Assist. Prof. Dr. Nashwan Ali | Electrode Sensor | Best Researcher Award

Assist. Prof. Dr. Nashwan Ali, University of Samarra, France

Dr. Nashwan Hussein Ali is an analytical chemist with expertise in electrochemistry, petroleum chemistry, and water analysis. He earned his Ph.D. (2015), M.Sc. (2012), and B.Sc. (2009) in Analytical Chemistry from Tikrit University, Iraq. Currently, he is an Invited Researcher at the University of Poitiers, France, focusing on electrochemical activity mapping of Pt-CeO₂ gradient films. He previously served as an Assistant Professor at the University of Samarra and a Lecturer at Hayat Private University. With extensive experience in analytical techniques such as HPLC, GC-FID, and spectroscopy, he has also worked as an analytical chemist in the petrochemical industry.

Professional Profile:

ORCID

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Summary of Suitability for Best Researcher Award

Dr. Nashwan Hussein Ali has a strong research background in analytical chemistry, electrochemistry, and petroleum chemistry. His extensive experience as a researcher and lecturer, along with multiple publications in peer-reviewed journals, makes him a suitable candidate for the Best Researcher Award.

🎓 Education:

📜 Ph.D. in Analytical Chemistry – Tikrit University, Iraq (2012 – 2015)
🧪 Master of Science in Analytical Chemistry – Tikrit University, Iraq (2009 – 2012)
⚛️ Bachelor of Science in Chemistry – Tikrit University, Iraq (2005 – 2009)

💼 Work Experience:

🔬 Invited Researcher (Apr 2022 – Present)
- University of Poitiers, UFR SFA, Equipe SAMCat – IC2MP UMR CNRS 7285, France
- Research Topic: Electrochemical activity mapping of Pt-CeO₂ gradient films using bipolar electrochemistry
- Supervised by Prof. ZIGAH Dodzi
🎓 Assistant Professor (Dec 2016 – Apr 2022)
- University of Samarra, College of Applied Science, Iraq
- Taught:
  - 🧪 Analytical Electrochemistry (Master’s students)
  - 📘 General Chemistry (Undergraduate)
  - 🌱 Green Chemistry (Undergraduate)
📖 Lecturer (Dec 2013 – Feb 2016)
- Hayat Private University for Science and Technology (HPUST), Erbil, Iraq
- Taught:
  - ⚗️ Analytical Chemistry (Undergraduate)
  - 🌿 Green Chemistry (Undergraduate)
🏭 Analytical Chemist (Apr 2011 – Jan 2014)
- Arab Company for Detergent Chemicals (ARADET), Baiji Refinery
- Conducted chemical analysis for petroleum and water samples using advanced techniques such as HPLC, GC-FID, GC/MS, Karl Fischer titration, UV-Vis spectroscopy.
- Performed quality control on crude oil properties and industrial water treatment.

🏆 Achievements, Awards & Honors:

🏅 Recognized Researcher in Electrochemistry and Analytical Chemistry
📖 Published Scientific Papers in reputable journals on Electrochemical Methods, Green Chemistry, and Petroleum Analysis
🏆 Academic Excellence Awards for contributions to teaching and research in Analytical Chemistry
🎤 Speaker & Presenter at international conferences in Electrochemistry and Green Analytical Methods

Publication Top Notes:

High-Performance ZIF-7@PANI Electrochemical Sensor for Simultaneous Trace Cadmium and Lead Detection in Water Samples: A Box–Behnken Design Optimization Approach

Spectrophotometric Determination of Captopril in Pharmaceutical Formulations based on Ion-Pair Reaction with the Red Congo

Synthesis and characterization of some new Indazolone and Carbohydrazide derivatives from azachalcones

Determination of loperamide HCL in pharmaceutical preparations using modified lon selective electrode

Determination of metoclopramide in pharmaceutical commercial using flow injection chemiluminescence technique

Ms. Xinlu Bai, Changchun university, China

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, following an Engineering Degree from Zhengzhou University of Finance and Economics (2018-2022). Xinlu has made significant contributions to the field of computer vision, particularly in dense pedestrian detection. His research includes the development of the GR-YOLO algorithm, which improves detection performance over existing methods like YOLOv8, with notable advancements in accuracy across various datasets. Xinlu’s work has been published in Sensors and has been guided by esteemed professors Deyou Chen and Nianfeng Li. He has been recognized for his excellence in competitions, winning the first prize in the Jilin Province Virtual Reality Competition, the second prize in the China Virtual Reality Competition (Data Visualization Track), and the third prize in the Jilin Province Ruikang Robot Competition.

Professional Profile:

Orcid

Suitability Summary for Best Researcher Award

Researcher: Xinlu Bai

Summary:

Xinlu Bai is a highly qualified candidate for the Best Researcher Award, distinguished by his innovative research and significant contributions to the field of computer science, particularly in pedestrian detection technology. Bai’s work demonstrates a clear commitment to advancing technology through rigorous research and practical applications.

🎓Education:

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, which he has been enrolled in since 2023. He previously completed his Engineering Degree at Zhengzhou University of Finance and Economics, where he studied from 2018 to 2022. Xinlu has made significant contributions to the field of computer vision, particularly in dense pedestrian detection. His development of the GR-YOLO algorithm, which enhances detection performance compared to YOLOv8, has been recognized through publications in Sensors and has been guided by esteemed professors Deyou Chen and Nianfeng Li. His excellence has been acknowledged in various competitions, including winning the first prize in the Jilin Province Virtual Reality Competition, the second prize in the China Virtual Reality Competition (Data Visualization Track), and the third prize in the Jilin Province Ruikang Robot Competition.

🏆Awards:

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, having previously completed his Engineering Degree at Zhengzhou University of Finance and Economics. His contributions to computer vision, particularly through the development of the GR-YOLO algorithm, have been published in Sensors and guided by Professors Deyou Chen and Nianfeng Li. Xinlu’s excellence in the field has been recognized with several prestigious awards: he won the First Prize in the Jilin Province Virtual Reality Competition, the Second Prize in the China Virtual Reality Competition (Data Visualization Track), and the Third Prize in the Jilin Province Ruikang Robot Competition.