Ms. Geetika Aggarwal, teesside university, United Kingdom
Dr. Geetika Aggarwal is a Lecturer in the School of Computing, Engineering, and Digital Technologies at Teesside University. She completed her PhD in Electronics and Communication Engineering at Northumbria University, Newcastle Upon Tyne, UK, where she designed a real-time wireless communication system for Electroencephalography (EEG) monitoring. Prior to her current role, Dr. Aggarwal was a Post-Doctoral Researcher at Nottingham Trent University, working on the Horizon 2020 Clean Sky EU project, focusing on Instrumentation and Control, Digital Signal Processing, Data Acquisition, Embedded Systems, Virtual Reality, and Artificial Intelligence using tools such as MATLAB/SIMULINK and LabVIEW. Dr. Aggarwal has received the Outstanding Staff Member Award in 2019 from the Department of Electrical and Electronic Engineering at Northumbria University. Her teaching responsibilities encompass various modules, including Sustainable Systems, Robust Control Systems, and Digital Signal Processing. She is a Fellow of the Higher Education Academy (FHEA), a member of the IEEE and IET, and serves as an Executive Committee Member of the IET Teesside Local Network. Dr. Aggarwal actively engages in research, with an academic profile that includes over 250 citations and a strong commitment to enhancing student learning experiences.
Professional Profile:
GOOGLE SCHOLAR
Suitability of Dr. Geetika Aggarwal for the Research for Women Researcher Award
Dr. Geetika Aggarwal is an exemplary candidate for the Research for Women Researcher Award due to her impressive academic background, diverse research experience, and significant contributions to the field of engineering and technology, particularly in sustainable systems and digital technologies. Her career trajectory reflects a strong commitment to both teaching and research, evidenced by her role as a Lecturer in the School of Computing, Engineering, and Digital Technologies at Teesside University.
🎓 Education
- PhD in Electronics and Communication Engineering
Northumbria University, Newcastle Upon Tyne, England, UK
(Oct 2015 – Oct 2019)
- Research Focus: Designed a real-time wireless communication system for Electroencephalography (EEG) monitoring.
💼 Work Experience
- Lecturer
School of Computing, Engineering, and Digital Technologies, Teesside University
(Nov 1, 2022 – Present)
- Post-Doctoral Researcher
Nottingham Trent University, England, UK
(Nov 2019 – Oct 2022)
- Worked on Horizon 2020 Clean Sky EU project involving:
- Instrumentation and Control 🛠️
- Digital Signal Processing 📊
- Data Acquisition 💻
- Embedded Systems 📡
- Virtual Reality 🕶️
- Artificial Intelligence 🤖
- Tools used: MATLAB/SIMULINK, LabVIEW, Audacity, Adobe Audition, Fusion 360.
🏆 Achievements
- Outstanding Staff Member Award 2019
Department of Electrical and Electronic Engineering, Northumbria University, UK 🌟
- Fellow of Higher Education Academy (FHEA)
Awarded on October 26, 2023 🎓
🏅 Professional Affiliations
- Member of the Institute of Electrical and Electronic Engineers (IEEE) ⚡
- Member of the Institute of Engineering and Technology (IET) ⚙️
- Executive Committee Member of IET Teesside Local Network and University Liaison 🤝
📚 Teaching Responsibilities
- Modules Taught:
- Sustainable Systems and Industry 4.0 🌱
- Sustainability 🌍
- Robust Control Systems (RCS) ⚙️
- Digital Control and Digital Signal Processing (DSP) 📊
- Embedded Systems 💻
- Linear Systems and Control 📏
- Electronic Principles ⚡
- Instrumentation 📏
- Design Implementation 🛠️
Publication Top Notes:
An Approach to Control Electric Automotive Water Pumps Deploying Artificial Neural Networks
Distributed Feature matching for Robust Object Localization in Robotic Manipulation
Intelligent Energy Management across Smart Grids Deploying 6G IoT, AI, and Blockchain in Sustainable Smart Cities
Parallel Implementation of Fuzzy-PID Controllers for Pitch Control of Offshore Wind Turbines
Integrated Operational Planning For Smart Electric Networks in Middlesbrough, UK
PLC & Scada Based Automation for Smart Juice Manufacturing Process