Frequently
Asked
Questions

Where is the venue?How do I get a ticket for the event?How do I get an invoice?What language will be spoken at the event?What's included in the festival ticket?Are meals included in the ticket?Will there be any networking opportunities?Is there a dress code for the festival?Is there parking available at the venue?How do I become a speaker?How do you select the speakers and talks?Are there any sponsorship opportunities?What happens if the festival is canceled?How can I contact the event organizers?
Talk
Reality-Centric AI
Responsible AI
Mihaela van der Schaar
Professor of ML, AI and Medicine at the University of Cambridge
Mihaela van der Schaar is the John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence, and Medicine at the University of Cambridge and a Fellow at The Alan Turing Institute in London. In addition to leading the van der Schaar Lab, Mihaela is the founder and director of the Cambridge Centre for AI in Medicine.Mihaela received numerous awards, including the Oon Prize for Preventative Medicine from the University of Cambridge (2018). Mihaela is personally credited as the inventor of 35 USA patents. She has made over 45 contributions to international standards for which she received 3 ISO Awards.
Talk
Friends don't let friends deploy black-box models
Data Engineering & MLOps
Explainability
Responsible AI
Rich Caruana
Senior Principal Research at Microsoft Research
Rich Caruana is a senior principal researcher at Microsoft Research. Before joining Microsoft, Rich was on the CS faculty at Cornell , at UCLA’s Med School, and at CMU’s Center for Learning and Discovery. Rich’s Ph.D. is from CMU. His thesis on Multi-Task Learning helped create interest in a new subfield of machine learning called Transfer Learning. Rich received an NSF CAREER Award in 2004 for Meta Clustering, best paper awards in 2005, 2007, and 2014, and co-chaired KDD in 2007. His current research focus is on learning for medical decision making, interpretable AI, and large language models.
Talk
Building recommendation systems for e-commerce marketplaces
Data Engineering & MLOps
Data Product Management
Recommendation and Personalization
Bongani Shongwe
Senior Data Engineer at Adevinta
Bongani is a data engineer working in personalization and recommendations for Adevinta's central team for the online classified markets across Europe and North America. He has a background as a full-stack software engineer but swapped to Data Engineering as it allowed him to follow his passion for large-scale distributed systems and related topics. Bongani obtained his MSc in Computer Science from the University of the Witwatersrand in 2014, focusing on peer-to-peer infrastructures for online gaming.
Talk
Multi-agent collaboration: Make AI code an entire application
Generative AI
Grigorij Dudnik
CTO and AI Engineer at Technospares
Grigorij is an enthusiast of generative AI, working in the field from almost its inception. Author of TinderGPT, an open-source autonomous AI dating app assistant, he is fascinated by the topic of multi-agent cooperation and uses AI agents to create code for the entire application from scratch. Contributes to Microsoft Autogen framework, which allows orchestrating those agents. He is also interested in open-source LLMs and their application in different fields, including robotics. He works with the finetuning of open-source models. Grigorij creates educational content on YouTube about open-source LLMs.
Talk
Creating a large dataset for pretraining LLMs
Deep Learning
Generative AI
NLP
Guilherme Penedo
ML Research Engineer at HuggingFace
With a background in Aerospace Engineering, Guilherme entered the ML world as a Research Engineer at a French startup called LightOn. While at LightOn, he was part of the Falcon team and was in charge of creating the pretraining dataset for the Falcon LLM: the RefinedWeb dataset. After working on the Falcon project, he joined HuggingFace, where he maintains the open-source data processing library "datatrove" and works on improving pretraining datasets as a member of the HuggingFace Science Team.
Talk
Vector Databases (pg_vector) and Real-Time Analytics
Advanced Analytics
Generative AI
NLP
Hubert Dulay
Developer Advocate at StarTree
Hubert Dulay is an O'Reilly author of "Streaming Data Mesh" and "Streaming Databases" (early access). He is a veteran engineer with over 20 years of experience in big and fast data. Hubert has compiled his experiences with data from his time while consulting for many financial institutions, healthcare organizations, and telecommunications companies, providing simple solutions that solved many data problems. With the massive growth in ML/AI, Hubert helps data practitioners understand how existing data pipelines can be altered for ML/AL.
