SigOpt is hosting our first user conference, the SigOpt AI & HPC Summit, on Tuesday, November 16, 2021. It will showcase the great work of our customers from a variety of industries with a diverse set of use cases. It’s virtual and free to attend, so sign up today at sigopt.com/summit. To give you a sense of the Summit, we published a series of blog posts to give a preview of the content. These blogs gave an overview of the summit and went through the Design, Explore, Optimize journey modelers use to refine and deploy their models. This post details the speakers coming to the SigOpt event to give you a sense of what to hear at the summit.
We put longer profiles of our speakers here, but below you find brief descriptions of the modelers and researchers coming to our summit.
Scott Clark: Scott Clark is the co-founder, former CEO, and current general manager of SigOpt, acquired by Intel in November 2020. Scott leads SigOpt’s ongoing efforts to build a product and vision of an Intelligent Experimentation platform that accelerates and amplifies the impact of modelers everywhere. Join Scott for his keynote presentation Boost AI Experimentation to Design, Explore, and Optimize Your Models
Subutai Ahmad, PhD: Subutai Ahmad is the VP of Research at Numenta, a research company that is applying neuroscience principles to machine intelligence research. Join Subutai for his talk How Can We Be So Slow? Winning the Hardware Lottery by Accelerating Sparse Networks
David Austin: David Austin is a Senior Principal Engineer at Intel Corporation working on AI based solutions for the industrial Internet-of-Things and edge segment. Join David for his talk Supercharging a 1st place Kaggle Solution to Reach Higher Performance
Sasikanth (Sasi) Avancha: Sasikanth has bachelor degrees in Computer Science and Engineering, Masters and Ph.D. degrees in Computer Science. He is currently a Senior Research Scientist with the Parallel Computing Lab in Intel Labs and is based out of Intel India in Bengaluru. He has over 20 years of industry and research experience. Join Sasikanth for his talk Optimizing and Scaling Graph Neural Networks
Basem Barakat: As a large-scale machine learning engineer at Habana, Basem leads efforts to accelerate AI workloads on Habana Gaudi and other Habana AI accelerator hardware, including MLPerf Submissions. Join Basem for his talk Hyperparameter Optimization for MLPerf Training with SigOpt
Evelyn Ding: Evelyn is a senior machine learning engineer at Habana Labs and previously occupied the same role for Intel. Join Evelyn for her talk Hyperparameter Optimization for MLPerf Training with SigOpt
Ke Ding: Ke is a Principal AI Engineer and Engineering Director at Machine Learning Performance group under Intel Software and Advanced Technology Group. Join Ke for this talk Faster, Better Training for Recommendation Systems
Rafael Gomez-Bombarelli: as the Jeffrey Cheah Assistant Professor at MIT’s Department of Materials Science and Engineering since 2018, his works aims to fuse machine learning and atomistic simulations for designing materials and their transformations. Join Rafael for this talk Designing New Energy Materials with Machine Learning
Vishwanath Hegadekatte: R&D Manager and Principal Scientist at Novellis’ Kennesaw R&D Center and leads the global AI and Advanced Modeling group. Come see his talk on Streamlining Materials Design with Intelligent Experimentation and see him on the panel for Best Practices for Experiment Design
Alexander Rosenberg Johansen: A PhD student in Computer Science at Stanford, supervised by Michael P Snyder. He leads a research lab in the exploration of machine learning in Bioinformatics and MedTech at stanford-health.github.io. Join Alexander for this talk Deep Learning for Proteomics and the Future of Medicine
Marat Latypov: An assistant professor in the Department of Materials Science and Engineering and a faculty member of the Applied Mathematics Graduate Interdisciplinary Program at the University of Arizona. Marat has a wide range of interests in the field of materials science including materials informatics, modeling and simulation, artificial intelligence, materials design and process optimization. Join Marat on the panel Best Practices for Experiment Design
Paul Leu: An Associate Professor and the BP America Faculty Fellow in the Industrial Engineering Department at the University of Pittsburgh. His research group the Laboratory for Advanced Materials at Pittsburgh (LAMP) focuses on functional materials. Join Paul for his talk Better Glass Design with Multi-Objective Bayesian Optimization and on this panel Best Practices for Experiment Design
