Ms. Elahe Afsharmanesh | Smart Sensors Awards | Best Researcher Award

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Ms. Elahe Afsharmanesh | Smart Sensors Awards | Best Researcher Award 

Ms. Elahe Afsharmanesh, Shahrood University of Technology, Iran

Elahe Afsharmanesh is a Ph.D. candidate in Nano Physics at Shahrood University of Technology, Iran, where she has been conducting research since September 2021. Her doctoral thesis focuses on the study of gas and photo sensing properties of nanostructures and nano-heterostructures based on SnO2, under the supervision of Prof. Hamid Haratizadeh. Elahe holds a Master of Science degree in Solid State Physics from the Islamic Azad University, Science & Research branch, Tehran, where she completed her thesis on the optical and morphological properties of ZnO/CNTs nanocomposites and their application in electrochemical sensors. She graduated with an outstanding GPA of 19.20/20.

Professional Profile:

SCOPUS

Summary of Suitability for the Best Researcher Award

Elahe Afsharmanesh, a Ph.D. candidate in Nano Physics at Shahrood University of Technology, Iran, is an outstanding candidate for the Best Researcher Award due to her exceptional research contributions, academic excellence, and deep involvement in the field of gas/photo sensing and nanomaterials. Her research, particularly on the design and application of metal oxide semiconductor sensors, 2D materials, and nanocomposites, has significant implications for advancing sensor technologies and their real-world applications.

Education:

  • Ph.D. Candidate in Nano Physics
    Sep. 2021 – Present
    Shahrood University of Technology, Shahrood, Iran
    Thesis Title: Study of Gas / Photo Sensing Properties of Nanostructures and Nano-Heterostructures Based on SnO2
    Supervisor: Prof. Hamid Haratizadeh
  • Master of Science in Solid State Physics
    Feb. 2011 – Feb. 2013
    Islamic Azad University, Science & Research Branch, Tehran, Iran
    Thesis Title: Carbon Nanotubes Supporting Effect for Optical and Morphological Properties of ZnO/CNTs Nanocomposite and Its Application in Electrochemical Sensors
    Supervisor: Dr. A. Pahlavan
    GPA: 19.20/20

🔬 Research Interests:

  • Metal Oxide Semiconductor Gas Sensors
  • 2D Materials & Nanocomposite Sensors
  • Fabrication of Wearable & Flexible Sensors
  • E-Nose & Smart Gas Sensors

🛠️ Laboratory Skills:

  • CVD & CBD Synthesis
  • Sputtering & Electrodeposition
  • Spin & Deep Coating
  • Nano Powder Synthesis & Coating
  • Sensor Device Fabrication

đź“š Previous Experience:

  • High School Teacher, Sari, Iran
  • Scientific Member, Student Research Institute, Sari, Iran

Publication top Notes:

Self-powered, highly selective and fast response time ammonia gas sensors based on an rGO/SnO2 nanocomposite

An improved electrochemical sensor based on triton X-100 functionalized SnO2 nanoparticles for ultrasensitive determination of cadmium

Synthesis of CdO nanoparticles using direct chemical precipitation method: Fabrication of novel voltammetric sensor for square wave voltammetry determination of chlorpromazine in pharmaceutical samples

Electrochemical behavior of morphine at ZnO/CNT nanocomposite room temperature ionic liquid modified carbon paste electrode and its determination in real samples

Dr. QingYang Ding | Smart Sensors Awards | Best Researcher Award

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Dr. QingYang Ding | Smart Sensors Awards | Best Researcher Award 

Dr. QingYang Ding, Beijing Union University, China

Ding Qingyang is a lecturer and Master’s Advisor with a distinguished career as a senior machine learning engineer. He earned his Ph.D. from the Central University of Finance and Economics in Beijing, China. An active member of the China Computer Association, the Higher Education Association, and the Blockchain Committee of the China Mobile Communication Association, Ding’s research interests span the smart Internet of Things, blockchain technology and its applications, as well as data mining and analysis. He has successfully led a general science and technology project funded by the Beijing Municipal Education Commission and contributed to several provincial and ministerial projects, including national key research and development initiatives and funding from the National Social Science Fund, Beijing Social Science Fund, and Beijing Natural Science Fund. With over 20 academic publications, one monograph, and applications for three national invention patents and two software copyrights, Ding Qingyang has made significant contributions to his fields of expertise.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Dr. Qingyang Ding is a lecturer and Master’s advisor with a strong academic background and professional experience in machine learning, blockchain, and the Internet of Things (IoT). He earned his Ph.D. from the Central University of Finance and Economics, Beijing, and is actively involved in various professional organizations such as the China Computer Federation and Blockchain Committee of China Mobile Communication Association.