Talk
Beyond text: Exploring the world with Large Multimodal Models
Advanced Analytics
NLP
Computer Vision
Jules Talloen
Senior Machine Learning Engineer at ML6
As a full-stack ML engineer, Jules is interested in the entire development process, from state-of-the-art research to data pipelines and web development. To stay at the forefront of innovation, he continuously monitors the latest research and enables applications built on top of the latest advancements. Using his technical expertise and drive for perfectionism, Jules translates business needs into high-quality, scalable, and performant data processing solutions.
Talk
Balancing Act: Recommendation systems in Retail Media
Data Product Management
Recommendation and Personalization
Forecasting
Domain-specific applications of AI
Kunal Chhabaria
Senior Product Manager at Walmart Connect
Kunal is a Senior Product Manager at Walmart Connect focused on building Machine Learning-based bid and budget recommendations for advertisers on Walmart's digital platforms. He has more than five years of Product Management Experience. Before Walmart, he was a part of the Tata Group's leadership development program - TAS. He contributed to building the first super-app in the Indian market, Tata Neu. Kunal is a double master's with his latest master's in Product Management from Carnegie Mellon University, Pittsburgh, United States. He has a background in Computer Engineering and completed his MBA from India.
Talk
The model wants what it wants: Strategies for label collection
Data Engineering & MLOps
Deep Learning
Marina Angelovska
Machine Learning Scientist at Booking.com
Marina is an experienced Machine Learning Scientist with engineering skills and a deep enthusiasm for innovation and collaboration. Her academic background in Computer Science (BSc) and Data Science (MSc)  taught her how to build and model. Marina's professional experience taught her how to design, plan, and execute, while her innovative mindset and curiosity drive her to proactively solve challenges. Working as a Machine Learning Scientist at Booking.com, she is currently focused on the NLP field.
Talk
Maximizing performance and reducing injuries in basketball
Computer Vision
Recommendation and Personalization
Domain-specific applications of AI
Explainability
Mehul S Raval
Professor and Associate Dean - Experiential Learning at Ahmedabad University
Dr. Raval is a researcher, educator, and mentor with over 25 years of experience and research expertise in computer vision, image processing, machine learning, data analytics, and engineering education. He has had the opportunity to engage in academic activities abroad and has received many accolades and awards. Raval's research has been published in reputable journals, magazines, conferences, and workshops, and his research has received support from institutions. He has been a reviewer for well-known publishers. He serves as Senior Editor and Associate Editor of IEEE Access and many other journals and has served IEEE.
Talk
First Principles Thinking in real world Machine Learning
Data Career Skills
Data Product Management
Data Team Leadership
Pedro Azevedo
General Partner at Union Square Ventures
Pedro Azevedo is a mechanical engineering graduate from the University of Aveiro who researched Autonomous Driving Assistance Systems (ADAS) in the Laboratory of Automation and Robotics at the Department of Mechanical Engineering. After completing his master's degree, Pedro transitioned to the industry, where he worked on real-time ML applied to the manufacturing industry and now works on large-scale machine learning systems, developing end-to-end ML pipelines through use cases in world-class fashion brands such as Adidas.
Talk
Policy as code: Automating compliance with Data Mesh
Data Centric
Data Engineering & MLOps
Data Product Management
Responsible AI
Shawn Kyzer
Associate Director of Data Engineering at AstraZeneca
Shawn is an innovative technologist and data strategist with over 15 years of experience. He is passionate about harnessing data strategy, engineering, and analytics to help businesses uncover new opportunities. His holistic view of technology and emphasis on developing strong engineering talent, focusing on delivering outcomes while minimizing outputs, sets him apart. Shawn's deep technical knowledge includes distributed computing, cloud architecture, data science, machine learning, and engineering analytics platforms. He worked as a consultant for prestigious clients, from secret-level government organizations to Fortune 500 companies.
Talk
High mileage of Low Rank Adapters
Data Engineering & MLOps
Deep Learning
NLP
Shikhar Chauhan
