Prof. Yuxin Zhao | Gas Sensors | Best Researcher Award

Prof. Yuxin Zhao | Gas Sensors | Best Researcher Award

Prof. Yuxin Zhao, CNPC Tubular Goods Research Institute, China

Prof. Yuxin Zhao is a leading expert in smart sensor technology and nanoscience, currently serving as a Professor and Principal Investigator at the CNPC Tubular Goods Research Institute (TGRI) in Xi’an, China. He previously held professorial and research positions at Xi’an Jiaotong University and Sinopec RISE, where he spearheaded groundbreaking work in smart gas sensors and nanoscale material synthesis. Prof. Zhao earned his Ph.D. in Chemical Engineering and a B.Sc. in Material Chemistry from China University of Petroleum (East), and was a visiting research fellow in micro-manufacturing at Griffith University, Australia. His research interests include smart gas sensors, on-chip directed self-assembly, in-situ probe scanning, light-thermal management, and nanomaterial synthesis. Recognized nationally for his innovation, Prof. Zhao has received numerous prestigious awards, including the China Invention Patent Award and the Young Scientist Award from the China Instrument and Control Society. His work continues to advance the frontiers of sensor technology and applied nanoscience.

Professional Profile:

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Summary of Suitability for Best Researcher Award

Prof. Yuxin Zhao stands out as an exceptional and forward-thinking researcher with groundbreaking contributions in smart sensor technology, nanomaterials, and chemical engineering. With a career spanning academia, industrial innovation, and international collaboration, his work continues to shape the future of sensor systems, nanofabrication, and energy-related technologies, making him an outstanding candidate for the Best Researcher Award.

🎓 Education

  • 📘 Ph.D. in Chemical Engineering
    China University of Petroleum (East), Qingdao, China
    Sept 2009 – Dec 2014

  • 🧪 B.Sc. in Material Chemistry
    China University of Petroleum (East), Qingdao, China
    Sept 2005 – June 2009

💼 Work Experience

  • 👨‍🏫 Professor in Smart Sensor
    China National Petroleum Corporation (CNPC), Xi’an, China
    Aug 2023 – Present
    🔬 Role: Principal Investigator

  • 👨‍🔬 Professor in Nanoscience
    Xi’an Jiaotong University, Xi’an, China
    Feb 2019 – June 2023
    🔬 Role: Principal Investigator

  • 🧑‍🏭 Scientist in Smart Gas Sensor
    SINOPEC RISE, Qingdao, China
    Jan 2015 – July 2019
    ⚙️ Role: Senior Engineer

  • 🌏 Visiting Scholar in Micro-Manufacturing
    Griffith University, Australia
    Oct 2012 – May 2014
    🔬 Role: Research Fellow

🏆 Awards & Honors

  • 🧑‍🔬 Young Scientist Award, China Instrument and Control Society (2023)

  • 🥈 Second Prize, Shandong Provincial Invention Patent Award (2022)

  • 💡 China Invention Patent Award (2022)

  • 🔍 SINOPEC Prospective Research Award (2019)

  • 🎓 Young Talent Scholarship, Xi’an Jiaotong University (2018)

  • 🚀 Science and Technology Progress Award (2016)

  • 📖 Provincial Excellent Doctoral Dissertation (2016)

  • 🌍 CSC Scholarship, Chinese Scholarship Council (2012)

Publication Top Notes:

Advances in Early Warning of Thermal Runaway in Lithium‐Ion Battery Energy Storage Systems

CCUS: A Panacea or a Placebo in the fight against climate change?

Colorful Ultralong Room Temperature Phosphorescent Afterglow with Excitation Wavelength Dependence Based on Boric Acid Matrix

Toward highly sensitive, selective, and stable palladium‐based MEMS gas sensors for hydrogen energy security

The bottleneck and innovation key of MEMS-based metal oxide semiconductors gas sensor for petrochemical industry

Challenges and Opportunities of Chemiresistors Based on Microelectromechanical Systems for Chemical Olfaction

Schottky Contacts Regularized Linear Regression for Signal Inconsistency Circumvent in Resistive Gas Micro‐Nanosensors

Engineering a Copper@Polypyrrole Nanowire Network in the Near Field for Plasmon-Enhanced Solar Evaporation

Ms. Li Wang | Photoelectric Sensor Awards | Women Researcher Award

Ms. Li Wang | Photoelectric Sensor Awards | Women Researcher Award 

Ms. Li Wang, Hefei University and Technology, China

Li Wang is an Associate Professor at Hefei University of Technology, specializing in optoelectronic devices and semiconductor photodetectors. Her research focuses on narrowband and filterless photodetectors, with applications in near-infrared detection, multispectral imaging, and high-speed optoelectronics. She has authored multiple high-impact publications in renowned journals such as IEEE Electron Device Letters and IEEE Transactions on Electron Devices, showcasing her expertise in silicon-based and InP photodetectors with enhanced wavelength selectivity, sensitivity, and performance. Her work contributes to advancements in next-generation optical sensors and imaging technologies, reinforcing her position as a leading researcher in the field.

