Mr. Naseer Ahmed | Accelerator Award | Excellence in Innovation

Mr. Naseer Ahmed | Accelerator Award | Excellence in Innovation 

Mr. Naseer Ahmed, Pakistan Atomic Energy Commission, Pakistan

Naseer Ahmed is an Electrical Power and Control System Engineer specializing in FPGA-based control systems for switch-mode power supplies. He holds a B.Sc. in Electrical Engineering from The Islamia University Bahawalpur (IUB) and an M.S. in Systems Engineering from the Pakistan Institute of Engineering and Applied Sciences (PIEAS). Since 2012, he has been serving as a Senior Engineer at the Pakistan Tokamak Plasma Research Institute, where he works on Verilog and VHDL programming for FPGA-based control systems, logic simulation, and PCB design using Altium. His expertise includes FPGA reconfigurable design, offering flexibility and precision in system development.

Professional Profile:

ORCID

Summary of Suitability for Excellence in Innovation

Naseer Ahmed demonstrates strong expertise in electrical power and control systems, with a particular focus on FPGA-based control systems for switch-mode power supplies. His experience at the Pakistan Tokamak Plasma Research Institute and his contributions to fusion engineering, high-voltage DC sources, and spherical tokamak studies highlight his research excellence.

🎓 Education:

📍 BSc. Electrical EngineeringThe Islamia University Bahawalpur (IUB) (2007–2011)

  • 📍 Location: Islamabad, Pakistan

  • 🏆 Grade: A

📍 MS Systems EngineeringPakistan Institute of Engineering and Applied Sciences (PIEAS) (2020–2022)

  • 📍 Location: Islamabad, Pakistan

  • 📊 CGPA: 3.18

💼 Work Experience:

👨‍💻 Senior EngineerPakistan Tokamak Plasma Research Institute (Aug 2012 – Present)

  • 🔹 Verilog HDL programming and logic simulation for Altera FPGAs using Quartus II software.

  • 🔹 VHDL programming on ISE and Vivado Design Suites for Xilinx FPGAs.

  • 🔹 PCB Design & Development on Altium for FPGA-based control cards.

🏅 Achievements, Awards & Honors:

🌟 Expertise in FPGA-based control systems for switch-mode power supplies.
🌟 Successfully developed custom FPGA control solutions for advanced electrical systems.
🌟 Contributed to high-impact research in Tokamak Plasma Research using FPGAs.
🌟 Strong background in C programming, VHDL, and PCB design for embedded applications.

Publication Top Notes:

Design and development of FPGA based trigger system for automation of metallic tokamak (MT-I)

An Inverter-Fed Cockcroft-Walton Multiplier Based High Voltage DC Source for Tokamak

Start-Up Studies of GLAST-III Spherical Tokamak in the Presence of Poloidal Field

Ms. Geetika Aggarwal | Next Generation Awards | Women Researcher Award

Ms. Geetika Aggarwal | Next Generation Awards | Women Researcher Award 

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:
    1. Sustainable Systems and Industry 4.0 🌱
    2. Sustainability 🌍
    3. Robust Control Systems (RCS) ⚙️
    4. Digital Control and Digital Signal Processing (DSP) 📊
    5. Embedded Systems 💻
    6. Linear Systems and Control 📏
    7. Electronic Principles ⚡
    8. Instrumentation 📏
    9. 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

 

 

Assoc Prof Dr. Hongfei Yang | Wayfinding Award | Best Researcher Award – 5015

Assoc Prof Dr. Hongfei Yang | Wayfinding Award | Best Researcher Award 

Assoc Prof Dr. Hongfei Yang, Shihezi University, Xinjiang, China

Yang Hongfei is an Associate Professor in the Department of Electronic Information Engineering at Shihezi University, specializing in Testing and Measurement Technology and Instruments. Born in September 1994 in Puyang, Henan, he has a robust academic background, holding a PhD from Jilin University, where he also completed his master’s and bachelor’s degrees in Mechanical Design. His academic journey includes a significant joint training exchange program at the University of Cambridge. Yang’s research interests focus on intelligent agriculture machinery and intelligent sensors, reflecting his commitment to innovative solutions in engineering. He has received several prestigious awards, including the National Scholarship for Doctoral Students and the title of “Outstanding Graduate Student” from Jilin University. Proficient in multiple software tools and with strong language skills, Yang is dedicated to fostering collaboration within academic circles and engaging in impactful scientific research. His aspiration is to excel as a university educator while contributing significantly to the field of instrumentation and technology.

