Dan Yarmoluk

Dan Yarmoluk is the business and market development lead for ATEK’s IoT products which include TankScan and AssetScan.  Dan has been involved in analytics, embedded design and components of mobile products for over a decade with a focus on creating and driving IIoT automation, condition monitoring and predictive maintenance programs with technology with how analytics and business models intersect to drive added value and digital transformation. Industries served include: oil and gas, refining, chemical, precision agriculture, food, pulp and paper, mining, transportation, filtration, field services and distribution. He writes frequently on data science, IoT and business models in a variety of publications.  He has an MBA and finishing his graduate degree in Data Science.

Director of Business Development, IIoT and Analytics

ATEK Access Technologies

Associate Professor

University of St. Thomas

Dr. Manjeet Rege

Manjeet Rege is an Associate Professor at the University of St. Thomas in Graduate Programs in Software. Prior to joining UST, Dr. Rege was a faculty in the College of Computing and Information Sciences at Rochester Institute of Technology. He has taught a number of courses at the undergraduate and graduate level in varied instructional formats such as traditional classroom, online, and blended (hybrid). For his teaching, he was nominated by the students for RIT’s Eisenhart Award for Teaching Excellence. Dr. Rege’s research has been applied to many domain problems in text mining, Web Analytics and mining K-12 education data. He has published in various peer-reviewed reputed venues such as IEEE Transactions on Knowledge and Data Engineering, Data Mining & Knowledge Discovery Journal, IEEE International Conference on Data Mining, and the World Wide Web Conference. He is on the editorial review board of Journal of Computer Information Systems and regularly serves on the program committees of various international conferences.  He currently teaches Data Analytics and Visualization; Big Data Management; Machine Learning and Statistical Data Analysis.

Listen to Podcast

Explore Our Library

Contact Us