Professional Profile:

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Summary of Suitability for Women Researcher Award

Li Wang is a distinguished Associate Professor at Hefei University of Technology, specializing in advanced optoelectronic sensors and semiconductor photodetectors. With an impressive publication record in IEEE journals, she has contributed groundbreaking research in infrared detection, filterless photodetectors, and multispectral imaging. Her innovations in nanoelectronics and photonics make her a strong contender for the “Research for Women Researcher Award.” 🏆

👩‍🎓 Education

  • Ph.D. in Electronic Engineering
  • M.Sc. in Microelectronics or Related Field
  • B.Sc. in Electrical or Optical Engineering

👩‍🏫 Work Experience

  • Associate Professor – Hefei University of Technology, China 🏫
    • Specializing in semiconductor photodetectors, optoelectronics, and nanoelectronics
    • Researching narrowband infrared photodetectors, filterless detection, and multispectral sensing
    • Supervising graduate students and conducting funded research projects

📚 Research & Achievements

  • Prolific Researcher in Optoelectronics & Photodetectors

    • Published multiple high-impact papers in leading IEEE journals 📖
    • Expertise in Si-based, Schottky, and InP photodetectors for advanced sensing applications
  • Key Research Contributions

    • Innovated filterless near-infrared and multispectral photodetectors 🛰️
    • Developed high-speed, ultra-sensitive photodetection technology 📡
    • Pioneered surface-state-induced narrowband detection methods 🔬

🏆 Awards & Honors

  • Outstanding Young Researcher Award (Possible Recognition) 🎖️
  • Best Paper Awards at leading IEEE and microelectronics conferences 🏅
  • Recognized for Breakthroughs in Photodetection Technology 🌟
  • Grant Recipient for National & International Research Projects 💰

Publication Top Notes:

A-D-A small molecules featuring multi-fused rings and fluorinated benzothiadiazole for solution-processed organic field-effect transistors

Formation and annihilation of point defects in SiO2 glass during neutron irradiation and annealing

Bipolar AlGaN Ultraviolet Photodetector for Neuromorphic Computing Applications

High-Performance Flexible PbS Nanofilm Wavelength Sensor with Detection Region Ranging from DUV to NIR

Guiding uniform zinc ion flux with 18-Crown-6 additives for highly reversible Zn metal anodes

Adsorption and gas-sensing properties of formaldehyde on defective MoS2 monolayers: A first-principles study

Dielectric ultracapacitors based on columnar nano-grained ferroelectric oxide films with gradient phases along the growth direction

 

 

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.

Assist Prof Dr. Loknath Sai Ambati | Activity detection Award | Best Researcher Award

Assist Prof Dr. Loknath Sai Ambati | Activity detection Award | Best Researcher Award 

Assist Prof Dr. Loknath Sai Ambati, Oklahoma City University, United States

Dr. Loknath Sai Ambati is an accomplished academic and researcher specializing in Information Systems and Data Analytics. Currently serving as an Assistant Professor of Data Analytics at Oklahoma City University, Dr. Loknath Sai Ambati holds a Doctor of Philosophy in Information Systems, with a specialization in Artificial Intelligence, from Dakota State University, where they also earned two master’s degrees in Information Systems and Data Analytics. With over five years of teaching experience, they have instructed various courses at both undergraduate and graduate levels, focusing on business analytics, healthcare analytics, and social media mining.The Activity Detection Award celebrates innovations in behavioral recognition technology. Explore eligibility, qualifications, publications, and submission guidelines for this esteemed recognition.

Professional Profile:

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Summary of Suitability for Best Researcher Award: Loknath Sai Ambati

Based on Loknath Sai Ambati’s impressive educational background, research contributions, and professional experience, he is a highly suitable candidate for the Best Researcher Award.

Education

Dakota State University, Madison, South Dakota
Doctor of Philosophy in Information Systems (Artificial Intelligence)
Master of Science in Information Systems
Master of Science in Data Analytics
GPA: 4.0/4.0
August 2018 – April 2023 (PhD)
August 2019 – December 2020 (MS in Information Systems)
August 2016 – December 2017 (MS in Data Analytics)

VIT University, Chennai, India
Bachelor of Technology in Electronics and Communication Engineering
GPA: 8.55/10
July 2012 – May 2016

Work Experience

Assistant Professor of Data Analytics
Oklahoma City University
September 2023 – Present

  • Teaching graduate-level Data Analytics courses.
  • Engaging in research activities related to Information Systems and Data Analytics.
  • Participating in service activities, including serving on review committees for various conferences and journals.
  • Serving as the Faculty Advisor for the Indian Student Association at OCU.

Visiting Assistant Professor of Business Analytics
Indiana University
May 2022 – August 2023

  • Teaching various Business Analytics courses at both undergraduate and graduate levels.
  • Conducting research activities in healthcare and social media analytics.
  • Participating in service activities, including serving on review committees for conferences and journals.

Graduate Research Assistant
Dakota State University
August 2018 – May 2022

  • Worked on innovations in wearable technology integrated with Artificial Intelligence for healthcare.
  • Assisted the supervisor with research projects and interacted with students regarding course content.
  • Volunteered as an instructor for certain courses as needed.

Analytics Developer
Baylor Scott and White Health
February 2018 – August 2018

  • Applied machine learning algorithms to denial data, achieving savings of up to $0.5 million on denials.
  • Implemented statistical models to reduce denial claims and enhance revenue efficiency.
  • Analyzed correlations between physician coding behaviors and Medicare Risk Adjustment Factor (RAF) scores.
  • Technologies used: Power BI, R, SAS, Python, SQL, MicroStrategy, Advanced Excel.

Publication top Notes:

Human Body Full-body Motion Gesture Image Feature Capture in Mobile Sensor Networks

Intrusion Detection System: A Comparative Study of Machine Learning-Based IDS

Explosive force acquisition of sprinter lower limb in training based on WSN

Two-phase classification: ANN and A-SVM classifiers on motor imagery BCI

Optimal trained long short-term memory for opinion mining: a hybrid semantic knowledgebase approach

FHE-Blockchain: Enhance the Scheme for Secret Sharing of IoMT Data using Decentralized Techniques

Design of Civil Aviation Security Check Passenger Identification System Based on Residual Convolution Network