Meet the speakers who will be present at Data Makers Fest 2024.
The Data Makers Fest organization has been working with a great team of advisors with diverse expertise in data. Their content curation will surely enhance this year's conference experience.
Gabriele Mazzini is the architect and lead author of the proposal for the Artificial Intelligence Act (AI Act) by the European Commission. Before joining the European Commission in 2017, Gabriele held several positions in the private sector in New York and served in the European Parliament and the EU Court of Justice. He has an LLM from Harvard Law School, a PhD in Italian and Comparative Criminal Law from the University of Pavia, and a Law Degree from the Catholic University in Milan. He is a Connection Science Fellow at the Massachusetts Institute of Technology (Media Lab) and is qualified to practice law in Italy and New York.
Gabriele Mazzini is the architect and lead author of the proposal for the Artificial Intelligence Act (AI Act) by the European Commission. Before joining the European Commission in 2017, Gabriele held several positions in the private sector in New York and served in the European Parliament and the EU Court of Justice. He has an LLM from Harvard Law School, a PhD in Italian and Comparative Criminal Law from the University of Pavia, and a Law Degree from the Catholic University in Milan. He is a Connection Science Fellow at the Massachusetts Institute of Technology (Media Lab) and is qualified to practice law in Italy and New York.
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.
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.
Bernardo is a data & AI leader, passionate about powering data transformations in companies and promoting social good in society using data. He is specialized in data science, machine learning and AI, having won two awards in this field (Innovation in Big Data Award by Thomson Reuters and Machine Learning & Neural Computation Award by Imperial College London). He has an MRes in Advanced Computing from Imperial College London, with a specialization in Machine Learning and a BSc in Electrical and Computer Engineering from Instituto Superior Técnico.
Daniel loves data, algorithms, and AI. He has a PhD in Computer Engineering and a Master in Artificial Intelligence. Daniel worked for several years at the University of Porto, where he lectured on computer science subjects and researched machine learning, computer vision, and other AI-related topics. Daniel also worked with École Polytechnique de Montréal, University College of London, the University of Gent, and Carnegie Mellon University. In 2015 he joined Veniam, where he helped to drive and set up the Data area (Science, Engineering, and Analytics). Since 2022, he is at Nexar working on deep-learning models.
Diogo Braga is a Machine Learning Engineer specializing in Graph Analytics. With a keen focus on innovation, he leads the development of cutting-edge graph-based solutions at EBCONT. Diogo's deep technical knowledge and understanding of graph algorithms empower organizations to harness the complexities of their data, facilitating well-informed decisions. His adept management of data resources guides businesses through the ever-evolving landscape of data-driven insights, ensuring sustainable growth and success.
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.
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.
Isaac is currently a Senior Research Engineer at Clarifai, where he works on improving their vector search capabilities and enabling new generative AI tech in production. Previously, he led custom enterprise solution development for visual search, built multi-modal retrieval systems, and helped maintain ML inference systems for LLMs and computer vision models. He spoke at various Python, ML conferences and meet-ups in Europe. Isaac's background is in Aerospace Engineering and Machine Learning and he holds undergraduate (B.A.Sc in EngSci) and graduate (M.A.Sc) degrees from the University of Toronto.
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.
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.
With over a decade of experience spanning various industries, a business background, and a master's in Data and Design, Letícia is known for her expertise in cultivating data-driven cultures, crafting compelling narratives, and implementing data visualization and design processes. At Odd, she leads a diverse team of experts in exploring creative and novel ways to push the limits of technology, communicating scientific discoveries, and delivering impactful data projects and tools for organizations. Being a proud Brazilian and Latin American, she wishes to be a South-Global representative and open cross-country opportunities.
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.
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.
Doctorate in the field of computer vision for medical images. Moiz has been working with images and textual data within the medical domain. Currently, Moiz has been involved in several projects related to bioinformatics, ML, and multi-omics in veterinary science and evolutionary hologenomics. Apart from the main projects, Moiz is working with other computer vision projects related to medical, infrastructure, and other smaller projects. Moiz's future projects will include multi-modal models within health science.
Muhammad Yasir Shabir is a dedicated Ph.D. researcher at Università di Torino, Italy. Collaborating with Synesthesia, he optimizes deep learning models while actively contributing to the MPAI community's AI standards. Additionally, he is an esteemed research member at EURIX Turin and an associate member of MPAI, enriching his expertise in AI and machine learning. As a lecturer at the University of Kotli AJK Pakistan, he shares his knowledge, bridging research and education to empower future data practitioners.
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.
