Chris Van Pelt is a co-founder of Weights & Biases, a developer MLOps platform. In 2009, Chris founded Figure Eight/CrowdFlower. Over the past 12 years, Chris has dedicated his career optimizing ML workflows and teaching ML practitioners, making machine learning more accessible to all. Chris has worked as a studio artist, computer scientist, and web engineer. He studied both art and computer science at Hope College.

Shubham Agarwal is a Staff ML Engineer at LinkedIn with a focus on content moderation. He has spent the last five years at the intersection of machine learning and real-world applications. His work is driven by a deep passion for applying AutoML technologies to solve complex business problems at scale, affecting millions of lives. He is eager to share insights and strategies at AutoML 2024, demonstrating the transformative potential of AutoML in creating impactful, scalable solutions

Hideaki Imamura is a researcher at Preferred Networks, Inc., and one of the core developers involved with Optuna development since 2020. He earned his Master’s degree in Computer Science from The University of Tokyo. He was the project manager for Optuna V3.0, is one of the authors of the Japanese book on Optuna and book on Bayesian optimization, and has been invited to give lectures and tutorials on Optuna and Bayesian optimization at ICIAM 2023 workshops and multiple domestic workshops in Japan.

Johannes Hoffart is heading the AI CTO office at SAP, a group of technology experts and scientists driving the development of business foundation models and knowledge graphs on SAP’s structured data. Before joining SAP in 2021, Johannes has led an AI research group on NLP and Knowledge Graphs at Goldman Sachs and co-founded a spin-off from the Max Planck Institute for Informatics with the goal of enabling businesses to tap into their knowledge hidden in text.

Rahma is a research scientist at Google Deepmind. Before that she was a Ph.D. candidate at Facebook AI Research and ENS Ulm, advised by Prof. Marco Baroni and Prof. Emmanuel Dupoux.

She is interested in understanding what made our language unique and how we can endow artificial models with such a communication protocol. Her recent work has centered on LLM pre/post-training within the Gemini team, where she played a key role in the release of Gemini Pro 1.5 with 1M context window.

Martin Rapp is a research scientist at Bosch AI Research. His focus is on optimizing deep learning models for efficient inference on resource-constrained hardware, leveraging techniques such as hardware-aware neural architecture search and knowledge distillation. Machine learning with limited computational resources has been his primary research interest for the past six years. Prior to joining Bosch in 2023, he was a researcher at KIT, where he specialized in machine learning for embedded systems.

Nilesh Jain is a Principal Engineer at Intel Labs and Director of Emerging Visual-AI Systems Research Lab. He focuses on developing cutting-edge technologies for edge and cloud systems, driving advancements in visual-AI applications. His current research focuses AI systems and infrastructure, algorithm-hardware co-design, and hardware-aware AutoML systems. As a Senior IEEE member, Nilesh has significantly contributed to the field with over 30 peer-reviewed publications and more than 45 patents, with many more pending.

Victor is the Director of Research and Hrvoje is a Senior Research Scientist at Secondmind, a machine learning based startup focused on helping automotive engineers to design and develop complex products, faster. Together they have a few decades of experience with developing and applying Bayesian optimization and probabilistic modelling to a broad range of problems across disciplines, from aerospace engineering to cognitive sciences. At Secondmind they have focused on scaling up Bayesian optimization and overcoming challenges of applying it to real-world problems faced by engineers in the automotive sector.