• The Company

    Born and Built at Georgia Tech.

  • Our Story

    DecisionIQ was founded in late 2014 to commercialize the IIoT research of Dr. Nagi Gebraeel is a Georgia Power Associate Professor in the School of Industrial & Systems Engineering at Georgia Tech. His research, which began in 2002 at Purdue University, is noteworthy on many levels, including the use of an equipment failure test lab and funding by a Career Grant from the National Science Foundation.
    In July-2015, Dr. Gebraeel joined with Co-Founder, Andrew Lewis, to start the commercialization work. DecisionIQ entered the Flashpoint accelerator in October-2015 and entered the market in June-2015. At Flashpoint, extensive customer discovery was essential to set the right feature set for the integration of this research into what is now called the Genesis IIoT Platform. In 2016 the Company was also a member of the Coca-Cola sponsored Bridge:ATLANTA innovation program. DecisionIQ's operations are at Georgia Tech's ATDC technology incubator, Tech Square, mid-town Atlanta.

    Our Customers

    Since entering the market, DecisionIQ has secured marquee customers from Coca-Cola to Southern Company. Our Genesis IIoT platform produces distinctly superior results. In fact, all our POCs have been recommended to deployment, with complete cost justification. Some examples of rave reviews from our customers...

    “We toured Hannover MSSE 2018. We looked everywhere. No company in predictive maintenance comes close to your Genesis platform. You are at least 3-4 years in-front of the competition.”

    Senior Reliability Engineer, Fortune 100 Manufacturer


    "You're the only analytics company able to predict this problem. Well done!"

    VP Product Engineering, Fortune 100 Communications Company

    Three other analytics companies unable to provide a solution.


    "Excellent work. You detected all the hidden equipment failures."

    VP Innovation, Top Five US Electrical Power Utility

    We the Team

    Xiaolei Fang, PhD

    Principal Research Scientist

    Dr. Xiaolei is an expert in industrial predictive analytics with experience in industrial sectors ranging from steel manufacturing to power plants. He recently received his M.S. degree in Statistics and Ph.D. degree in Industrial Engineering from the Industrial and Systems Engineering (ISyE) school at Georgia Tech. His expertise lies in the field of industrial predictive analytics for High-Dimensional and Machine Learning applications in the energy, manufacturing, and service sectors. Specifically, he is focused on addressing analytical, computational, and scalability challenges associated with statistical and optimization methodologies for analyzing massive amounts of complex data structures for real-time asset management and optimization. He was the winner of the Jarvis Ph.D. Student Research Award at Georgia Tech. LinkedIn...

    Nagi Gebraeel, PhD

    Co-Founder, Chief Data Scientist

    Nagi is a visionary and world leader in the science of analytics for equipment health and failure prevention. He is a Professor at Georgia Tech's top ranked Industrial and Systems Engineering school (ISyE) school, and holds a Masters and Doctorate in Industrial & Systems Engineering from Purdue University.​ He brings 15 years of focused analytics research on real-world failure test lab projects with major industrial partners and the National Science Foundation. Nagi is Director of the Georgia Tech Manufacturing Center for Predictive Analytics, and Associate Director for analytics at Georgia Tech's Strategic Energy Institute. Nagi leads the development of the Genesis platform, and daily infuses his lifetime of experience in the science of equipment failure to our data science team, codifying his expertise into a new breed of specialized AI & ML algorithms. LinkedIn...

    Chris Hanes

    Principal Data Engineer

    Chris completed his undergraduate studies at the University of Michigan in computer science and worked over six years as a full stack developer, with an emphasis on building the back end data base infrastructure necessary to support the applications. He was also CTO in a funded startup building a web based platform for online learning. He received his Masters of Science in Analytics from Georgia Tech and is excited to bring his diverse package of coding experience back to the startup sector. This experience is proving essential to building our Genesis platform, including custom tools that automatically connect, curate and process client operations in real time with superior AI & ML results.  LinkedIn...

    Felipe Imanishi

    Data Science Engineer

    After completing his electrical engineering bachelors degree at the highly rated Universidade Federal do Espírito Santo in Brazil, Felipe worked at Schlumberger for seven years as a General Engineer on over 50 off-shore oil rigs in Malaysia, Norway and the Gulf of Mexico. He ultimately led drilling teams on large scale projects including drilling the longest well in the Gulf of Mexico. Now completing his Master of Science in Analytics at Georgia Tech, he is already fulfilling his personal goal at DecisionIQ -- to work in different industries and actively impact their performance. He is part of a team building a new generation of AI & ML algorithms able to solve downtime and maintenance problems common to all industrial sectors. LinkedIn...

    Andrew Lewis

    Co-Founder, CEO

    A former fighter aircraft designer at the General Dynamics F-16 skunk works, and now a serial entrepreneur with over 25 years experience. Andrew is a proven product visionary who builds great teams at the intersection of fast-breaking technologies and markets. Past innovations include the first application of delta wings to advance performance on current generation fighter aircraft, first multi-processor desktop computers (built under a clone license from Apple), and a pre YouTube cloud platform for easy video publishing. Andrew brings his first-hand experience building innovative technology solutions to the Company's product strategy. He holds a Bachelors in Aerospace Engineering from Georgia Tech and an MBA from the University of Chicago.

    @LewisAndrewF  LinkedIn...

    Michael Phillips

    Principal Data Scientist

    Michael began writing and coding machine learning and optimization algorithms in high school, focusing on the stock market and sports analytics. He received a Bachelor's degree in Computer Science from Auburn University before going on to receive a Master of Science in Analytics from Georgia Tech. Michael worked as a graduate research assistant at Georgia Tech, focusing on anomaly detection algorithms for large distributed datasets. Michael has provided key technical leadership to architect and code the type of AI & ML engines that accurately predict failures in operation of heavy assets with significant economic savings.  LinkedIn...


    Join a top team of data scientists and engineers able to tackle enterprise class IIoT problems. Learn from the best from a technical team that has been building IIoT solutions since 2003. We are looking for the best. If you're one of the best then help lead us forward. If interested, contact us via the form below with a description of your interest and skill set.


    Open Positions:

    • Data Scientist skilled in coding with python.
    • Industrial Engineer skilled in statistics, coding
    • Mechanical Engineer (or equivalent) confident with basic coding
    • Full Stack Developer skilled in app/platform development


    Commercializing University Research

    This research is based in the #1 rated Georgia Tech School of Industrial and Systems Engineering. Under the leadership of Dr. Nagi Gebraeel, the research has been underway for 15 years, 25 man-years of combined work. It is centered in four research areas, each bringing unique facets of real world application. It has been integrated into new platform, the Genesis IIoT.

    Analytics & Prognostics Laboratory

    A very unique aspect is the use of an equipment failure test lab, the Analytics and Prognostics Laboratory. It set the stage for using empirical methods to build a new generation of real world algorithms, developed with a systematic approach of measuring actual equipment failure and testing results against predictions. Funded by the National Science Foundation and major industrial partners ensures both real world and highly challenging problems and commensurate results.

  • Contact Us

    We work at the ATDC incubator in Tech Square, Atlanta. We look forward to connecting and exploring how we can bring the power of the IIoT to your operation.