Data Scientist at KBC Bank NV
Shikhar Chauhan has worked with Deep Learning for images and text throughout his entire career, from solving fake news with AI to automating electronic waste recycling to automating document processing for a bank and optimizing internal processes using GenAI. Shikhar has also been a contributor to Transformers, Torchvision, and spaCy. He loves to share knowledge and keep up to date with the industry and the latest in the field. Shikhar is fascinated by NLP, Images, and Multi-Modal AI.
Talk
DGCF: Deep Graph-Powered Recommendations
Deep Learning
Recommendation and Personalization
Sofia Bourhim
Research Scientist at ENSIAS
Sofia Bourhim is a Research Scientist. She is working on Graph Machine Learning and its interdisciplinary applications to AI for Good problems. She recently obtained her Ph.D. in the field of AI. She previously interned at Microsft research lab (MARI) as a Research intern and is a recipient of the Microsoft PhD Fellowship. Sofia's contributions extend to receiving recognition for the best research papers at various conferences and notable events like NeurIPS'23 and Gitex'23.
Talk
Unlocking LLMs: From forgiving errors to ethical considerations in domain adaptation
Domain-specific applications of AI
NLP
Responsible AI
Vivek Kumar
General Partner at Union Square Ventures
Vivek Kumar is a Senior Researcher/Scientist and the Chair of Open Source Intelligence at the University of Federal Armed Forces under the Federal Ministry of Defence, Germany. He coordinates STELAR, an EU's Horizon 2020 program targeting "Artificial Intelligence, Data, and Robotics" in agri-food. Dr. Kumar won the Marie Sklodowska-Curie fellowship in 2019 for the EU's Horizon 2020 ITN network program PhilHumans & worked with Philips Research, Netherlands, and the University of Cagliari to receive a doctorate in 2023. His current research focuses on NLP, Knowledge Graphs, LLMs, AI Fairness & Bias.
Talk
The ML monitoring flow for models deployed to production
Data Engineering & MLOps
Explainability
Responsible AI
Wojtek Kuberski
Co-Founder and CTO at NannyML
Wojtek Kuberski is an AI professional and entrepreneur with a master's in AI from KU Leuven. He founded Prophecy Labs, a consultancy specializing in machine learning, before getting his current role as a co-founder and CTO of NannyML. NannyML is an open-source library for ML monitoring. At NannyML, he leads the research and product teams, contributing to novel algorithms in the model monitoring space. Wojtek was featured in the Breakout Session at Web Summit for "some of the world's most exciting early-stage startups".
Talk
Reality-Centric AI
Responsible AI
Mihaela van der Schaar
Professor of ML, AI and Medicine at the University of Cambridge
Mihaela van der Schaar is the John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence, and Medicine at the University of Cambridge and a Fellow at The Alan Turing Institute in London. In addition to leading the van der Schaar Lab, Mihaela is the founder and director of the Cambridge Centre for AI in Medicine.Mihaela received numerous awards, including the Oon Prize for Preventative Medicine from the University of Cambridge (2018). Mihaela is personally credited as the inventor of 35 USA patents. She has made over 45 contributions to international standards for which she received 3 ISO Awards.
Talk
Friends don't let friends deploy black-box models
Data Engineering & MLOps
Explainability
Responsible AI
Rich Caruana
Senior Principal Research at Microsoft Research
Rich Caruana is a senior principal researcher at Microsoft Research. Before joining Microsoft, Rich was on the CS faculty at Cornell , at UCLA’s Med School, and at CMU’s Center for Learning and Discovery. Rich’s Ph.D. is from CMU. His thesis on Multi-Task Learning helped create interest in a new subfield of machine learning called Transfer Learning. Rich received an NSF CAREER Award in 2004 for Meta Clustering, best paper awards in 2005, 2007, and 2014, and co-chaired KDD in 2007. His current research focus is on learning for medical decision making, interpretable AI, and large language models.
Talk
Building recommendation systems for e-commerce marketplaces
Data Engineering & MLOps
Data Product Management
Recommendation and Personalization
Bongani Shongwe
Senior Data Engineer at Adevinta
Bongani is a data engineer working in personalization and recommendations for Adevinta's central team for the online classified markets across Europe and North America. He has a background as a full-stack software engineer but swapped to Data Engineering as it allowed him to follow his passion for large-scale distributed systems and related topics. Bongani obtained his MSc in Computer Science from the University of the Witwatersrand in 2014, focusing on peer-to-peer infrastructures for online gaming.
