NZE-AI

About Me

Dr. Zeinab Teimoori, P.Eng.
Assistant Professor at Thompson Rivers University

Email: zteimoori@tru.ca
Phone: (250) 828-5107
LinkedIn:

Education

Ph.D. in Software Engineering Lakehead University, Canada (2020-2024)
M.Sc. in Software Engineering: Multimedia Systems University of Tehran, Iran (2015-2018)
B.Sc. in Software Engineering Shariaty Technical University, Iran (2011-2015)

Research Interests

AI
Machine Learning
Smart Cities
Intelligent Transportation Systems
Quantum Computing

Research Projects

Digital Twin Cold-Climate Heat Pump Analysis

A Regime-aware physics-informed Digital Twin for cold-climate heat pump performance prediction

DT ML Energy Sustainablity

AI Performance in AEV

Performance analysis of AI systems in autonomous vehicles.

AI ML AEV Analysis

Smart Building Energy Management

AI-enabled smart and sustainable energy ecosystem for TRU Campus buildings

AI Energy Sustainablity

Global Triple Mitigation AI-Based Plan

Restore the atmosphere’s natural ability to clean itself and slow climate warming much faster.

AI ML Global Warming GHG Emission

Teletechnovision in Pollution

TIP is implemented as the capability layer to enable sensing, data collection, spatial analysis and community feedback.

IoT Environment Sustainability

Optimized EV Energy Management

Accurate battery SoC estimation to mitigate range anxiety and optimize energy consumption in electric vehicles.

AI ML Energy

Mobile Charging Stations

Enhanced recommendation system combining fixed and mobile charging stations for optimal EV charging solutions.

AI Optimization Smart Grid

Electric Bus Management

Load balance optimization for intelligent public transport systems using AI-driven scheduling and routing.

AI Transportation Optimization

EV Path Planning

AI-powered navigation considering real-time road conditions, obstacles, and safety parameters for optimal routing.

AI Navigation Safety

LLM-Assisted Smart EV

Leveraging Large Language Models for adaptive recommendations and natural communication in electric vehicles.

LLM NLP AI

EV Federated Learning

Energy source recommendation using hybrid federated and transfer learning models for improved accuracy.

Federated Learning ML Privacy

Quantum ML for E-bus

Hybrid quantum computing machine learning SoC risk classification for fleet charging request management.

Quantum Computing ML Classification

Intelligent Transportation System Standards Analysis

Review and analysis of the current Canadian Standards to improve the performance of the Intelligent Transportation Systems.

Canadian Standards Transportation Smart Grids

Research Team

Current Members

Graduate Research Assistant

• Asmita Bashyal
Data Science Department
• Vaishnav Petre
Data Science Department
• Buhimila Golani Mboja
Environmental Science Department

Undergraduate Research Assistants

Past Members

Graduate Research Assistants

• Gursahib Singh
Computing Science Department / 2026
• Thamalee Dasanayake
Computing Science Department / 2026

Undergraduate Research Assistants

•
• Brock Young
Department of Engineering / 2026
• Isaac Latta
Department of Engineering / 2026
• Victor Okorie
Department of Engineering / 2025

Publications

Google Scholar Profile

2026 - A Hybrid Quantum–Classical Learning and Knowledge Distillation Framework for Electric Bus Charging Risk Prediction and Coordination (IEEE OA ITS - Submitted)
2026 - Performance Analysis of AI Systems in Autonomous Vehicles: A Review (SN Signal, Image and Video Processing - Submitted)
2026 - TSF for IoT-enabled environmental systems integrating capabilities, enabling conditions, safeguards, and net environmental outcomes (SN Discover IoT)
2026 - A Comprehensive Review on Electric Vehicles: Technologies, Performance Optimization, and the Role of Quantum Computing (Energies)
2026 - Intelligent Transportation System Charging Infrastructure: Standards Analysis (2nd ICIET)
2026 - The G2C-DTP Pipeline: A Case Study of Safe and Performant Large-Scale Data Migration Between Modern Distributed Storage Systems (2nd ICIET)
2026 - Teletechnovision in Pollution: A Communication-Driven IoT Framework for Urban Air Quality Decision Support(2nd ICIET)
2025 - LLM-Enabled EV Charging Stations Recommendation (arXiv)
2024 - Deep Transfer Learning for Detecting EVs Energy Parameters (IEEE TAI)
2024 - Smart Vehicles Recommendation System for AI Communication (IEEE TCE)
2024 - User-centric EV Charging Recommendation (IEEE MELECON)
2024 - EV Charging Source Recommendation System (NRC STEM Symposium)
2024 - Mobile Charging Profit Optimization (IEEE TCE)
2022 - Intelligent EV Energy Management Systems Review (Sustainability)
2022 - Secure Cloudlet Charging with FL (IEEE TII)
2022 - Detecting Review Spammers in Social Media (JADM)