Mr. Mehrdad Esmaeilipour | Smart Systems | Best Wearable Sensing Technology Award

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Mr. Mehrdad Esmaeilipour | Smart Systems | Best Wearable Sensing Technology Award 

Mr. Mehrdad Esmaeilipour, Aria Plasma Gostar Pars, Iran

Mehrdad Esmaeilipour is a seasoned Electronics Engineer recognized for his innovative contributions to green technology and environmental sustainability. Currently serving as a Senior Electronics Engineer at Arya Plasma Gostar Pars Company, he leads the development of cutting-edge air purification and water filtration systems that utilize intelligent circuit design and cold plasma technology. He is also the founder and CEO of Parsa Pardazesh Bushehr Sanat Company (PPBS Co.), an electronics and IT enterprise fostering innovation and providing career opportunities for young professionals. His entrepreneurial mindset and passion for social impact led to the invention of a smart bracelet for visually impaired individuals, integrating artificial intelligence to enhance navigation and emergency support. Mehrdad has a solid academic background in electronics engineering from Islamic Azad University and a proven record in project leadership, robotic system development, and patent innovation. He holds multiple patents, including one for a cold plasma-based wastewater treatment system and another for his AI-powered smart wearable. Known for his strong technical expertise, community involvement, and mentorship initiatives, Mehrdad continues to shape the future of sustainable and assistive technology.

Professional Profile:

GOOGLE SCHOLAR

✅ Summary of Suitability

Mehrdad Esmaeilipour exemplifies innovation in wearable sensing technology, with a clear passion for leveraging electronics engineering for social impact and sustainability. His work spans environmental systems, robotics, and digital health, but his standout contribution to wearable sensing lies in the development of a patented smart bracelet for the visually impaired—an AI-powered device designed to enhance real-time navigation and emergency response.

🎓 Education

  • 🧑‍🎓 Bachelor’s Degree in Electronics Engineering Technology
    Islamic Azad University – 📅 Jan 2012

  • 🧑‍🎓 Associate’s Degree in Electronics
    Islamic Azad University – 📅 Jan 2009

  • 🎓 Diploma in Electronics
    Azadegan Technical High School – 📅 Jan 2006

💼 Work Experience

1️⃣ Senior Electronics Engineer

Arya Plasma Gostar Pars Company (Plasma Systems)
📍 Nov 2017 – Present
🔧 Key Responsibilities:

  • 👨‍🔬 Lead circuit production and R&D for purification systems

  • ⚡ Design power, plasma, control, and sensor circuits

  • 🧪 Innovate ICs for air & water purification

  • 🔍 Supervise quality control & team management

  • 📈 Support marketing and product optimization

  • 🌱 Promote environmental sustainability

  • 💻 Tools: Altium Designer, Eagle

🏆 Achievements:

  • 📄 Patent: “Treatment of Spent Caustic and Disulfide Oil Wastewater”

  • 💨 2022: Intelligent Air Purification for Bushehr Province

  • 🌊 2021: Cold Plasma Odor Removal System in Hormuz

  • 🖊️ 2020: Closed Circuit Water System for Pen Factory

  • 💧 2019: Air Purification for Bandar Abbas Stations

  • 🌊 2018: Microbial Sea Water Purification at Persian Gulf University

2️⃣ CEO & Lead Engineer

Parsa Pardazesh Bushehr Sanat Company (PPBS Co.)
📍 Dec 2014 – Present
🔧 Key Responsibilities:

  • 👨‍💼 Team leadership, project planning, and staff development

  • 🧠 Mentorship, skill development, and technical training

  • 🧰 Proficiency in electronics & IT solutions

🏆 Achievements:

  • 🔐 2024: Designed & Secured ImmiEnglish Website

  • 🛡️ 2021: Installed Security Systems at Iran Oxford Academy

  • 📡 2020: Established Telecom & Network Systems

3️⃣ Robotic Team Volunteer

Islamic Azad University – Electrical Department
📍 550 hours, Voluntary Role
🔧 Key Contributions:

  • 🤖 Circuit & sensor integration in robotic systems

  • ⚙️ Implemented PID and advanced control methods

  • 🧑‍🏫 Mentored students and led project teams

🏆 Achievements:

