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Chicago (August 26, 2021) — VelocityEHS, the global leader in cloud-based environmental, health, safety (EHS) and environmental, social, and corporate governance (ESG) software, announced today that Dr. Julia Penfield, Ph.D., principal machine learning scientist at VelocityEHS, has received the Best Paper Award for her work on the application of machine learning in predictive online monitoring for the maintenance of power system assets at the 2021 international conference oSmart Grid (icSmartGrid). The paper, “Machine Learning Based Online Monitoring of Step-Up Transformer Assets in Electrical Generating Stations,” was co-authored by Matt Holland, Maintenance Engineer at BC Hydro and provides evidence of the significant financial and safety benefits of applying machine learning to predictive monitoring programs.

Machine learning is a sub-set of artificial intelligence which can “learn” patterns and behavior in data. When applied to predictive maintenance scenarios, machine learning-based solutions eliminate most of the guesswork around the data collected over time to monitor the operating state of equipment to find patterns that can help predict and prevent failures. This can lead to major cost savings, higher predictability, and the increased availability and use of the systems being monitored.

“Our studies prove the increasingly common view that machine learning in predictive maintenance outperforms traditional maintenance strategies,” said Dr. Penfield. “Furthermore, BC Hydro’s success in using machine learning for a predictive online monitoring risk identification scheme demonstrates that machine learning is both an attainable and useable tool all companies should implement to achieve operational excellence. Whether its analyzing incident reports for categorization, facilitating efficient root cause and corrective action identification, extracting requirements from regulatory documents for auditing purposes, or using computer vision for remote ergonomic evaluation and analysis, machine learning replaces the costly human labor efforts required to complete these tasks to significantly increase safety, time/cost efficiencies, productivity, and profitability.”

Dr. Julia Penfield is globally recognized for her significant contributions to the machine learning field. After graduating from the University of British Columbia (UBC) with a Ph.D. in the Application of Machine Learning in Electrical Engineering, she continued working in the electric utility industry at BC Hydro, the electric utility of British Columbia, Canada. There, Dr. Penfield led the machine learning and data sciences programs such as electrical demand forecasting using advanced recurrent neural networks architecture, generation plant asset failure prediction using unsupervised machine learning, and wind farm generation forecast using fully connected neural networks architecture. She also utilized Natural Language Processing (NLP) and Computer Vision (CV) in several machine learning projects. Following eight years in the electric utility industry, Dr. Penfield joined VelocityEHS in 2021 as the principal machine learning scientist leading its Machine Learning Programs.

“With the largest R&D investment in the industry, VelocityEHS is at the forefront of innovative machine learning technologies,” said John Damgaard, CEO of VelocityEHS. “Our advanced Industrial Ergonomics software is the most widely, actively deployed and highly valued application of Machine Learning technology in the industry, used by more than 200 leading manufacturers in the automotive, food & beverage, pharmaceutical, and aerospace industries. Under Dr. Penfield’s direction, we will continue to find better ways to leverage machine learning to support our customers in evolving from a documentation and compliance focus to a focus on prediction, intervention, and outcomes in complex areas of EHS and ESG management.”

Part of the VelocityEHS Accelerate® Platform, the company’s all-in-one advanced Industrial Ergonomics solution combines online training, smart assessment tools and powerful program management features to seamlessly deploy, monitor, and manage the industrial ergonomics process across one, hundreds or even thousands of locations. The system’s sensorless motion-capture technology allows users to perform real-time risk assessments with video taken on any mobile device, collecting data faster and more accurately than any other method. The company’s recent acquisition of Kinetica Labs’ sensorless motion-capture technology further advances its industry leadership in innovative machine learning. As part of the acquisition agreement, Dr. Penfield will oversee the ongoing new research by Dr. SangHyun Lee, founder and CTO of Kinetica Labs and a professor at the University of Michigan, focused on the continued enhancement of Kinetica’s existing motion capture technology and the development of new EHS applications and use cases by utilizing the state-of-the-art machine learning sciences.

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About VelocityEHS
Trusted by more than 20,000 customers worldwide, VelocityEHS is the global leader in true SaaS enterprise EHS technology. Through the VelocityEHS Accelerate® Platform, the company helps global enterprises drive operational excellence by delivering best-in-class capabilities for health, safety, environmental compliance, training, operational risk and environmental, social and corporate governance (ESG). The VelocityEHS team includes unparalleled industry expertise, with more certified experts in health, safety, industrial hygiene, ergonomics, sustainability, the environment, AI, and machine learning than any EHS software provider. Recognized by the EHS industry’s top independent analysts as a Leader in the Verdantix 2021 Green Quadrant Analysis—VelocityEHS is committed to industry thought leadership and to accelerating the pace of innovation through its software solutions and vision.

VelocityEHS is headquartered in Chicago, Illinois, with locations in Ann Arbor, Michigan; Tampa, Florida; Oakville, Ontario; London, England; Perth, Western Australia; and Cork, Ireland. For more information, visit