“On Keeping Things Simple”
Angela leads the newly-formed team through development of machine learning algorithms, sentiment analysis, and anomaly detection processes. Angela is also a technical advisor for Mirah, a startup focused on making behavioral healthcare more objective and data-driven. Her previous projects earned accolades such as INFORMS’ Edelman award for Achievement in Operations Research and the Management Sciences; and the Massachusetts Innovation & Technology Exchange award for Big Data and Analytics Innovations. She discovered data science while studying math at MIT, only back then it wasn’t called that yet. Over the past two decades she has learned to lead data teams in academic, commercial, and industrial applications.
“Industrial Machine Intelligence: The Golden Braid of Data Streams, AI, and Human Expertise”
Drew is a world-renowned data scientist, entrepreneur, author, and speaker. He’s also the founder and CEO of Alluvium. Along with his experience building companies, Drew has advised and consulted for companies across many industries, ranging from fledgling start-ups to Fortune 100 companies, as well as academic institutions and government agencies at all levels. As a visionary in data science and large-scale computational – Drew will share his views on the emerging stack of big data technologies and how intelligent software systems will support normal business operations. He will focus on the benefits of AI to industrial businesses.
“Nuclear Energy: What Can Analytics Do for Economics and Safety?”
Abstract: The nuclear energy industry is at a crossroads: existing nuclear reactors are struggling to operate economically in some tough markets, and construction of new designs in the U.S. is slow and over budget. At the same time, interest in and development of the next generation of nuclear reactors is growing at an unprecedented rate, and some other nations are building new reactors efficiently. Can the current fleet reduce costs? Will the next generation of designs be “walkaway safe” and cost-competitive? What about safeguards and recycling of nuclear fuel? Data Analytics and Machine Learning can be impactful in answering these questions. This talk will frame some of the big challenges in nuclear energy and how Data Analytics are starting to be used. We’ll also look to the future in terms of where the biggest impacts are likely to be and what we can do to move quickly.
“Securing Machine Learning Systems”
Raluca Ada Popa is a co-director of the RISELab at UC Berkeley, as well as a co-founder and CTO of a cybersecurity startup called PreVeil. Raluca developed practical systems that protect data confidentiality by computing over encrypted data, as well as designed new encryption schemes that underlie these systems. Raluca has received her PhD in computer science as well as her Masters and two BS degrees, in computer science and in mathematics, from MIT. She is the recipient of an Intel Early Career Faculty Honor award and George M. Sprowls Award for best MIT CS doctoral thesis.
“ML to cure the world”
Patrick Franklin, VP – Predix Platform, GE Digital
“Prediction of fatigue related cumulative damage and crack growth”
“Data-driven analytics for Asset Performance Management (APM) software development”
“Machine Learning and Optimization for Reducing Emissions and Improving Efficiency in Coal-Fired Power Generation Units”
“Data Aggregation and Sharing – a necessity for Digital Twins in Healthcare”
“Unreasonable Effectiveness of Data For Healthcare Imaging”
“Navigating a Rocky Marriage: Data Science and Physics Models, Challenges and Solutions”
“Machine Learning Use Case Study for Remote Monitoring and Diagnostic Global Services”
“Machine Learning for Enriching Industrial Asset Data”
“Machine learning in the Industrial Inspections Domain”
“A Novel Recurrent CNN Architecture for Continuously Improving Segmentation from Video; An Ultra-Sound Nerve Segmentation Application”
“Aviation Innovations in the Industrial Internet of Things”
“Guiding Principles for Machine Learning in Production”
“Principles ofUI/UX for ML”
Invited Poster Presenters:
“Ultrasound Doppler Exam Automation by Machine Learning”
“Digital Solutions and Big Data Analytics in Oil and Gas: Enhance Oil Recovery and Intelligence Oil Field”
“An architecture for online update and monitoring of ML models in Production environments”
“Machine learning challenges in industrial internet”