Alex Lowden: Data Science Manager & Team Lead within the AI practice of Accenture where he is predominantly focused on applying machine learning to unlock value within the Energy & Chemicals industries. Join Alex for this talk A Novel Framework for Predictive Maintenance Using Deep Learning and Reliability Engineering
Eddie Mattia: Product Manager from SigOpt who worked closely with SigOpt customers to help them design better Experiments and better optimize their models and is now focused on custom projects and using them to build product features that empower data scientists. Join Eddie on the panel Optimizing and Scaling Graph Neural Networks
Michael McCourt: Leads research and engineering at SigOpt, an Intel Company. We are responsible for developing, deploying, and maintaining the SigOpt platform both by creating tools to power intelligent experimentation and making sure these tools robustly meet the usage demands of our users. See Michael on the panel Best Practices for Experiment Design and for a Recap of the Conference
Shayan Mortazavi: Data Science Manager at Accenture Industrial Analytics Group, where he is currently working within resources industries with interests in predictive maintenance, digital plant engineering, and optimization for upstream industries and the water industry. Join Shayan for his talk A Novel Framework for Predictive Maintenance Using Deep Learning and Reliability Engineering
Sulata Patra: a results-driven leader and IT expert with over ten years of experience in manufacturing, finance, data science, and engineering. Most recently, she led efforts to build conversational AI to enhance customer support at Mindtree. Join Sulata for her talk Optimizing Pre-Trained Transformers in Conversational AI for Faster Inference, Better Accuracy
Bhanu Prakash: An accomplished machine learning and software architect with over 20 years of experience in the consumer electronics, semiconductor, and automotive industries. Currently, Bhanu draws on this expertise to address a variety of problems in conversational AI at Mindtree. Within Mindtree. Join Bhanu for his talk Optimizing Pre-Trained Transformers in Conversational AI for Faster Inference, Better Accuracy
Venkatesh Ramanathan: a Director, Data Science at PayPal where he is leading several applied research initiatives including ML on Graphs. enkatesh holds a Ph.D. degree in Computer Science with specialization in Machine Learning and Natural Language Processing (NLP). Join Venkatesh on the panel Optimizing and Scaling Graph Neural Networks
Meghana Ravikumar: As a Product Manager at SigOpt, she leads engineering, marketing and client teams in defining new modeling innovation, vetting market fit, developing requirements, managing product releases and launching breakthrough technologies to algorithmic trading firms, US intelligence agencies and leading streaming service providers globally.
Pablo Zegers, Ph.D.: He is a co-founder of Anastasia, focused on developing artificial intelligence tools for commercial businesses, and Sortbox, dedicated to building machines based on artificial intelligence for the agrotech sector. He was recognized as the 2020 Outstanding Electrical Engineer by the Chilean electrical companies and the IEEE. He was a Member of the Board of the Chilean IEEE Section, and he is a Senior Member of the IEEE. Join Pablo Zegers for his talk Democratizing Time Series Forecasting for Any Industry
Jian Zhang: A senior software engineering manager at Intel, recently he and his team primarily focused on implementing and optimizing end to end AI solutions on distributed CPU cluster, democratizing AI models to improve scalability & usability on commodity hardware. Join Jian for his talk Democratizing End-to-End Recommendation Systems
Da Zheng: senior applied scientist at AWS AI, where he develops deep learning frameworks including MXNet, DGL (Deep Graph Library) and DGL-KE. His research interest includes high-performance computing, scalable machine learning systems and data mining. Join De on the panel Optimizing and Scaling Graph Neural Networks
If you want to get a better sense of how SigOpt could impact your workflow than by simply reading about use cases, sign up in seconds at sigopt.com/signup. If you want to learn from our customers, sign up for the SigOpt Summit for free at sigopt.com/summit. Attendees will be able to join the talks and panels, meet with speakers in breakout rooms for deeper discussions and network with each other. Look for future posts that focus more deeply on the themes that will cut across the talks and panels at the Summit. We look forward to seeing you there!