Talk
Multi-agent collaboration: Make AI code an entire application
Generative AI
Grigorij Dudnik
CTO and AI Engineer at Technospares
Grigorij is an enthusiast of generative AI, working in the field from almost its inception. Author of TinderGPT, an open-source autonomous AI dating app assistant, he is fascinated by the topic of multi-agent cooperation and uses AI agents to create code for the entire application from scratch. Contributes to Microsoft Autogen framework, which allows orchestrating those agents. He is also interested in open-source LLMs and their application in different fields, including robotics. He works with the finetuning of open-source models. Grigorij creates educational content on YouTube about open-source LLMs.
Talk
Creating a large dataset for pretraining LLMs
Deep Learning
Generative AI
NLP
Guilherme Penedo
ML Research Engineer at HuggingFace
With a background in Aerospace Engineering, Guilherme entered the ML world as a Research Engineer at a French startup called LightOn. While at LightOn, he was part of the Falcon team and was in charge of creating the pretraining dataset for the Falcon LLM: the RefinedWeb dataset. After working on the Falcon project, he joined HuggingFace, where he maintains the open-source data processing library "datatrove" and works on improving pretraining datasets as a member of the HuggingFace Science Team.
Talk
Vector Databases (pg_vector) and Real-Time Analytics
Advanced Analytics
Generative AI
NLP
Hubert Dulay
Developer Advocate at StarTree
Hubert Dulay is an O'Reilly author of "Streaming Data Mesh" and "Streaming Databases" (early access). He is a veteran engineer with over 20 years of experience in big and fast data. Hubert has compiled his experiences with data from his time while consulting for many financial institutions, healthcare organizations, and telecommunications companies, providing simple solutions that solved many data problems. With the massive growth in ML/AI, Hubert helps data practitioners understand how existing data pipelines can be altered for ML/AL.
Talk
Beyond text: Exploring the world with Large Multimodal Models
Advanced Analytics
NLP
Computer Vision
Jules Talloen
Senior Machine Learning Engineer at ML6
As a full-stack ML engineer, Jules is interested in the entire development process, from state-of-the-art research to data pipelines and web development. To stay at the forefront of innovation, he continuously monitors the latest research and enables applications built on top of the latest advancements. Using his technical expertise and drive for perfectionism, Jules translates business needs into high-quality, scalable, and performant data processing solutions.
Talk
Balancing Act: Recommendation systems in Retail Media
Data Product Management
Recommendation and Personalization
Forecasting
Domain-specific applications of AI
Kunal Chhabaria
Senior Product Manager at Walmart Connect
Kunal is a Senior Product Manager at Walmart Connect focused on building Machine Learning-based bid and budget recommendations for advertisers on Walmart's digital platforms. He has more than five years of Product Management Experience. Before Walmart, he was a part of the Tata Group's leadership development program - TAS. He contributed to building the first super-app in the Indian market, Tata Neu. Kunal is a double master's with his latest master's in Product Management from Carnegie Mellon University, Pittsburgh, United States. He has a background in Computer Engineering and completed his MBA from India.
Talk
The model wants what it wants: Strategies for label collection
Data Engineering & MLOps
Deep Learning
Marina Angelovska
Machine Learning Scientist at Booking.com
Marina is an experienced Machine Learning Scientist with engineering skills and a deep enthusiasm for innovation and collaboration. Her academic background in Computer Science (BSc) and Data Science (MSc)  taught her how to build and model. Marina's professional experience taught her how to design, plan, and execute, while her innovative mindset and curiosity drive her to proactively solve challenges. Working as a Machine Learning Scientist at Booking.com, she is currently focused on the NLP field.
Talk
Maximizing performance and reducing injuries in basketball
Computer Vision
Recommendation and Personalization
Domain-specific applications of AI
Explainability
Mehul S Raval
Professor and Associate Dean - Experiential Learning at Ahmedabad University
