About the authors
Alena Traukina is the IoT practice lead at Altoros. She has over 12 year experience in the delivery and support of business-critical software applications, working closely with business owners and providing strategic and organizational leadership for software development. Over the years, Alena has served in different capacities, ranging from software engineer, to software engineering manager, to head of Altoros's Ruby department. She was also one of the first GE Predix Influencers.
Jayant Thomas (JT) has a passion for IoT, machine learning, and cloud-native architectures at scale. His passion has led him to many successful adventures at Veritas, GE, Oracle, AT&T, Nuance, and other start-ups, building platforms at scale. JT is an MBA graduate from UC Davis, and has an M.Tech from NIIT, as well as more than 15 patents in IoT, NLP processing, and cloud architectures. JT is also an enthusiastic speaker/writer, and has contributed to many conferences and meetups. In addition, JT is an active fitness and health freak, dabbling in various diets and health fads.
Prashant Tyagi is responsible for enabling the big data strategy at GE Digital for IIoT, leveraging IT and operational data for predictive analytics. He works with P&L verticals to enable their IoT use cases on the data and analytics platform.
He is on the board of ISSIP, focused on service innovation. He leads a cross-industry special interest group on IoT and analytics, and is an adviser to the open source fog computing initiative, ioFog, which is an Eclipse foundation initiative. He holds a B.Tech from IIT Delhi, an MBA from IIM Bangalore, and an MS in computer science from Clemson University. He has publications in leading journals and magazines and is a renowned public speaker and panelist, having featured at several conferences.
Kishore Reddipalli is a software technical director and expert in building IIoT big data and cloud computing platforms and products at ultra scale. He is passionate about building software for analytics and machine learning to make the authoring of algorithms at scale, from inception to production, a simpler process. He has been a speaker at global conferences on big data technologies. Over the years, he has provided leadership in various capacities. Throughout his career, his roles have ranged from software engineer to director of engineering and architecture for the development of platforms and products in domains such as clinical decision support systems, electronic medical records, Predix Platform, Predix Operations Optimization for IIoT, and etch-process control at nanometer level using big data and machine learning technologies in the semiconductor industry. He holds an MS in computer science from Texas A&M University Corpus Christi.