Pedro Henriques is the co-founder and CTO of The Newsroom, on a mission to fight misinformation and break filter bubbles in the news, through AI. With 7+ years of experience in Data Science and AI, he has previously worked at large tech companies like LinkedIn and PayPal, and has been recognised as a top social entrepreneur in Europe by the EIB Institute. The Newsroom is backed by Inco and Google.org, and was one of six startups globally selected to partner with Meta on human-centric explainable AI.
Dr. Poonam Chaudhary is currently working as is currently working as the Data Science Lead and Associate Professor with the Department of CSE, The Northcap University. She is a target-driven, dedicated professional with more than 15 years of experience in teaching, administration, industry, and research. She has guided around 35 B. Tech projects, and 15 M.Tech theses, and currently supervising 4 Ph.D. Scholars. She has published 20+ research papers, chapters, and books in national and international conferences and peer-reviewed journals.
Rita Costa is a Data Visualization professional based in Portugal. She is passionate about using data to tell stories that shed light on relevant topics. She trained and worked as a data journalist and now leads the Data Visualization team at Feedzai, working at the intersection of research and product development. Other works include "Flags of Inequality", an award-winning piece that uses visual metaphors to highlight inequalities in legal rights for queer people in Europe.
Sam Debruyn is a Microsoft Data Platform MVP and Cloud Data Solution Architect passionate about the modern data stack. In his day-to-day, he designs and implements data platforms that support customers in harvesting the full potential of their data. Sam has over 10 years of experience with Microsoft Azure and regularly blogs about his adventures in data. He contributes to the data community through blog posts, open-source projects, and speaking engagements at data meetups and conferences.
Serg Masís is a Data Scientist in agriculture with a lengthy background in entrepreneurship and web and mobile development, and the author of the bestselling book "Interpretable Machine Learning with Python", and the upcoming book "DIY AI" for Addison-Wesley for a broader audience of curious developers, makers, and hobbyists. He's passionate about data-driven decision-making, Explainable AI, Responsible AI, behavioral economics, and making AI more accessible
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.
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.
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.
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.
Vinitra Swamy is a 4th-year machine learning PhD at EPFL in Switzerland. Her research on explainability and human-centric machine learning is co-advised by ML4ED and MLO labs. Prior to entering Switzerland, Vinitra graduated from UC Berkeley with both a Bachelor's and Master's in Computer Science at age 20, holding the record for the youngest graduate in the EECS department. She spent two years at Microsoft AI working on open-source AI frameworks as a lead engineer for the Open Neural Network eXchange (ONNX). She also lectured data science courses at the UC Berkeley Division of Data Sciences and the University of Washington CSE Department.
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".
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José Varela is passionate about Machine Learning, he created his first speech-to-text solution at INESC Macau back in 1998. Since then he's never stopped diving deeper and deeper into programming, data processing, and deep learning. For the last years 6 José has been at NTT Data Portugal, focusing on Deep Learning, and helping deliver value to Advanced Analytics customers in fields such as Utilities, Banking and Industry. José regularly speaks at different universities and corporate events and teaches Data Analytics at a Post-Grad course at IPS.
Rutuja Pawar combines a deep foundation in Computer Science enriched with a specialization in Data Science through her Masters. Her experience in technology, strategy, and consulting is broad, spanning years of collaboration with diverse teams across IT and Business. In her current role as a VIS Consultant at Accenture Germany, her focus lies on Data & Design, empowering clients to unlock the potential of their critical business data through intuitive, user-centric dashboards. Beyond her primary role, Rutuja wears many hats - a mentor, a Design Thinking Coach, a Tech Trainer, a #IAmRemarkable Facilitator, and a skilled Public Speaker.
Stephen is a Sr. Solutions Architect with AWS and concentrates on Data Analytics and Data Platforms. With over a decade of experience in software engineering and DevOps, he is committed to enhancing data engineering productivity and architecting resilient data platforms. Building on engineering best practices like automation or iterative software development, Stephen is passionate to create efficient solutions that empower organizations to deliver analytical workloads of high quality.
Having built vast know-how on forecasting and inventory management, Diogo is able to bolster companies on how to set up analytical models to anticipate demand uncertainty and, further on the chain, use these forecasts on state-of-the-art inventory optimization algorithms and operations planning. Before LTPlabs, Diogo had completed a Master’s degree in Industrial Engineering and Management at FEUP. Outside of work, Diogo is a sports enthusiast, especially for everything played with a racket.
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Luís Espírito Santo is a joint PhD student working on a theoretical computational framework that includes both learning and creativity. He is also one of the main organizers of Deep Learning Sessions Portugal. His general interests lie in Artificial Intelligence, Maths, Cognition Sciences and the Arts and he is currently researching on Generative Machine Learning Models, Computational Creativity and Formal Learning Theory. He is also the CTO at two startups bandwaggon.ai and MagicSync.