Dr. Raval is a researcher, educator, and mentor with over 25 years of experience and research expertise in computer vision, image processing, machine learning, data analytics, and engineering education. He has had the opportunity to engage in academic activities abroad and has received many accolades and awards. Raval's research has been published in reputable journals, magazines, conferences, and workshops, and his research has received support from institutions. He has been a reviewer for well-known publishers. He serves as Senior Editor and Associate Editor of IEEE Access and many other journals and has served IEEE.
Talk
First Principles Thinking in real world Machine Learning
Data Career Skills
Data Product Management
Data Team Leadership
Pedro Azevedo
General Partner at Union Square Ventures
Pedro Azevedo is a mechanical engineering graduate from the University of Aveiro who researched Autonomous Driving Assistance Systems (ADAS) in the Laboratory of Automation and Robotics at the Department of Mechanical Engineering. After completing his master's degree, Pedro transitioned to the industry, where he worked on real-time ML applied to the manufacturing industry and now works on large-scale machine learning systems, developing end-to-end ML pipelines through use cases in world-class fashion brands such as Adidas.
Talk
Policy as code: Automating compliance with Data Mesh
Data Centric
Data Engineering & MLOps
Data Product Management
Responsible AI
Shawn Kyzer
Associate Director of Data Engineering at AstraZeneca
Shawn is an innovative technologist and data strategist with over 15 years of experience. He is passionate about harnessing data strategy, engineering, and analytics to help businesses uncover new opportunities. His holistic view of technology and emphasis on developing strong engineering talent, focusing on delivering outcomes while minimizing outputs, sets him apart. Shawn's deep technical knowledge includes distributed computing, cloud architecture, data science, machine learning, and engineering analytics platforms. He worked as a consultant for prestigious clients, from secret-level government organizations to Fortune 500 companies.
Talk
High mileage of Low Rank Adapters
Data Engineering & MLOps
Deep Learning
NLP
Shikhar Chauhan
Data Scientist at KBC Bank NV
Shikhar Chauhan has worked with Deep Learning for images and text throughout his entire career, from solving fake news with AI to automating electronic waste recycling to automating document processing for a bank and optimizing internal processes using GenAI. Shikhar has also been a contributor to Transformers, Torchvision, and spaCy. He loves to share knowledge and keep up to date with the industry and the latest in the field. Shikhar is fascinated by NLP, Images, and Multi-Modal AI.
Talk
DGCF: Deep Graph-Powered Recommendations
Deep Learning
Recommendation and Personalization
Sofia Bourhim
Research Scientist at ENSIAS
Sofia Bourhim is a Research Scientist. She is working on Graph Machine Learning and its interdisciplinary applications to AI for Good problems. She recently obtained her Ph.D. in the field of AI. She previously interned at Microsft research lab (MARI) as a Research intern and is a recipient of the Microsoft PhD Fellowship. Sofia's contributions extend to receiving recognition for the best research papers at various conferences and notable events like NeurIPS'23 and Gitex'23.
Talk
Unlocking LLMs: From forgiving errors to ethical considerations in domain adaptation
Domain-specific applications of AI
NLP
Responsible AI
Vivek Kumar
General Partner at Union Square Ventures
Vivek Kumar is a Senior Researcher/Scientist and the Chair of Open Source Intelligence at the University of Federal Armed Forces under the Federal Ministry of Defence, Germany. He coordinates STELAR, an EU's Horizon 2020 program targeting "Artificial Intelligence, Data, and Robotics" in agri-food. Dr. Kumar won the Marie Sklodowska-Curie fellowship in 2019 for the EU's Horizon 2020 ITN network program PhilHumans & worked with Philips Research, Netherlands, and the University of Cagliari to receive a doctorate in 2023. His current research focuses on NLP, Knowledge Graphs, LLMs, AI Fairness & Bias.
Talk
The ML monitoring flow for models deployed to production
Data Engineering & MLOps
Explainability
Responsible AI
Wojtek Kuberski
Co-Founder and CTO at NannyML
Wojtek Kuberski is an AI professional and entrepreneur with a master's in AI from KU Leuven. He founded Prophecy Labs, a consultancy specializing in machine learning, before getting his current role as a co-founder and CTO of NannyML. NannyML is an open-source library for ML monitoring. At NannyML, he leads the research and product teams, contributing to novel algorithms in the model monitoring space. Wojtek was featured in the Breakout Session at Web Summit for "some of the world's most exciting early-stage startups".

