ODSC Europe 2023 Speakers

Michael Bronstein, PhD

Michael Bronstein is the DeepMind Professor of AI at the University of Oxford and Head of Graph Learning Research at Twitter. He was previously a professor at Imperial College London and held visiting appointments at Stanford, MIT, and Harvard, and has also been affiliated with three Institutes for Advanced Study (at TUM as a Rudolf Diesel Fellow (2017-2019), at Harvard as a Radcliffe fellow (2017-2018), and at Princeton as a short-time scholar (2020)). Michael received his PhD from the Technion in 2007. He is the recipient of the Royal Society Wolfson Research Merit Award, Royal Academy of Engineering Silver Medal, five ERC grants, two Google Faculty Research Awards, and two Amazon AWS ML Research Awards. He is a Member of the Academia Europaea, Fellow of IEEE, IAPR, BCS, and ELLIS, ACM Distinguished Speaker, and World Economic Forum Young Scientist. In addition to his academic career, Michael is a serial entrepreneur and founder of multiple startup companies, including Novafora, Invision (acquired by Intel in 2012), Videocites, and Fabula AI (acquired by Twitter in 2019).

Physics-inspired Learning on Graph(Keynote)

Yonina Eldar

Yonina C. Eldar is a Professor in the Department of Math and Computer Science at the Weizmann Institute of Science, Rehovot, Israel, where she heads the center for Biomedical Engineering and Signal Processing. She is also a Visiting Professor at MIT and at the Broad Institute and an Adjunct Professor at Duke University, and was a Visiting Professor at Stanford University. She is a member of the Israel Academy of Sciences and Humanities, an IEEE Fellow and a EURASIP Fellow. She has received many awards for excellence in research and teaching, including the IEEE Signal Processing Society Technical Achievement Award, the IEEE/AESS Fred Nathanson Memorial Radar Award, the IEEE Kiyo Tomiyasu Award, the Michael Bruno Memorial Award from the Rothschild Foundation, the Weizmann Prize for Exact Sciences, and the Wolf Foundation Krill Prize for Excellence in Scientific Research. She is the Editor in Chief of Foundations and Trends in Signal Processing, and serves the IEEE on several technical and award committees. She heads the Committee for Promoting Gender Fairness in Higher Education Institutions in Israel.

Laurence Moroney

Laurence Moroney leads AI Advocacy at Google, working with the Google AI Research and product development teams. He’s the best-selling author of ‘AI and Machine Learning for Coders,’ as well as the instructor on the Fundamentals of TinyML course at HarvardX, and the popular TensorFlow specializations with deeplearning.ai and Coursera. He’s passionate about empowering software developers to succeed in Machine Learning, democratizing AI as a result. Laurence is based on Washington State in the USA.

A Hands-on Guide to Machine Learning with TensorFlow(Tutorial)

Leonidas Souliotis, PhD

Leonidas (Leo) is a Senior Data Scientist at Astrazeneca. His work is focused around machine learning in oncology, including clinical and non clinical applications. He is also enthusiastic about NLP applications in oncology and how this can be used to leverage patient treatment. He is also a workshop facilitator in the European Leadership University (ELU), NL and has also been a data science educator at DataCamp. He holds a PhD from the University of Warwick, UK. in bioinformatics and ML, an MSc in statistics from Imperial College London, UK and a BSc in Statistics and Insurance Science from the University of Piraeus, GR.

Introduction to Python for Data Analysis(Bootcamp)

Duygu Altinok, PhD

Duygu Altinok is a senior NLP engineer with 12 years of experience in almost all areas of NLP including search engine technology, speech recognition, text analytics and conversational AI. She authored several publications in NLP area at conferences such as LREC and CLNLP. She also enjoys working for open-source projects and a contributor of spaCy library.

Duygu earned her undergraduate degree in Computer Engineering from METU, Ankara in 2010 and later earned her Master’s degree in Mathematics from Bilkent University, Ankara in 2012. She spent 2 years at University of Bonn for her PhD studies. She is currently a senior engineer at Deepgram with a focus on conversational AI and speech technology.

Originally from Istanbul, Duygu currently resides in Berlin, DE with her cute dog Adele.

Sentiment Analysis Tricks with Keras, spaCy and Transformers(Tutorial)

Aoife Cahill, PhD

Aoife Cahill is a Natural Language Processing (NLP) expert and a director of AI research at Dataminr, the leading real-time information discovery platform. Since joining in 2021, Aoife has led a team of data scientists focused on the efficient iterative process of developing and evaluating AI technology that supports the expansion of Dataminr’s internal and external products.

Prior to Dataminr, Aoife led a team of research scientists and engineers working on high-stakes NLP applications in the educational domain at the Educational Testing Service (ETS). The NLP teams at ETS are known leaders in the field of developing and deploying robust, well-documented, scalable NLP prototypes that maintain fairness across user groups.

Aoife holds a PhD in Computational Linguistics from Dublin City University, Ireland, and has also spent time conducting NLP research in Germany, Norway and in the U.S. As an active member of the computational linguistics research community, her research has been published in top-tier journals including Computational Linguistics and the Journal of Research on Language and Computation, as well as conference proceedings at the annual conference for the Association for Computational Linguistics (ACL), the International Conference on Computational Linguistics (COLING) and the Conference on Empirical Methods in Natural Language Processing (EMNLP).