  • 🤖 2025: Robotic Prototype Developed

  • 🛠️ 2024: Advanced Control System Integration

  • 👥 2023: Student Mentorship and Team Development

🏅 Patents, Inventions & Honors

🔬 Patents & Inventions

  1. 🧠 Smart Bracelet for the Visually Impaired
    📍 Intellectual Property Center, Iran
    📅 Nov 2024 | 🌍 International Tier
    🆔 ID: 140350340002004729 | ✅ Code: 456116

  2. 💧 Cold Plasma Sterilizer for Oil & Gas Wastewater Treatment
    🤝 Co-Inventor with Arya Plasma Gostar Pars Company
    📄 Recognized & Under Patent Process

🏆 Honors

  • 🌟 Recognized Emerging Entrepreneur for founding PPBS Co.

  • 👨‍🔧 Lead Engineer on multiple national environmental tech projects

  • 🧑‍🏫 Esteemed mentor and organizer of robotics programs

Publication Top Notes:

Design, Construction and Performance Comparison of Fuzzy Logic Controller and PID Controller for Two-Wheel Balance Robot(Smart Sensors)

Advanced Design,Simulation,Monitoring,Control,and Maitenance Strategies for Photovoltaic Solar Power Systems (BOOK)

Advancements in Cold Plasma Technology for Electronic and Surface Sterilization Applications

Advances and Challenges in Lithium-Ion Battery Technology

Design of an Optimal Proportional-Integral-Derivative Controller Utilizing AI Techniques for Brushless Direct Current Motor with Phase shift. Design of an Optimal Proportional …

Advancements in Cold Plasma Technology for Electronic and Surface Sterilization Applications

Design, Construction and Performance Comparison of Fuzzy Logic Controller and PID Controller for Two-Wheel Balance Robot

An Extensive Optimization Framework for Energy Management within Energy Hubs: A Comparative Analysis of Simulated Multi-Agent Systems, Genetic Algorithms, and Mixed-Integer …

 

 

Dr. Zhiwei Zhang | Deep Learning Awards | Best Researcher Award

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Dr. Zhiwei Zhang | Deep Learning Awards | Best Researcher Award 

Dr. Zhiwei Zhang, AVIC Manufacturing Technology Institute, China

Zhiwei Zhang, is a research engineer specializing in aviation manufacturing technology in China. He holds a bachelor’s and master’s degree in Automation from Shenyang Ligong University and earned his Ph.D. in Instrument Science and Technology from Yanshan University. His research focuses on digital radiographic and industrial CT nondestructive testing, computer vision, and ensemble learning algorithms for additive manufacturing. He has published seven SCI-indexed research papers and holds two authorized patents. Zhiwei Zhang also serves as a reviewer for the Journal of Computational Methods in Sciences and Engineering, reflecting his active contribution to the academic and industrial research community.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award: Zhiwei Zhang

Zhiwei Zhang, a highly skilled research engineer in aviation manufacturing technology, has demonstrated outstanding contributions in the fields of nondestructive testing, computer vision, and ensemble learning for additive manufacturing. His innovative research integrates cutting-edge technologies like digital radiography, industrial CT, and machine learning, addressing critical challenges in the aerospace industry.

🎓 Education

  • 🏫 Bachelor’s Degree in Automation – Shenyang Ligong University

  • 🎓 Master’s Degree in Automation – Shenyang Ligong University

  • 🧪 Ph.D. in Instrument Science and Technology – Yanshan University

💼 Work Experience

  • 👨‍🔧 Research Engineer – Specializing in aviation manufacturing technology in China

  • 🔬 Focus areas include:

    • Digital radiographic and industrial CT nondestructive testing

    • Computer vision

    • Ensemble learning algorithms for additive manufacturing

🏆 Achievements

  • 📄 Published 7 SCI-indexed research papers in high-impact journals

  • 🧾 Granted 2 authorized patents

  • 🧑‍⚖️ Reviewer for the Journal of Computational Methods in Sciences and Engineering

🎖️ Awards & Honors

  • 🏅 Recognized for contributions in nondestructive testing and AI applications in manufacturing
    (Note: Specific award titles not mentioned; can be added if provided.)