Professional Profile:

Scopus 

Summary of Suitability for Best Researcher Award: Yang Hongfei

Candidate Profile: Yang Hongfei, an associate professor at Shihezi University, specializes in Testing and Measurement Technology and Instruments. With a strong academic background, including a PhD from Jilin University and a joint training program at the University of Cambridge, Yang has consistently demonstrated excellence in research and education.

Education:

  • 2020.09 – 2023.09: PhD in Testing and Measurement Technology and Instruments, Jilin University
  • 2018.10 – 2019.01: Joint Training Exchange Master’s Program, University of Cambridge
  • 2017.09 – 2020.06: Master’s in Mechanical Design and Theory, Jilin University
  • 2012.09 – 2016.06: Bachelor’s in Mechanical Design, Manufacturing and Automation, Dalian University

Work Experience:

  • 2023.11 – Present: Associate Professor, Department of Electronic Information Engineering, Shihezi University

Publication top Notes:

Neural network-based 3D point cloud detection of targets in unstructured environments

MI-FPD: Magnetic Information of Free Precession Signal Data Measurement Method for Bell-Bloom Magnetometer

Efficient Measurement of Free Precession Frequency in Bell-Bloom Atomic Magnetometers

EHA-YOLOv5: An Efficient and Highly Accurate Improved YOLOv5 Model for Workshop Bearing Rail Defect Detection Application

RT-FPS: Relaxation Time of Free Precession Signal Measurement Method for Bell-Bloom Magnetometer

Gabriel Danciu | Intelligent sensing | Excellence in Research

Mr. Gabriel Danciu | Intelligent sensing | Excellence in Research

Lecturer at Transilvania University, Romania

Danciu Gabriel is a prominent researcher and educator from Romania, specializing in electrical engineering and computer science. Currently serving as a Şef lucrări at the University of Transilvania in Brașov, he combines his academic role with practical experience as an engineer and manager at Siemens. With a robust publication record exceeding 50 papers, Gabriel is recognized for his contributions to artificial intelligence, image processing, and software architecture. He is an active member of the IEEE and has presented at numerous international conferences. His commitment to education is reflected in his mentoring roles and project coordination, making him a vital part of the academic community. Gabriel’s expertise in developing algorithms for RGB-D cameras and his innovative research approaches have earned him respect in the field. He aims to bridge theoretical knowledge with practical applications, enhancing technological advancements and shaping the next generation of engineers.

Profile:

Google Scholar Profile

Strengths for the Award:

  1. Extensive Experience: Gabriel has over 15 years of experience in academia and industry, demonstrating a strong commitment to both education and research.
  2. Publication Record: With over 50 published works, he shows a robust contribution to fields such as AI, image processing, and software architectures, indicating high productivity and impact in his research area.
  3. Diverse Skill Set: His competencies in various programming languages (C++, C#, Python) and expertise in software architecture showcase his technical proficiency, which is critical for modern research.
  4. Leadership Roles: As a Şef lucrări (Head of Department) and an engineer at Siemens, he has proven leadership capabilities, indicating his ability to manage projects and mentor others effectively.
  5. International Engagement: Participation in over 5 European projects and presentations at numerous conferences reflects his active engagement with the global research community.
  6. Research Innovation: His focus on cutting-edge topics like AI and image processing highlights his relevance and adaptability to current technological trends.

Areas for Improvement:

  1. Language Proficiency: While he is proficient in English, improving his German skills could enhance his collaboration opportunities in Europe, particularly in multilingual environments.
  2. Broader Collaboration: Expanding his research network beyond existing affiliations could lead to more interdisciplinary projects and greater innovation.
  3. Public Engagement: Increasing visibility through popular science publications or community outreach could enhance his impact beyond the academic sphere.
  4. Mentoring: Actively seeking to mentor younger researchers or students could foster new talent in the field and enhance his leadership profile.

