Dr. Sridhar Patthi | Artificial Intelligence | Best Researcher Award

Published on by Network Awards

Dr. Sridhar Patthi | Artificial Intelligence | Best Researcher Award

Dr. Sridhar Patthi , Marri Laxman Reddy Institute of Technology and Management , India

Dr. Patthi Sridhar is a seasoned academic and researcher currently serving as Professor and Director at Marri Laxman Reddy Institute of Technology and Management in Hyderabad, Telangana State. With a Ph.D. in Electrical and Electronics Engineering from Jawaharlal Nehru Technological University, Hyderabad, his expertise spans across various disciplines including image detection, deep learning for image processing, self-supervised learning, and anomaly detection. He has a rich educational background, holding a Master of Technology in both Computer Science and Engineering from GIET University, Odisha, and in Electrical Power Systems from JNTU Kakinada, Andhra Pradesh. Dr. Sridhar has held progressive academic roles, previously serving as Professor and Dean at Institute of Aeronautical Engineering, Hyderabad. His research focuses on fault detection and diagnosis in electrical systems, power quality, and algorithms for research-oriented projects, reflecting his commitment to advancing technology and education.

Professional Profile:

Orcid

🎓Education:

Dr. Patthi Sridhar is a distinguished academic and researcher currently holding the position of Professor and Director at Marri Laxman Reddy Institute of Technology and Management in Hyderabad, Telangana State. He completed his Ph.D. in Electrical and Electronics Engineering from Jawaharlal Nehru Technological University, Hyderabad. His educational journey includes a Master of Technology in Computer Science and Engineering from GIET University, Odisha, and another Master of Technology in Electrical Power Systems from JNTU Kakinada, Andhra Pradesh.

🏢Work Experience:

Dr. Sridhar’s professional career spans various significant roles in academia. Prior to his current position, he served as Professor and Dean at the Institute of Aeronautical Engineering, Hyderabad, where he also held the position of Head of the Electrical and Electronics Engineering department. Before that, he worked as an Associate Professor and Officer in Charge of Examinations at the same institute.

Publication Top Notes:

  • Adaptive neuro-fuzzy inference system based evolving fault locator for double circuit transmission lines
    • Source: IAES International Journal of Artificial Intelligence
    • Year: 2020
  • Design of power analyzer using LabVIEW
    • Source: Journal of Physics: Conference Series
    • Year: 2020
  • Step-up resonant converter for induction motor drive applications
    • Source: Journal of Physics: Conference Series
    • Year: 2020
  • Determination of stray losses using myDAQ
    • Source: Journal of Engineering and Applied Sciences
    • Year: 2018
  • Interfacing myRIO to control various sensors in electrical applications
    • Source: Journal of Engineering and Applied Sciences
    • Year: 2018

 

 

Dr. Ali Rohan | Artificial Intelligence Awards | Best Researcher Award

Published on by Network Awards

Dr. Ali Rohan | Artificial Intelligence Awards | Best Researcher Award

Dr. Ali Rohan, National Subsea Centre, United Kingdom

👨‍🔬 Dr. Ali Rohan is a versatile researcher and educator in the fields of robotics, artificial intelligence (AI), and computer vision. With a strong academic background including a MSc – PhD in Electrical, Electronics & Control Engineering from Kunsan National University, South Korea, he has delved into various facets of cutting-edge technology. As a Lead Researcher at institutions like the National Subsea Centre in the UK and Dongguk University in South Korea, he spearheaded groundbreaking projects like SeaSense, focusing on underwater visual systems, and DAIRYVISION, revolutionizing livestock farming with AI and machine vision. His expertise spans from real-time implementation of AI for UAVs to structural damage monitoring using AI with UAVs. Dr. Rohan’s contributions extend beyond research, as he has also shared his knowledge as an educator, teaching courses on robotics, data science, and control systems engineering. With a passion for innovation and a dedication to advancing technology, Dr. Rohan continues to make significant strides in shaping the future of AI and robotics. 🤖✨

🌐 Professional Profile:

Scopus

Linkedin

Orcid

Google Scholar

🎓 Education

Ph.D. in Electrical, Electronics & Control Engineering
Department of Control & Robotics Engineering, Kunsan National University, Kunsan, South Korea
(Feb 2016 – Mar 2020)

B.Sc (Hons) in Electrical Engineering
School of Electrical Engineering, The University of Faisalabad, Pakistan
(Oct 2008 – Jul 2012)

🖥️ Technical Competence

  • Areas of Specialization: AI, Machine Learning, Deep Learning, Computer Vision, Robotics, Automation
  • Programming Languages: C, C++, C#, Matlab, Python
  • AI & Machine Learning Libraries: TensorFlow, PyTorch, Scikit-learn, Keras
  • Operating Systems: Windows, Linux, macOS, Robot Operating System (ROS)

🔍 Research Interests :