Publication Top Notes:

A Hybrid Framework for Metal Artifact Suppression in CT Imaging of Metal Lattice Structures via Radon Transform and Attention-Based Super-Resolution Reconstruction

Complex Defects Detection of 3-D-Printed Lattice Structures: Accuracy and Scale Improvement in YOLO V7

A Prediction Model for Maximum Stress of Additive Manufacturing Lattice Structures Based on Voting-Cascading

Deep convolution IT2 fuzzy system with adaptive variable selection method for ultra-short-term wind speed prediction

An improved meta heuristic IT2 fuzzy model for nondestructive failure evaluation of metal additive manufacturing lattice structure

An improved stacking ensemble learning model for predicting the effect of lattice structure defects on yield stress

Data-driven XGBoost model for maximum stress prediction of additive manufactured lattice structures

Adaptive Defect Detection for 3-D Printed Lattice Structures Based on Improved Faster R-CNN

A Hybrid Model Based on Jensen’s Inequality Theory for 3D Printed Lattice Structures Maximum Stress Prediction

Prof. Din-Yuen Chan | Deep Learning | Best Scholar Award

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Prof. Din-Yuen Chan | Deep Learning | Best Scholar Award 

Prof. Din-Yuen Chan, National Chiayi University, Taiwan

Din-Yuen Chan is a prominent scholar in electrical engineering with extensive experience in visual signal processing and computer vision. He earned his Ph.D. in Electrical Engineering from National Cheng Kung University, Taiwan, in 1996. A member of the Visual Signal Processing and Communication Technical Committee (VSPC TC) since 2010, he served as the founding director of the Department of Electrical Engineering (2007–2011) and as Dean of the College of Science and Engineering at National Chiayi University (2017–2020). His research spans semantic object detection, video/audio coding, stereoscopic 3D, AI-based pattern recognition, and deep learning neural networks. In the past five years, he has published multiple SCI-indexed journal papers on topics such as stereo matching, instance segmentation, speaker diarization, depth estimation, and autonomous robotics. As a frequent corresponding author, he continues to lead innovations in applied AI and multimedia processing.

Professional Profile:

SCOPUS

Summary of Suitability for the Best Scholar Award

Dr. Din-Yuen Chan has maintained an outstanding academic career for over two decades, contributing significantly to the fields of electrical engineering and computer vision. His long-standing commitment to advancing knowledge is reflected in his leadership roles and consistent research output in areas such as semantic object detection, AI-based pattern recognition, video/audio coding, and stereoscopic 3D.

🎓 Education

  • Ph.D. in Electrical Engineering
    National Cheng Kung University, Taiwan 🇹🇼
    Completed in 1996

💼 Work Experience

  • 🧠 Member, Visual Signal Processing and Communication Technical Committee (VSPC TC)
    Since 2010

  • 🏛️ Founding Director, Department of Electrical Engineering, National Chiayi University
    2007 – 2011

  • 🎓 Dean, College of Science and Engineering, National Chiayi University
    2017 – 2020

🧪 Research Interests

  • 🔍 Computer Vision

  • 🎯 Semantic Object Detection

  • 🎞️ Video/Audio Coding

  • 🤖 AI-based Pattern Recognition

  • 🥽 Stereoscopic 3D

  • 🧠 Deep Learning Neural Networks

🏅 Achievements & Honors

  • ✍️ Published multiple SCI-indexed journal papers in high-impact venues, including:

    • EURASIP Journal on Image and Video Processing

    • IET Computer Vision

    • Multimedia Tools and Applications

    • Applied Sciences

  • ⭐ First or corresponding author in many significant papers on stereo matching, depth estimation, 3D object placement, and speaker diarization.

  • 🤖 Developed a low-cost autonomous outdoor robot with end-to-end deep learning navigation.

  • 🧏 Invented a new speaker-diarization technology using spectral-LSTM.

  • 🎓 Recognized leader in academia for establishing and leading research and administrative departments.

Publication Top Notes:

A new speaker-diarization technology with denoising spectral-LSTM for online automatic multi-dialogue recording

Natural-Prosodic Cross-Lingual Personalized TTS

New Efficient Depth Estimation and Real-Time Object 3D Recognition Models for Humanoid Robotic Environment Understanding

Rational 3D object placement based on deep learning based plane detection

INTEGRATED LIGHT-RESNET AND POOLFORMER NETWORKS FOR SHAPE-PRESERVING LANE DETECTION