AI for Emergency Response(Demo Talk)

Tuana Çelik

Tuana is a Developer Advocate at deepset. She works on improving the developer experience and adoption of deepset’s Open Source NLP framework: Haystack. Originally from Istanbul, she moved to the UK in 2014 where she obtained a Master’s degree in Computer Science from the University of Bristol (in 2018). She initially started her career as a Software Engineer but then decided to become more involved with open source communities and educating people. This led her to developer relations. She worked as a developer advocate at Cumul.io before moving to deepset in 2022.

Semantic Search in NLP – How to Build Question Answering with Haystack(Talk)

Suraj Subramanian

Suraj is an ML engineer and developer advocate at Meta AI. In a previous life, he was a data scientist in personal finance. After being bitten by the deep learning bug, he worked in healthcare research (predicting patient risk factors) and behavioral finance (preventing overly-risky trading). Outside of work, you can find him hiking barefoot in the Catskills or being tossed on the Aikido mat.

Look, Listen, Read: Unified AI with TorchMultimodal(Talk)

Rachel Kellam

Rachel is a Product Manager in Appen’s Autonomous Vehicles working group. In that role, she is working to provide high quality data on all levels of autonomy for motor vehicle clients. Prior to joining Appen, Rachel worked on data science tools to enable model interpretability, fairness testing and automated machine learning. Other passions of hers include using AI and technology to act as a catalyst towards solving humanitarian-centered problems for non-profits around the world.

Manu Kanwarpal

Manu Kanwarpal is a Senior Specialist in the EMEA AI Global Black Belt team at Microsoft. He specialises in Azure Machine Learning and works with some of Microsoft’s largest customers on establishing their end to end processes for Data Science & MLOps. He is one of the authors of Microsoft’s unified MLOps accelerator called “MLOps v2”.

Microsoft’s Accelerator for MLOps(Workshop)

Shayan Mohanty

Shayan Mohanty is the CEO and Co-Founder of Watchful, a company that largely automates the process of creating labeled training data. He’s spent over a decade of leading data engineering teams at various companies including Facebook, where he served as lead for the stream processing team responsible for processing 100% of the ads metrics data for all FB products. He is also a Guest Scientist at Los Alamos National Laboratory and has given talks on topics ranging from Automata Theory to Machine Teaching.

Bias is Good: Arguments for Programmatic Labeling(Demo Talk)

Cindy Weng

Cindy Weng is a Senior Cloud Solution Architect at Microsoft in Data & AI. She specializes in architecting MLOps solutions for customers across a variety of industries including retail, financial services, consumer goods, and tech. She is one of the authors of the MLOps V2 unified accelerator by Microsoft.

Microsoft’s Accelerator for MLOps(Workshop)

Adam Reichenthal, PhD

Adam is an experienced Data Scientist at Imperva’s threat research group where he works on creating machine learning algorithms to help protect Imperva’s customers against database attacks. Before joining Imperva, he obtained a PHD in Neuroscience from Ben-Gurion University of the Negev.

ML with Humans: Integrating Experts into the Learning Process(Workshop)

Meissane Chami

Meissane Chami serves ThoughtWorks, Inc. as a Senior ML Engineer, advising and developing innovative data science and machine learning solutions from proof of concept to production. She has gained expertise setting up innovation frameworks and conducting fast cycle proof of concepts. Her primary areas of expertise are in Natural Language processing, MLOps, DevOps, cloud computing, containerisation and Python. She holds a MSc degree in Machine Learning and Data Science form University College London School of Engineering.

Data Science in the Industry: Continuous Delivery for Machine Learning(Training)

Andy Symonds, PhD

Andy Symonds is a technologist passionate about using data science in new and interesting ways. With a background in academia before moving into consulting, he loves problem solving and experimentation. Andy works with clients to help them gain insights and drive business value, by developing proof of concepts and moving these solutions into production.

Data Science in the Industry: Continuous Delivery for Machine Learning(Training)

Vishal Singh

With a bachelor’s degree in Engineering Physics from IIT Delhi, Vishal has a strong background in mathematics and statistics. He thoroughly enjoys working with Data Science, Machine Learning, and Big Data technologies, with a firm belief in learning by doing.

Aspect-Based Sentiment Analysis: Predict Market Impact of Financial Documents and other Use Cases(Tutorial)

Philip Rathle

Philip is SVP of Products for Neo4j, the company behind the open source Neo4j graph database&data science platform. Philip has a deep understanding of how graphs are used, where the space is going, and what uniquely differentiates graph technologies from others and from each other. With 10+ years as Neo4j’s head of product, he thrives on helping users solve intractable problems using the power of connected context, and offers a uniquely rich perspective on the increasingly popular space that he helped to pioneer and grow. Philip is a contributor to the book Graph Databases, published by O’Reilly Media, and he frequently speaks and writes about the technologies, tools, and techniques for deriving value from data. Prior to Neo4j Philip co-founded a data infrastructure startup, worked as Head of Product for database tooling vendor Embarcadero Technologies, and worked at many global companies as a consultant on large-scale mission-critical data projects.

Production Ready Graph Data Science: Better Predictions With The Data You Already Have(Talk)