Find the answer to all your questions, and if you don't, email us, and we'll be happy to help!

Where is the venue?

You'll find the Data Makers Fest at Alfândega do Porto, a congress center right by the river in beautiful Porto. You won't believe the stunning sights within walking distance. The address is Rua Nova da Alfândega, Edifício da Alfândega, Porto.

How do I get a ticket for the event?

Just head over to the Get Tickets page and follow the steps.

How do I get an invoice?

During the purchase, you'll have the opportunity to request an invoice. This will be sent to your email within 20 minutes of your payment. Any changes to the invoicing data are not guaranteed and must be requested to the ticketing platform by email - support@last2ticket.com - within 30 days of your purchase.

What language will be spoken at the event?

Data Makers Fest talks and activities will be conducted in English.

What's included in the festival ticket?

All of our festival tickets include access to both conference days, with all the activities and spaces, and exclusive access to recordings of all talks right after the event.

Are meals included in the ticket?

Sorry, foodies, the festival ticket doesn't cover meals. But, we've got free-flowing water and coffee all day, and who knows, maybe some surprise snacks too. And don't worry about getting hungry—our food court will have some food trucks dishing out breakfast, lunch, snacks, and - of course - beer for the two days.

Will there be any networking opportunities?

We've got some awesome networking activities up our sleeves. We won't spill the tea yet, but trust us, there'll be plenty of chances to connect with other attendees, sponsors, and speakers. Oh, and did we mention the networking beer?

Is there parking available at the venue?

There's no designated parking for attendees at the venue, but don't worry! There's a paid public parking lot just a short 400-meter walk away. However, we highly recommend taking public transportation. There’s a bus stop in front of the main entrance. We'll provide you with all the information in the app.

How do I become a speaker?

The Call for Speakers for 2024 has already closed, with over 200 submissions. However, if you feel you have what it takes, we would love to have you on stage next year. Please write us at speakers@datamakersfest.com.

How do you select the speakers and talks?

We want Data Makers Fest to be a place of growth and valuable insights. To achieve this, we are always seeking the most relevant technical perspectives in the data field. Each year, we release a Call for Speakers and then, together with our Content Advisors squad, select the talks. During this process, the evaluators only have access to the outline and description of the session, and not to the speaker or affiliation. This ensures that every talk is selected solely based on content quality and topic relevance. Apart from the Call for Speakers, we also invite some specific speakers and keynotes to create an neat agenda.

Are there any sponsorship opportunities?

Sure! If you feel Data Makers Fest might be a match for your company, we'd love to talk. Besides sponsoring, we also have other opportunities for your company to benefit from the next edition of our festival. Please fill in the form on the footer ("Partner with us") or send us an email to corporate@datamakersfest.com.

What happens if the festival is canceled?

In the unlikely event of the festival being canceled or postponed, tickets will remain valid and can be used at the next in-person edition. Alternatively, attendees can opt for a full refund.

How can I contact the event organizers?

We're always here to help! Drop us a line at hi@datamakersfest.com, and we'll gladly assist you.