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
- 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.
- 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.
- 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.
- 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.
- 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.
- 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