Haris Mansoor | Electricity Forecasting | Best Researcher Award

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Mr. Haris Mansoor | Electricity Forecasting | Best Researcher Award

Mr. Haris Mansoor, Lahore University of Management Sciences, Pakistan

Inamul Hasan Shaikh is an Associate Professor at the Department of Electrical Engineering, University of Engineering and Technology Taxila, Pakistan πŸ‡΅πŸ‡°. With expertise in optimization and control systems, he’s contributed significantly to research and academia. His work includes tuning optimal hyperparameters of controllers and teaching linear algebra and probability. Inamul has a passion for guiding students and advancing the field of electrical engineering through innovative research. πŸŽ“πŸ”¬

Publication Profile:

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Education:

Haris Mansoor pursued his academic journey in electrical engineering, demonstrating a passion for cutting-edge technology. He earned his Bachelor of Science in Electrical Engineering, specializing in Power, from the University of Engineering and Technology Lahore. Building upon this foundation, he completed his Master’s degree in Control Systems at the University of Engineering and Technology Taxila. Haris’s thirst for knowledge led him to Lahore University of Management Sciences, where he embarked on a PhD in Electrical Engineering, delving into the realms of Machine Learning, Deep Learning, and Optimization under the guidance of Advisor Naveed Arshad. πŸŽ“πŸ”ŒπŸ”¬

 

Experience:

Haris Mansoor’s professional journey reflects a remarkable dedication to advancing technology across diverse fields. As a Senior Deep Learning Engineer at Intelligent Systems Group in Pakistan, he spearheaded numerous projects in Natural Language Processing (NLP), Computer Vision (CV), and Reinforcement Learning (RL), leveraging various AI architectures and algorithms. His tenure as a Graduate Research Assistant at Lahore University of Management Sciences showcased his innovative contributions to Short-Term Load Forecasting algorithms, addressing Pakistan’s energy challenges. Haris’s international collaborations, including stints at King Fahd University of Petroleum and Minerals in Saudi Arabia and Georgia State University in the USA, underscore his global impact in machine learning and beyond. πŸŒπŸ€–πŸ”¬

 

Research Focus:

Haris Mansoor’s research focus primarily revolves around energy forecasting and optimization, with a particular emphasis on Short-Term Load Forecasting (STLF) using advanced techniques such as smart meter data analysis and graph neural networks. His contributions span various domains including machine learning, control systems, and energy economics. Through his work, he aims to address critical challenges in energy infrastructure, improve forecasting accuracy, and optimize resource allocation strategies. Haris’s expertise and dedication in these areas are evident through his numerous publications and citations, demonstrating his commitment to advancing knowledge and technology in the field of electrical engineering. βš‘πŸ”πŸ“ˆ

 

Publication Top Notes:

  1. Short term load forecasting using smart meter data πŸ“Š Cited by: 35, Year: 2019
  2. Short-term load forecasting using AMI dataπŸ”‹ Cited by: 23*, Year: 2023
  3. Fair allocation based soft load shedding πŸ’‘ Cited by: 16, Year: 2021
  4. Past vector similarity for short term electrical load forecasting at the individual household levelπŸ”Œ Cited by: 14, Year: 2021
  5. Impact of missing data imputation on the fairness and accuracy of graph node classifiers πŸ“‰ Cited by: 8, Year: 2022
  6. Genetic algorithm based optimal back stepping controller design for stabilizing inverted pendulum πŸ”„ Cited by: 7, Year: 2016
  7. Genetic algorithm based LQR control of hovercraft πŸ›³οΈ Cited by: 7, Year: 2016
  8. Market model for demand response under block rate pricing πŸ’° Cited by: 4, Year: 2020
  9. Hour-ahead load forecasting using ami data ⏳ Cited by: 3, Year: 2019
  10. An Interactive Educational Tool for Double Spring-Mass-Damper System Analysis & Control 🧬 Cited by: N/A, Year: 2023