Aldan studied CS in Spain, France and Switzerland, graduating as valedictorian. He completed 4 internships and was selected by Django as a Google Summer of Code contributor. He received a grant from the Spanish government to undertake research on Natural Language Processing. He garnered recognition for leadership and academic excellence through several awards. He's also the founder of 3 associations and contributes to open-source. Currently, he works as Technology Research Specialist in AI at The Dock, Accenture’s flagship R&D and global innovation center.
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Alexey Yudin started his journey in the software development industry back in 2016. At first, he worked with back-end systems using languages like Java, Scala, and Python. By 2019, he transitioned into the Data field and mastered tools like Spark, Airflow, and Hive. In 2021, he started working with the Google Cloud Platform for building data pipelines. Currently, Alexey Yudin is a Senior Data Engineer at inDrive – the ride-hailing app with 200+ million app installs across 46 countries. He is responsible for streaming delivery of the most important data inside the company; his pipelines process 500+ million records daily.
During his BSc in Biomedical Engineering in Portugal, Bernardo Pereira had his first contact with AI, sparking his curiosity and leading him to continue studying AI during his MSc in Medical Imaging in the Netherlands. Through a series of internships in hospitals and research labs, Bernardo found out how to best combine these two worlds. Working at Philips Healthcare, he gained a deeper understanding of medical imaging as both a technology and a business, realizing that these are intrinsically linked. Now at Quibim, Bernardo applies all these learnings, pouring them into algorithms that turn images into actionable insights.
Filipa Marques, a data scientist with 16 years of experience in insurance, specializes in actuarial science and data analysis. With a strong math background, particularly in statistics, she's made significant contributions to the field. Her passion for advancing analytical methods led to research in machine learning, guiding 4 master's theses, one focused on causal ML. Demonstrating a commitment to data-driven decision-making, she continues to explore innovative approaches, extracting actionable intelligence from complex datasets to drive industry value.
Nuno is an engineer who loves to build things, especially if it involves data and machine learning. After helping build different startups in the Artificial Intelligence (AI) space, Nuno is now working on the OutSystems AI strategy to accelerate the way software powers innovation around the world.Nuno has a Masters in Industrial Engineering and Management from the Faculty of Engineering of the University of Porto (FEUP), and has published work in journals such as Decision Support Systems.
Filipa works as AI Program Manager at Continental, where she plays a pivotal role in establishing and steering innovative AI solutions across the value chain of tires. With a strong foundation in computer vision, deep learning and generative AI, Filipa brings a deep technical perspective to her cross-functional work with business and engineering. She holds an Integrated Masters in Bioengineering from the University of Porto, complemented by international study experiences in the UK and the Netherlands. Filipa also belongs to the Lead Team of Data Science for Social Good Portugal, a community which focus on using data for social impact.
Gonçalo Almeida holds a Masters' degree in Data Science and Advanced Analytics from Nova IMS and is currently pursuing a PhD in Data Science in the same institution. He started working at JTA, three years ago as a Data Scientists, and has been involved in the foundation of the Machine Learning & AI Pillar, which he now leads. Over the years, Gonçalo has worked in multiple projects, ranging from applying Machine Learning to more business oriented problems to projects involving the developments of Computer Vision and Natural Language Process solutions.
Gustavo Pereira is a data scientist with expertise in machine learning and statistics. He holds a master’s degree in Data Analytics from the University of Porto, where he conducted his thesis on modeling wildfires through extreme values distributions. He has three years of professional experience as a data scientist, working firstly for a consultancy firm and currently for NOS. At NOS, he has applied regression, classification, and time-series models for predicting customer dissatisfaction and new sales. He is proficient in exploring new data sources and techniques, as well as in improving machine learning automation and reliability.
João has been working with Data for a while now, building systems for it, using it, presenting it and teaching it. He has strong opinions, albeit weakly held, on managing data as infrastructure, configuration driven development and SQL still being king in the data world. With a background in Information Systems, João worked with Big Data systems and visualization in his masters before moving on to the industry where he works as a Data Engineer developing cloud-based data systems and analytics use cases for the BMW Group.
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Luís Ferreira is a Data Scientist and Machine Learning Engineer who loves to turn data into powerful insights and smart solutions. During his PhD at the University of Minho, Luís spent several years as a Machine Learning researcher and sharing what he knows in courses and bootcamps at various educational institutions. Currently, he's part of the team at Critical TechWorks. There, he focuses on developing, deploying, and managing ML models that help BMW unlock the full value of its data.