🤖 Dr. Ali Rohan, an accomplished researcher, specializes in Robotics, Artificial Intelligence (AI), Computer Vision, Automation and Control, Image Processing, Signal Processing, and Machine Learning. His expertise lies in leveraging these domains to innovate solutions for various real-world challenges, from enhancing industrial automation to advancing medical diagnostics. With a keen interest in interdisciplinary research, Ali consistently explores the intersection of these fields to develop cutting-edge technologies with profound societal impacts. 🚀

🔬 Research Experience & Projects

Dr. Rohan has led and contributed to various research projects in areas such as underwater robotics, agricultural monitoring using drones, AI for healthcare, and structural damage detection using UAVs. His work includes projects funded by prestigious bodies like the Net Zero Technology Centre, InnovateUK, and the Australian Research Council.

👨‍🏫 Teaching Experience

Dr. Rohan has taught a range of modules covering topics such as fundamentals of prognostics and health management, robotics, control systems engineering, data science, and power electronics. His teaching expertise spans both theoretical principles and practical applications in engineering and technology.

🏅 Certifications & Awards

Dr. Rohan holds certifications in areas such as Prognostics and Health Management and has received recognition for his contributions to research and academia.

📚 Publication Impact and Citations :

Scopus Metrics:

  • 📝 Publications: 19 documents indexed in Scopus.
  • 📊 Citations: A total of 437 citations for his publications, reflecting the widespread impact and recognition of Dr. Ali Rohan’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 644 📖
    • h-index: 14  📊
    • i10-index: 15 🔍
  • Since 2018:
    • Citations: 629 📖
    • h-index: 14 📊
    • i10-index: 14 🔍

👨‍🏫 A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. 🌐🔬

Publication Top Notes:

 

 

 

Farshad Bolouri | Artificial Intelligence | Best Researcher Award

Published on by Network Awards

Mr Farshad Bolouri: Artificial Intelligence | Best Researcher Award

Research Associate at Texas Tech University, United States

Farshad Bolouri is an accomplished researcher with a Master’s degree in Electrical Engineering from Texas Tech University, specializing in Computer Vision, Machine Learning, Robotic Perception, and Remote Sensing. His research interests focus on Agricultural Robotics, Precision Farming, and Machine Learning in Digital Agriculture.

🌐 Professional Profiles:

🎓 Education : 

Farshad Bolouri, a mastermind in Electrical Engineering, graduated with a Master of Science from Texas Tech University in August ’23 🎓. His stellar GPA of 3.86 reflects his dedication to his studies, with a focus on cutting-edge fields like Computer Vision, Machine Learning, Robotic Perception, and Remote Sensing 🌐🤖.

Prior to his master’s journey, Farshad excelled in his Bachelor’s in Computer Engineering, graduating Summa Cum Laude with a perfect GPA of 4.0 in May ’21 🏆. He added a touch of diversity with a minor in Mathematics and Computer Science, earning accolades such as the Highest Ranking Graduate from the College of Engineering and the ‘Outstanding Design Project’ award from ECE 🏅🔧.

Farshad’s academic journey is not just about grades; it’s a testament to his passion for pushing boundaries and achieving excellence in the realm of technology and engineering 🚀.

🔍 Research Interests : 

Farshad Bolouri’s research interests are a captivating blend of technology and agriculture 🌾. In the realm of Agricultural Robotics and Precision Farming, he’s delving into the development of custom robotic solutions. His focus lies on intelligent multi-sensor integration, aiming to optimize in-field plant phenotyping specifically for specialty crops 🤖🌱. Venturing into the realm of Machine Learning in Digital Agriculture, Farshad applies cutting-edge AI/ML techniques for data interpretation. His goal is to enable accurate high-throughput phenotyping and precise yield estimation, revolutionizing the way we approach modern farming practices 📊🌾. In the domain of 3D Computer Vision for Field Mapping, Farshad employs advanced techniques for accurate and real-time field mapping. By integrating 3D computer vision, he aims to enhance the precision and efficiency of agricultural decision-making processes 🌐🚜.

Research Focus:

Farshad Bolouri’s research focus spans across Agricultural Robotics and Precision Farming 🌾, as evident in his groundbreaking work on “CottonSense.” This High-Throughput Field Phenotyping System leverages intelligent multi-sensor integration for optimized cotton fruit segmentation and enumeration on edge devices, revolutionizing cotton farming practices 🤖🌱. Additionally, his contribution to improving short-term multiphase production forecasts in unconventional tight oil reservoirs showcases a keen interest in merging technology with geoenergy science and engineering ⛽🔍. Farshad’s commitment to advancing phenotyping for flower abortion in soybeans through image analysis and machine learning demonstrates a versatile expertise in the intersection of agriculture, computer vision, and AI 🌺🔬.

Publications Top Notes  :
  • CottonSense: A high-throughput field phenotyping system for cotton fruit segmentation and enumeration on edge devices