Assoc Prof Dr. Shabana Urooj | Electrical Engineering | Women Researcher Award

Assoc Prof Dr. Shabana Urooj | Electrical Engineering | Women Researcher Award

Associate Professor at Electrical Engineering , Princess Nourah bint Abdulrahman University , Saudi Arabia

👨‍🎓She remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 She successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

  1. Ph.D. in Electrical Engineering (2011) – Department of Electrical Engineering, Jamia Millia Islamia (A Central University) in New Delhi, India. Her thesis was titled “Design & Development of Computer-based Biophysical Model for Diagnosing Pulmonary Edema.”
  2. Master of Technology in Electrical Engineering with specialization in Instrumentation & Control (2003) – Aligarh Muslim University in Aligarh, Uttar Pradesh, India. Her dissertation focused on the “Design of Sub-optimal Controller for Linear Time Invariant System incorporating Sensitivity Considerations.”
  3. Bachelor of Engineering in Electrical Engineering (1998) – Aligarh Muslim University in Aligarh, Uttar Pradesh, India.

Shabana Urooj ‘s citation metrics and indices from Google Scholar are as follows:

  • Cited by: All: 2123, Since 2018: 1488
  • Citations: 2123 (All), 1488 (Since 2018)
  • h-index: 24 (All), 20 (Since 2018)
  • i10-index: 64 (All), 44 (Since 2018)

These metrics showcase the impact of Urooj ‘s work within the academic community, demonstrating the number of citations his publications have received and the influence of his research output.

Research Area(s) & Interests:

Computer-Based Diagnosis of Chronic Diseases and Bio-Medical Instrumentation: Dr. Urooj’s expertise includes the development of computer-based models for diagnosing chronic diseases, particularly in the field of bio-medical instrumentation. Her work likely involves the use of computational tools and techniques to analyze medical data and aid in the diagnosis and monitoring of chronic conditions. Optimization & Control, WSN, BAN: Dr. Urooj’s research interests extend to optimization and control systems, as well as Wireless Sensor Networks (WSN) and Body Area Networks (BAN). This expertise suggests involvement in designing and implementing control algorithms, optimizing system performance, and working with wireless communication technologies in healthcare applications. Material Research, Nanomaterials for Engineering Applications: Dr. Urooj is also engaged in material research, particularly in the area of nanomaterials for engineering applications. Her work likely involves the synthesis, characterization, and application of nanomaterials in various engineering fields, such as electronics, materials science, or biomedical engineering.

Teaching Experience:

Associate Professor at College of Engineering, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia (since 15th September 2019): In her current role, Dr. Urooj serves as an Associate Professor, likely contributing to the academic and research activities of the College of Engineering at Princess Nourah bint Abdulrahman University. Assistant and Associate Professor at the Department of Electrical Engineering, Gautam Buddha University, Gr. Noida, UP, India (6th July 2011 to 13th Sep 2019): Dr. Urooj previously worked as both an Assistant and Associate Professor at Gautam Buddha University. She also served as the Head of the Department of Electrical Engineering from 1st August 2018 to September 2019, demonstrating leadership and administrative skills in addition to her teaching and research responsibilities. Associate Professor at the Department of Electronics & Instrumentation Engineering, Galgotias College of Engineering and Technology, Gr. Noida, UP, India (31st July 2009 to 5th July 2011): Prior to her tenure at Gautam Buddha University, Dr. Urooj worked as an Associate Professor at Galgotias College of Engineering and Technology, where she likely contributed to the academic and research activities of the Department of Electronics & Instrumentation Engineering.

MEMBESRSHIP COUNCILS/COMMITTEES:

• Director: College of Engineering Club- 2022-23, 2023-24
• Member of M. Sc Program in collaboration with Essex University UK.
• Member of B. S IoT in collaboration with College of Computer Science.
• General Co-Chair CCAML2024 Committee
• Track Chair (Special Session) IEEE APSCON 2024

Publications:

Fuzzy clustering algorithm for enhancing reliability and network lifetime of wireless sensor networks

  • Published in Energy in 2020 with 1150citations.

Entropy index in quantitative EEG measurement for diagnosis accuracy

  • Published in Energy in 2013 with 83 citations.

A robust polynomial filtering framework for mammographic image enhancement from biomedical sensors

  • Published in Energy in 2013 with 62 citations.

A composite wavelets and morphology approach for ECG noise filtering

  • Published in Energy in 2013 with 56 citations.

Strategies, current status, problems of energy and perspectives of Yemen’s renewable energy solutions

  • Published in Energy in 2018 with 53 citations.

An improved CAD system for breast cancer diagnosis based on generalized pseudo-Zernike moment and Ada-DEWNN classifier

  • Published in Energy in 2016 with 52 citations.

Non-linear polynomial filters for edge enhancement of mammogram lesions

  • Published in Energy in 2016 with 49 citations.

Human visual system based unsharp masking for enhancement of mammographic images

  • Published in Energy in 2017 with 48 citations.

 

Dr. Ali Jahedsaravani | Electrical Engineering | Best Scholar Award

Dr. Ali Jahedsaravani : Leading Researcher in Electrical Engineering

Assistant Professor at Electrical Engineering, Khatam al Anbiya University, Iran

He remarkable academic journey, extensive research contributions, and dedication to the field of psychology are truly commendable. Your wealth of knowledge and diverse skill set reflect a deep commitment to understanding and addressing critical issues such as bullying, inclusion, and socialization.

🔬 He successful completion of a PhD in Psychology, along with the numerous advanced courses and workshops, showcases your continuous pursuit of excellence and expertise in your field.

🏆 The awards and recognitions, including the First Place in the Poster Award at the University of Stavanger, underscore the impact of your research and the high regard it holds in the academic community.

Professional Profiles:

Education:

Ph.D. in Automation and Control Engineering from the University Putra Malaysia, Malaysia, earned between 2011 and 2015, with a GPA of 3.75 on a scale of 4. MSc in Automation and Control Engineering at Islamic Azad University, Gonabad branch, Iran, completed between 2008 and 2011, with a GPA of 18.28 on a scale of 20. BSc in Electronic Engineering from Islamic Azad University, Iran, Birjand, completed between 2002 and 2007, with a GPA of 14.77 on a scale of 20.

Areas of Interest:

  1. Assistant Professor at the Faculty of Engineering, Khatam al-Anbiya University, from 2018 to the present.
  2. Lecturer at the Faculty of Engineering, Khatam al-Anbiya University, from 2016 to 2018.

Publications:

Measurement of bubble size and froth velocity using convolutional neural networks

Prediction of Froth Flotation Performance Using Convolutional Neural

Recognition of process conditions of a coal column flotation circuit using computer vision and machine learning

Flotation froth image classification using convolutional neural networks

Machine vision based monitoring and analysis of a coal column flotation circuit

An image segmentation algorithm for measurement of flotation froth bubble size distributions

Development of a machine vision system for real-time monitoring and control of batch flotation process

Application of Image Processing and Adaptive Neuro-fuzzy System for Estimation of the Metallurgical Parameters of a Flotation Process