Education:

  • Ph.D. in [specific discipline not mentioned] from the Central University of Finance and Economics, Beijing, China.

Work Experience:

  • Lecturer and Master’s Advisor with a focus on technology and engineering.
  • Senior Machine Learning Engineer with extensive industry and academic experience in AI and data technologies.
  • Professional Member of:
    • China Computer Association
    • Higher Education Association
    • Blockchain Committee of China Mobile Communication Association

Publication top Notes:

A Resource Allocation Algorithm for Cloud-Network Collaborative Satellite Networks with Differentiated QoS Requirements

Impact of Perceived Value and Community Attachment on Smart Renovation Participation Willingness for Sustainable Development of Old Urban Communities in China

Blockchain Empowered Reliable Federated Learning by Worker Selection: A Trustworthy Reputation Evaluation Method

OBBC: A Blockchain-Based Data Sharing Scheme for Open Banking

Permissioned Blockchain-Based Double-Layer Framework for Product Traceability System

Assoc. Prof. Dr. Eugénio Rocha | Smart Sensors Awards | Best Researcher Award

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Assoc. Prof. Dr. Eugénio Rocha | Smart Sensors Awards | Best Researcher Award

Assoc. Prof. Dr. Eugénio Rocha ,University of Aveiro,Portugal

EugĂ©nio Rocha graduated in Computer Science (Artificial Intelligence) from the University of Coimbra in 1994 and earned his Master’s (1998) and PhD (2004) in Mathematics (Nonlinear Control Theory) from the University of Aveiro. He has been an Associate Professor at the University of Aveiro’s Department of Mathematics since 2004. Rocha has served as a member of the Portuguese Mathematical Society Board of Directors and the European Mathematical Society’s Committee on Electronic Publishing. His research spans theoretical and applied mathematics, including Ordinary and Partial Differential Equations, Functional Analysis, and Nonlinear Control Theory, with applications in various fields such as biological systems and nanotechnology. Rocha has coordinated several national and international research projects and received notable awards, including the Portuguese Scientific and Technological Innovation Prize.

Professional Profile:

Scopus

Suitability for the Research for Best Researcher Award: Eugénio Alexandre Miguel Rocha

Eugénio Alexandre Miguel Rocha is a highly suitable candidate for the Research for Best Researcher Award. His exceptional academic qualifications, innovative research contributions, leadership roles, and significant awards reflect his outstanding impact in the field of mathematics and its applications. His broad expertise and contributions to both theoretical and applied aspects of mathematics, along with his active participation in impactful research projects, make him a distinguished candidate deserving of this recognition.

🎓Education:

Eugénio Rocha earned his Bachelor of Science in Computer Science with a focus on Artificial Intelligence from the University of Coimbra in 1994. He then pursued advanced studies at the University of Aveiro, where he completed his Master of Science in Mathematics, specializing in Nonlinear Control Theory, in 1998. Following this, he obtained his PhD in Mathematics, also in Nonlinear Control Theory, from the same institution in 2004.

🏢Work Experience:

Eugénio Rocha has been serving as an Associate Professor in the Department of Mathematics at the University of Aveiro since 2004. Prior to this role, he was an Assistant Professor at the same institution from January 2004 to February 2021. Additionally, he held a position as an Assistant Professor at Universidade de Aveiro from 2013 to 2019.

🏆Awards and Honors:

Eugénio Rocha was awarded the Portuguese Scientific and Technological Innovation Prize, Engo Jaime Filipe in 2019. Additionally, he received a Special Mention for the Innovation Prize in Information Technology and Communication from APDC/Siemens in 2006.

Publication Top Notes:

  • Title: Estimating Data Complexity and Drift Through a Multiscale Generalized Impurity Approach
  • Title: Adaptive Framework for Maintenance Scheduling Based on Dynamic Preventive Intervals and Remaining Useful Life Estimation
  • Title: Robust Mortality Prediction on a Recirculating Aquaculture System
  • Title: The Effect of Delay Techniques on a Lassa Fever Epidemic Model
  • Title: Advancements in Epidemiological Modeling: Bayesian Regularization Neural Networks for Smoke Dynamics