Anthony S. Deese, Ph.D.
Department Chair and Professor
Department of Electrical and Computer Engineering
The College of New Jersey
[10/2023] Linear Optimization/Programming and Introduction to (Lagrange) Duality
[04/2023] Implicit vs. Explicit Numerical Simulation of System Dynamics
[04/2023] Automatic Differentiation and the Reverse/Adjoint Mode
[08/2022] Advection and Flux Continuity
[06/2022] Introduction to LTSpice
[04/2022] Machine Learning to Solve Ordinary Differential Equations
[04/2022] Convolutional Neural Networks
[02/2022] Runge-Kutta Method (RK4)
[07/2022] React Native Layouts
[07/2021] RESTful APIs and cURL Commands for Twitter Web Application
[07/2020] Bluetooth Low Energy and AutoStart AndroidOS Apps
[01/2020] Particle Photon WiFi Module and AndroidOS API
[11/2019] Arrays and Pointers for C Programming Language
[09/2017] Introduction to Android Studio
[07/2016] Introduction to JavaScript, HTML5, and Web APIs
[08/2016] Custom Java Exceptions
Research Notes for Download
Recent Publications
Communication and Energy Harvesting for Long-Term Geo-Tracking of Large Outdoor Assets using the LPWAN Technologies of LoRa and NB-IoT
The objective of this research is track outdoor assets like construction equipment using a set of custom, durable, low-cost wireless tracking modules that rely on low-power-wide-area network (LPWAN) technologies like LoRa and NB-IoT. Furthermore, these modules should utilize innovative energy harvesting techniques to extend their lifetime and reduce battery requirements.
Most Recent Publication: Link to IEEE Explore
Most Recent Presentation/Video: https://youtu.be/rebGPAx88fI
Smart Wireless Network for Automation of Residential and Commercial Loads to Facilitate Participation in Demand Response Initiatives
In this work, researchers study a smart wireless network for automation of residential and commercial loads that would facilitate their participation in system-wide demand response initiatives. Primary research objectives include: 1) developing a cost-effective and ultra-low power meshed network, 2) developing a learning-based optimization algorithm for load automation, and 3) applying this optimization to demand response.
Most Recent Publication: http://bit.ly/2YhcAC7
Most Recent Presentation/Video: n/a