Dr. Yue Wang | Sensor development Award | Best Researcher Award

Dr. Yue Wang | Sensor development Award | Best Researcher Award 

Dr. Yue Wang, University of Science and Technology Liaoning, China

Dr. Yue Wang is an Associate Professor at the School of Chemical Engineering at the University of Science and Technology Liaoning in China. He earned his Bachelor’s degree from the University of Science and Technology Anshan and both his Master’s and Doctorate degrees from the University of Science and Technology Liaoning and Saitama Institute of Technology, Japan, respectively. Since joining the University of Science and Technology Liaoning in 2006, Dr. Wang has focused his research on sensors and biosensors, biofuel cells, supercapacitors, energy harvesting, and artificial muscles. His work has resulted in over 60 published scientific papers, garnering approximately 600 citations, reflecting his significant contributions to the field. Dr. Wang has secured multiple research grants from various institutions, including the Education Department of Liaoning Province and the Natural Science Foundation of Liaoning Province, to advance his projects on conductive sensors, pesticide sensors, electrochemical biosensors, and wearable smart sensing technologies. Additionally, he completed a visiting scholarship at the University of Texas at Dallas in 2019-2020, further enhancing his academic and research expertise.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award: Yue Wang

Yue Wang is an exemplary candidate for the Best Researcher Award, primarily due to his substantial academic qualifications, extensive research contributions, and impactful work in the field of Material Science, specifically within sensor and biosensor technologies.

Education

  • Bachelor’s Degree in Material Science
    University of Science and Technology Anshan, China
    September 1998 – July 2002
  • Master’s Degree in Material Science
    University of Science and Technology Liaoning, China
    September 2003 – March 2006
  • Ph.D. in Material Science
    Saitama Institute of Technology, Japan
    April 2008 – March 2011

Work Experience

  • Associate Professor
    University of Science and Technology Liaoning, China
    April 2006 – Present
  • Visiting Scholar
    University of Texas at Dallas
    April 2019 – March 2020

Publication top Notes:

A carbon black–doped chalcopyrite–based electrochemical sensor for determination of hydrogen peroxide

Glucose oxidase, horseradish peroxidase and phenothiazine dyes-co-adsorbed carbon felt-based amperometric flow-biosensor for glucose

Crab gill–derived nanorod-like carbons as bifunctional electrochemical sensors for detection of hydrogen peroxide and glucose

Cellulose-derived hierarchical porous carbon based electrochemical sensor for simultaneous detection of catechol and hydroquinone

A triphenylamine based fluorescent probe for Zn2+ detection and its applicability in live cell imaging

1,8-naphthalimide-triphenylamine-based red-emitting fluorescence probes for the detection of hydrazine in real water samples and applications in bioimaging in vivo

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:

SCOPUS

 

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