Education:

Danciu Gabriel pursued his academic journey at the University of Transilvania in Brașov, where he obtained his Bachelor’s degree in Automatică și Informatică Industrială in 2004. He continued his studies at the same institution, completing a Master’s degree in Electrical Engineering and Telecommunications in 2006. Gabriel then earned his Ph.D. in 2014, focusing on developing algorithms for image processing using RGB-D cameras. His educational background laid a solid foundation for his future roles in academia and industry. As an Asistent universitar from 2007 to 2022, he dedicated himself to teaching and research, culminating in his current position as Șef lucrări, where he engages in educational leadership, research activities, and administrative duties. Gabriel’s academic achievements are complemented by ongoing professional development, ensuring that he stays at the forefront of technological advancements and educational methodologies in his field.

Experience:

Danciu Gabriel boasts extensive professional experience spanning over 15 years in both academia and industry. He began his career as a Software Engineer at Dynamic Ventures from 2005 to 2017, where he focused on research, mentorship, and software development. In 2018, he transitioned to Siemens as an Engineer, Researcher, and Manager, where he continues to work on innovative research projects while mentoring emerging talent. Concurrently, he has held various academic positions at the University of Transilvania, serving as an Asistent universitar for 15 years before advancing to Şef lucrări in 2022. His dual role allows him to integrate theoretical knowledge with practical applications, contributing to the growth of his students and the advancement of technology. Gabriel’s experience is characterized by a commitment to education, research innovation, and leadership, positioning him as a key figure in the fields of electrical engineering and computer science.

Research Focus:

Danciu Gabriel’s research primarily revolves around artificial intelligence, image processing, and software architecture, with a specific emphasis on RGB-D cameras. His work in developing innovative algorithms for depth image analysis has significantly contributed to advancements in computer vision and signal processing. Gabriel has published over 50 papers in renowned journals and conferences, exploring various topics, including noise pollution monitoring, functional verification in digital designs, and object tracking methods. He actively participates in European projects, collaborating with interdisciplinary teams to address real-world challenges through technology. Gabriel is passionate about integrating theoretical concepts with practical applications, aiming to improve the efficiency and accuracy of image processing techniques. His ongoing research endeavors focus on enhancing machine learning models and exploring new avenues in automated systems, positioning him at the cutting edge of technological innovation in the fields of engineering and computer science.

Publication Top Notes:

  • Shadow removal in depth images morphology-based for Kinect cameras 🌌
  • Objective erythema assessment of Psoriasis lesions for PASI evaluation 🌿
  • A novel approach for face expressions recognition 😊
  • Improved contours for ToF cameras based on vicinity logic operations 🖼️
  • Cost-efficient approaches for fulfillment of functional coverage during verification of digital designs 💻
  • Coverage fulfillment automation in hardware functional verification using genetic algorithms 🔍
  • Extended control-value emotional agent based on fuzzy logic approach 🤖
  • Scale and rotation-invariant feature extraction for color images of iris melanoma 🌈
  • Level up in verification: Learning from functional snapshots 📊
  • Noise pollution monitoring using mobile crowd sensing and SAP analytics 📱
  • Debugging FPGA projects using artificial intelligence 🧩
  • Debug FPGA projects using machine learning 📈
  • Efficient analysis of digital systems’ supplied data ⚙️
  • Method proposal for blob separation in segmented images 🔍
  • Solutions for Roaming and Interoperability Problems Between LTE and 2G or 3G Networks 📶
  • Methods of Object Tracking 🕵️‍♂️
  • Adaptive Scaling for Image Sensors in Embedded Security Applications 🔒
  • A method proposal of scene recognition for RGB-D cameras 🌍
  • Genetic algorithm for depth images in RGB-D cameras 🔧
  • Hierarchical contours based on depth images 🗺️

Conclusion:

Gabriel Danciu demonstrates a strong profile as a candidate for the Best Researcher Award, with a solid foundation in research, a wealth of experience, and a proven track record of publications and collaborations. By addressing the suggested areas for improvement, particularly in broader engagement and mentorship, he could further strengthen his candidacy and impact in the research community.