Glory Justin | Engineering | Best Researcher Award

Ms. Glory Justin | Engineering | Best Researcher Award

ย Research assistant/PhD Candidate of Rensselaer Polytechnic Institute, United Statesย 

๐ŸŒŸ Ms. Glory Justin, a Data Scientist and Power Systems expert, is completing her PhD in Electrical Engineering at Rensselaer Polytechnic Institute ๐ŸŽ“. Specializing in AI-driven power grid optimization, she boasts a strong academic and industry background, including roles at GE Global Research and Heliogen. An inspiring leader, she has served as President of the Black Graduate Students Association and Vice President of the Society of Women Engineers. Recognized with awards like the Google Grace Hopper Scholarship, Ms. Justin excels in Matlab, Python, and TensorFlow, driving innovation in power systems and AI research ๐Ÿ”ฌ๐Ÿ’ก.

Professional Profile:

Education๐ŸŽ“

๐ŸŽ“ Ms. Glory Justin is a PhD candidate in Electrical Engineering at Rensselaer Polytechnic Institute, set to graduate in August 2024, with a GPA of 3.75/4.0. She holds an MS in Electrical Engineering from the same institution (May 2022), specializing in Control and Automation with a minor in Power Systems. Previously, she earned her Bachelor of Engineering in Electrical and Electronic Engineering from the Federal University of Technology, Owerri, Nigeria (November 2017), graduating with a GPA of 4.4/5.0 and a concentration in Power System Engineering ๐Ÿ“š๐Ÿ”‹.

 

Professional Experience ๐Ÿ“š

 

๐Ÿ’ผ Ms. Glory Justin has extensive professional experience in power systems and AI. At Rensselaer Polytechnic Institute, she developed AI models for power grid stability. As a Fellow Intern at GE Global Research, she created fast inverter models for hybrid electric power systems โœˆ๏ธ. At Heliogen, she modeled thermal energy storage for solar plants ๐ŸŒž. Additionally, she served as a Teaching Assistant, guiding over 80 students in electrical engineering courses. Her work combines deep technical expertise with practical applications, enhancing efficiency and innovation in the power sector ๐Ÿ”ฌ๐Ÿ’ก.

Research Interest ๐Ÿ”

๐Ÿ”ฌ Ms. Glory Justin’s research interests focus on the intersection of AI and power systems. She specializes in optimizing power grid stability and integrating renewable energy sources ๐ŸŒฑ. Her work includes developing reinforcement learning models to balance frequency in power grids and using deep learning techniques to enhance thermal energy storage systems. Passionate about advancing energy efficiency and reliability, she leverages tools like TensorFlow and Matlab to drive innovations in smart grid technologies. Her goal is to create sustainable and resilient power systems that meet the growing demands of modern energy infrastructures ๐Ÿ’กโšก.

Award and Honor๐Ÿ†

๐Ÿ† Ms. Glory Justin has received numerous prestigious awards and honors throughout her academic career. She earned third prize (Peopleโ€™s Choice) in the Three Minute Thesis Competition in May 2023 and was awarded the Google Grace Hopper Scholarship for Women in Computing in 2021. Additionally, she has been recognized with multiple scholarships, including the Chevron (Agbami) Medical and Engineering Professional Scholarship, ExxonMobil Scholarship, Shell Petroleum Development Company Joint Venture Scholarship, and Nigerian National Petroleum Corporation/Total Scholarship. These accolades highlight her outstanding achievements and dedication to excellence in the field of electrical engineering and AI ๐ŸŒŸ๐ŸŽ“.

 

Research Skills๐ŸŒŸ

๐Ÿ”ฌ Ms. Glory Justin is skilled in leveraging advanced AI techniques for power systems research. Proficient in Matlab, Python, TensorFlow, and PLECs, she develops models for power grid stability and renewable energy integration ๐ŸŒฑ. Her expertise includes reinforcement learning, deep learning, and real-time simulation, enabling her to optimize energy systems effectively. She excels in reducing computational time and improving system efficiency. Additionally, her strong analytical and problem-solving abilities, combined with excellent teamwork and communication skills, make her adept at conducting interdisciplinary research and driving innovation in the field of smart grid technologies ๐Ÿ’กโšก.

Achievements๐Ÿ†

  • ๐ŸŽ“ PhD Candidate in Electrical Engineering at Rensselaer Polytechnic Institute (graduating August 2024)
  • ๐Ÿ’ผ Developed AI models for power grid stability at Rensselaer Polytechnic Institute
  • โœˆ๏ธ Created fast inverter models for hybrid electric power systems at GE Global Research
  • ๐ŸŒž Modeled thermal energy storage for solar plants at Heliogen
  • ๐Ÿ† Third prize (Peopleโ€™s Choice) in the Three Minute Thesis Competition (May 2023)
  • ๐ŸŽ–๏ธ Google Grace Hopper Scholarship for Women in Computing (2021)
  • ๐Ÿ’ก Published multiple research papers in top conferences and journals
  • ๐Ÿ“š Served as President of the Black Graduate Students Association and Vice President of the Society of Women Engineers at RPI
  • ๐Ÿ“œ Earned scholarships from Chevron, ExxonMobil, Shell, and Nigerian National Petroleum Corporation/Total
  • ๐Ÿ”ฌ Proficient in Matlab, Python, TensorFlow, and PLECs for power systems research and AI applications.

Projects๐Ÿ”ฌ๐Ÿ“ˆ

  • ๐Ÿ”‹ Power Grid Stability Optimization: Developed AI models using reinforcement learning to balance frequency in power grids with increased renewable energy at Rensselaer Polytechnic Institute.
  • โœˆ๏ธ Hybrid Electric Power Systems: Established a fast inverter model in PLECs for aircraft hybrid electric power systems at GE Global Research.
  • ๐ŸŒž Thermal Energy Storage: Modeled a thermal energy storage tank prototype for a concentrated solar plant to facilitate product scale-up at Heliogen.
  • ๐Ÿ“š Teaching Assistant Projects: Organized study groups and provided academic support for courses in Electrical Energy Systems, Distributed Systems & Sensor Networks, and Computer Communication Networks at Rensselaer Polytechnic Institute.
  • ๐Ÿ“ˆ Graph Neural Networks for Power Systems: Conducted research on using graph neural networks for real-time small-signal security assessment of power systems.

Publication ๐Ÿ“š

๐Ÿ“˜ ย Real-time Small-Signal Security Assessment Using Graph Neural Networks

  • ๐Ÿ‘ฉโ€๐Ÿ’ผ Authors: Glory Justin, Santiago Paternain
  • ๐Ÿ“… Year: Accepted June 27, 2024
  • ๐Ÿ“– Journal/Conference: Sustainable Energy, Grids and Networks.