Miguel Freire, born in 1997 in Covilhã, Portugal, discovered his passion for technology early in life. Pursuing his interests, he moved to Lisbon in 2015 to study Electrical and Computer Engineering at IST-Lisbon. From 2018 to 2020, Freire worked as a Full-stack web developer at Aptoide, honing his skills. In 2020-2021, he conducted early-stage research at INESC-ID and completed his Master's Thesis in Deep Reinforcement Learning under the guidance of Arlindo Oliveira in 2022. Driven by his expertise, Freire co-founded NeuralShift in 2021 alongside Alexandre Borges and Arlindo Oliveira.
Philipp Bach, a postdoctoral researcher at the Chair of Statistics with Applications in Business Administration at the University of Hamburg and Head of Trainings and Executive Teaching at Economic AI, focuses on statistical methods for causal machine learning and their software implementation. Philipp applies these methods mainly in the context of economic research questions and collaborations with industry. Along with colleagues from Economic AI, Philipp offers industry training in the context of Causality, and Causal AI/ML targeted at data scientists and/or managers.
Telmo holds a Master’s in Electrical and Computer Engineering and has been working in the machine learning industry for the past six years. He's currently ML Team Lead at Loka, an AWS Partner for Life sciences and GenAI, leading projects on the application of Biological Large Language Models (BioLLMs) for AI-driven Drug Discovery. An expert in deep learning, probabilistic modelling and time series, Telmo also passionately contributes to education as an instructor at the Lisbon Data Science Academy and organizer of PyData Lisbon.
Dr. Tolga Kaya is a Professor and Director of Electrical and Computer Engineering programs at the School of Computer Science and Engineering. Dr. Kaya’s research primarily focuses on sports data analytics on wearable devices to monitor athletes’ physiology. He currently incorporates machine learning techniques to predict athlete performance and injury. He is well-known in the field of hydration research and sports data analytics. Besides his Ph.D. in Electronics Engineering, Dr. Kaya also has an M.A. in Education Technology and an MBA.
Ziv Levy works at Wix.com as a software engineer in the Data Science division. He is passionate about open-source projects and has a particular interest in web performance optimization. Ziv appreciates technology most when it incorporates visual elements and spends his free time mixing techno music.
Miguel Vicente is a recent Master’s graduate in Electrical and Computer Engineering from Instituto Superior Técnico, where he specialized in cyber-physical systems. Currently, he is working on his thesis at Fidelidade's Centre for Artificial Intelligence and Analytics, exploring the application of causal machine learning and A/B testing to optimize marketing strategies and enhance business outcomes. Miguel is looking to apply his technical skills and drive for innovation to make an impactful contribution to data science and machine learning.
Nuno B. Brás is a Senior Data Engineer and Data Scientist with extensive experience in consulting, teaching, and research.
He is currently a Partner and co-founder at DareData, an international company operating in the field of data and AI.
With over ten years of experience in developing startups and international businesses, Nuno has a background in Physics Engineering and holds a PhD in Electrical and Computer Engineering in the area of Signal Processing. He also has been a university professor for several years in the fields of programming, data, and machine learning.
Pedro Santos is a passionate physicist and a data scientist who loves uncovering hidden patterns. His transition from physics to data science was fueled by his curiosity about the inner workings of things. When he's not unraveling data puzzles, he enjoys exploring new destinations as a travel enthusiast or honing his skills in his favorite PS5 games, proudly embracing his inner nerd. Pedro brings vigor and passion to everything he does, whether it's applying statistical principles to data or using machine learning to solve problems. If you're interested in science intertwined with geek culture, Pedro is the go-to person.
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Ricardo Araújo holds an MSc in Bioengineering from the Faculty of Engineering and a PhD in Computer Science from the Faculty of Sciences, both obtained at the University of Porto. Currently, he works as a Senior Computer Vision & AI Engineer at JTA: The Data Scientists. He is driven by the pursuit of algorithms that can imbue computers with human-like capabilities and is dedicated to innovating in the field of Artificial Intelligence to develop technologies that address societal needs.
Yoav Nordmann is a Backend & Data Architect and Tech Lead with over 25 years of experience. His experience ranges from being part of infrastructure teams at big corporate firms and other times being the single developer at startups coding late into the night. At Tikal he holds the position of a Group Leader mentoring fellow workers. He is passionate about new and emerging technologies, knowledge sharing and a fierce advocate for open source. Being in the industry for so long gives him a sense of perspective on different languages, architectures, and hypes.
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. Recently, he switched to exploring the possibilities that LLM can bring. He has a background as a full-stack software engineer but switched 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.
