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6 Machine & Deep Learning Experts Announced for ODSC East 2022 6 Machine & Deep Learning Experts Announced for ODSC East 2022
Machine and deep learning are cornerstones of data science, setting the stage for everything else that data can do. As we... 6 Machine & Deep Learning Experts Announced for ODSC East 2022

Machine and deep learning are cornerstones of data science, setting the stage for everything else that data can do. As we gear up for ODSC East 2022, we want to highlight a few early-announced speakers coming to the event April 19th-21st, with these six speakers who will share their expertise in the field.

ODSC East 2022 Machine & Deep Learning Speakers

Sharmistha Chatterjee | Senior Manager of Data Sciences | Publicis Sapient | Need of Adaptive Ethical ML Models in Post-Pandemic Era

Sharmistha Chatterjee is a data science evangelist with 16+ years of professional experience in the field of machine learning (AI research and productionizing scaleable solutions) and cloud applications. She has worked in both Fortune 500 companies, as well as in very early-stage startups. She is currently working as a senior manager of data sciences at Publicis Sapient where she leads the digital transformation of clients across industry verticals.

Juhi Pandey | Senior Data Scientist | Publicis Sapient | Need of Adaptive Ethical ML Models in Post-Pandemic Era

Juhi Pandey is an artificial intelligence and machine learning evangelist, a speaker, and a mentor. She has nearly 11 years of experience, with statistical and architectural experience in different domains like life science, marketing, finance, and supply chain management. She has rich experience in building and scaling AI and machine learning businesses.

Julie Josse, PhD | Advanced Researcher | Inria

Julie Josse is a senior researcher in statistics and machine learning applied to health at Inria, a French research institute in digital sciences, and Professor at Ecole Polytechnique (Paris). She is an expert in the treatment of missing values (inference, multiple imputation, matrix completion, MNAR, supervised learning with missing values) and has created a website on the topic for users. Julie Josse is dedicated to reproducible research with R statistical software: she has developed packages including FactoMineR and missMDA to transfer her work.

Gael Varoquaux, PhD | Research Director/Director, Scikit-learn | Inria 

Gaël Varoquaux is a research director working on data science and health at Inria (French Computer Science National research). His research focuses on using data and machine learning for scientific inference, with applications to health and social science, as well as developing tools that make it easier for non-specialists to use machine learning. He is a core developer of scikit-learn, joblib, Mayavi, and nilearn, a nominated member of the PSF, and often teaches scientific computing with Python using the scipy lecture notes.

Balaji Lakshminarayanan, PhD | Staff Research Scientist | Google Brain

Balaji is currently a Staff Research Scientist at Google Brain working on machine learning and its applications. Previously, he was a research scientist at DeepMind for 4.5+ years. Before that, he received a PhD in machine learning from Gatsby Unit, UCL supervised by Yee Whye Teh. His research interests include scalable, probabilistic machine learning, with focuses on uncertainty, deep generative models, GANs, and more.

Thomas Kopinski, PhD | Professor for Data Science |The  University of South Westphalia | Dealing with Bias in Machine Learning

Thomas is a professor in data science and machine learning living in Essen, Germany. His research focus is in applied machine learning and deep learning with a specification in object detection and bias mitigation. Currently, he is leading two research projects, one on embedded ML in the field of predictive maintenance for automobile part manufacturing. The other project is on embedded ML in the field of skill-based people analytics within the context of deconstruction of nuclear power plants in the context of energy transition.

https://odsc.com/boston

ODSC East 2022 Call for Speakers

 

We’re still looking for more data science practitioners, thought leaders, and decision-makers to speak at ODSC East 2022! Interested in sharing your expertise? Learn more here, including what we’re looking for, deadlines, and how to get started.

Register for ODSC East 2022 Now

Now’s the best time to register for ODSC East 2022 and hear from these ODSC East machine learning and deep learning speakers, as prices are the best that they’re going to get. At 75% off, you won’t find a better deal. Register here and cross one thing off your end-of-the-year to-do list.

ODSC Team

ODSC Team

ODSC gathers the attendees, presenters, and companies that are shaping the present and future of data science and AI. ODSC hosts one of the largest gatherings of professional data scientists with major conferences in USA, Europe, and Asia.

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