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Justin Grammens

Instructor

Software Engineering and Data Science

  • Education
  • Master of Software Systems, University of Saint Thomas
    Graduate Certificate in Unix, C and C++, University of Minnesota
    BA – Applied Math and Physics, Augsburg University
  • Expertise
  • Internet of Things, Machine Learning (TensorFlow & PyTorch ), Artificial Intelligence, TinyML, Arduino, Microcontrollers, Native Mobile Applications (Android, iOS), Cloud Computing (AWS, Azure or Google Cloud), Programming Languages (Java, Python, Ruby, C, C++ ), Agile Software Development Process

Mr. Grammens graduated with a BA from Augsburg University in 1996 and completed his Masters in Software Systems at the University of Saint Thomas in 2005. He has worked in companies of all sizes and is a serial entrepreneur having founded and had multiple exits in technology companies over his career. He is currently the Founder and CEO of Lab651 and Recursive Awesome. At both companies, Mr. Grammens is the creator, producer, and host of the AppliedAI Podcast which allows him to interview some of the world's leading experts on Artificial Intelligence & Machine Learning, and the co-founder of the 501(c)(3) non-profit Emerging Technologies North which oversees the Applied AI Meetup. He is the Co-founder of Captovation - an easy-to-use Artificial Intelligence platform that uses NLP and Computer Vision to help presenters improve their skills by providing them with audio and visual analytics to pinpoint areas that could be strengthened. Justin is an avid runner having completed multiple marathons, enjoys giving back by presenting at conferences, and being a lifelong learner, reading books on a wide variety of subjects. Most importantly, Justin is blessed to have a loving wife and two amazing boys who are the light of his life and keep him strong and centered.

Reach out and schedule a time to connect with Justin at JustinGrammens.com

 


Internet of Things
IoT with Machine Learning

Shared file system predictive storage techniques Shared file system predictive storage techniques
Code42 US Patent Number: 9727423 · Issued Aug 8, 2017

System for a Distributed File System Element CollectionSystem for a Distributed File System Element Collection
Code42 US Patent Number: 9053124 · Issued Jun 9, 2015

Monitoring And Management Of Lost ProductMonitoring And Management Of Lost Product
US Patent:20110040660 · Issued Aug 10, 2010

Monitoring And Management Of Lost ProductMonitoring And Management Of Lost Product
US Patent 20110040660 · Filed Aug 10, 2010

IoT Weekly News - Subscribe to hand-picked articles by Justin Grammens on the Internet of Things and Artificial Intelligence of Things. Published and delivered to your Inbox every Wednesday. Free Forever.

TinyML - Tiny machine learning is broadly defined as a fast-growing field of machine learning technologies and applications including hardware, algorithms and software capable of performing on-device sensor data analytics at extremely low power, typically in the mW range and below, and hence enabling a variety of always-on use-cases and targeting battery-operated devices.

TensorFlow - TensorFlow is an end-to-end open-source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.