Azim Keshtkar

Azim Keshtkar

Title
Adjunct Faculty
Department
Energy Management
Campus
Vancouver
Area(s) of Expertise
Building Automation Systems, Internet of Things (IoT), Energy Forecasting, Electrification
Education Credentials
Ph.D.
Industry Credentials
P.Eng.
Joined New York Tech
2018

Azim Keshtkar received his Ph.D. in 2015 from Simon Fraser University (SFU). His research was focused on developing adaptive learning principles using a synergy of fuzzy logic techniques, wireless sensor capabilities and smart grid incentives to bring forward an adaptable autonomous thermostat for energy management in residential buildings. He has a wide range of industry experience in areas such as electric vehicles, developing low-level hardware/software for internet of things for fleet management, and energy and demand forecasting in smart grid environments.

Selected Publications

  1. A. Keshtkar and S. Arzanpour (2017). An adaptive fuzzy logic system for residential energy management in smart grid environments. Applied Energy, volume186, pp. 68-81, Feb. 2017.
  2. A. Keshtkar and S. Arzanpour (2016). Adaptive residential demand-side management using rule-based techniques in smart grid environments. Energy and Buildings, volume 133, pp. 281-294, Dec. 2016.
  3. A. Keshtkar, S. Arzanpour, F. Keshtkar, and P. Ahmadi (2015). Smart residential load reduction via fuzzy logic, wireless sensors, and smart grid incentives. Energy and Buildings, volume 104, pp. 165-180, Oct. 2015.
  4. A. Keshtkar and S. Arzanpour, (2015). An Autonomous System via Fuzzy Logic for Residential Peak Load Management in Smart Grids. 47th. North American Power Symposium (NAPS), North Carolina, Charlotte, USA, 4-6 Oct. 2015.
  5. A. Keshtkar and S. Arzanpour (2014). Design and Implementation of a Rule-based Learning Algorithm Using ZigBee Wireless Sensors for Energy Management. 27th IEEE Canadian Conference on Electrical and Computer Engineering, pp. 1436-1441, Toronto, Canada, May 2014.
  6. A. Keshtkar and S. Arzanpour (2014). A Fuzzy Logic System for Demand-side Load Management in Residential Buildings. 27th IEEE Canadian Conference on Electrical and Computer Engineering, pp. 266-270, Toronto, Canada, May 2014.

Courses Taught at New York Tech

  • Energy Management, ENGY 610
  • Computer Application for Energy Management, ENGY 730
  • Automated Building Energy Control Systems, ENGY 820

Contact Info