focuses on understanding SAS customer business needs, and on showcasing how these needs and problems can be addressed with SAS advanced solutions.
Jordan BakermanSr. Analytical Training Consultant, SAS
Jordan Bakerman holds a Ph.D. in statistics from North Carolina State University. His dissertation centered on using social media to forecast real world events, such as civil unrest and influenza rates. As an intern at SAS, Jordan wrote the SAS Programming for R Users course for students to efficiently transition from the R to SAS using a cookbook style approach. As an employee, Jordan has developed courses demonstrating how to integrate open source software within SAS products. He is passionate about statistics, programming, and helping others become better statisticians.
Jo-fai (Joe) ChowData Science Evangelist, H2O
Jo-fai (or Joe) has multiple roles (data scientist / evangelist / community manager / customer success manager) at H2O.ai. He is best known as the H2O #360Selfie guy nowadays. On Twitter, he sounds like a die-hard MATLAB fanboy with the handle @matlabulous (because MATLAB was his favourite tool at Uni). Since joining H2O.ai in 2016, Joe has delivered H2O talks/workshops in 40+ cities around Europe, US, and Asia. He is the organizer of London Artificial Intelligence & Deep Learning meetup - one of the biggest data science communities in Europe with 9500+ members.
Kevin O'BrienData Scientist, Coillte
Kevin O'Brien is Coillte's Forestry Resource Modeller, based in their offices in Limerick. Kevin has been very active in the data science community over the past decade, and is now a director of Python Ireland, the Community lead for Forwards: The R Foundation taskforce on women and other under-represented groups, a European R User Meeting conference committee member, and Social media chair of JuliaCon. He was formerly a Mathematics and Statistics lecturer at the University of Limerick.
Avik SenguptaVP Engineering, Julia Computing
Avik Sengupta is VP Engineering and head of Julia Computing's European headquarters in London. Avik is the head of product development and software engineering at Julia Computing, contributor to open source Julia and maintainer of several Julia packages. Avik is the author of Julia High Performance, co-founder of two artificial intelligence startups in the financial services sector and creator of large complex trading systems for the world's leading investment banks. Prior to Julia Computing, Avik was co-founder and CTO at AlgoCircle and at Itellix, director at Lab49 and head of algorithmic solutions at Decimal Point Analytics. Avik earned his MS in Computational Finance at Carnegie Mellon and MBA Finance at the Indian Institute of Management in Bangalore.
Jon McLooneDirector of Technical Communication & Strategy, Wolfram Research
Jon McLoone is central to driving the company's technical business strategy and leading the consulting solutions team. With over 25 years of experience working with Wolfram Technologies, Jon has helped in directing software development, system design, technical marketing, corporate policy, business strategies and much more. Jon gives regular keynote appearances and media interviews on topics such as the Future of AI, Enterprise Computation Strategies and Education Reform, across multiple fields including healthcare, fintech and data science. He holds a degree in mathematics from the University of Durham. Jon is also Co-founder and Director of Development for computerbasedmath.org, an organisation dedicated to fundamental reform of maths education and the introduction of computational thinking. The movement is now a worldwide force in re-engineering the STEM curriculum with early projects in Estonia, Sweden and Africa.
Now or never Tickets
What You Get
- Practical and advanced level talks led by top experts
They’re among us We are in The ML Revolution age
Machines can learn. Incredibly fast. Faster than you. They are getting smarter and smarter every single day, changing the world we’re living in, our business and our life. The artificial intelligence revolution is here. Come, learn and make this threat your biggest advantage.
Our Attendees What they say about ML Prague
Are you attending too? Do you have tips for what not to miss?February 27, 2021
Guys, job more than well done 👍 thanks for great conference🙂— Ivan Kasanický (@IvanKasanicky) February 28, 2021
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If you have any questions about Machine Learning Prague, please e-mail us at
Scientific program & Co-Founder
Gonzalo V. Fernández
(Communities & Media partnerships)