Dr. Rui Yang | Sensor protection Awards | Best Researcher Award

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Dr. Rui Yang | Sensor protection Awards | Best Researcher Award

Dr. Rui Yang, Guilin University of Electronic Technology, China

Rui Yang, Ph.D., is currently a doctoral candidate at the School of Computer and Information Security at Guilin University of Electronic Science and Technology, where he is specializing in deepfake detection. He obtained his Master’s degree from the same university, focusing on small-scale face detection in complex backgrounds. His research interests lie at the intersection of computer vision, machine learning, and multimedia security. Rui has contributed significantly to the field through several publications in prestigious journals, including IEEE Signal Processing Letters and ACM Transactions on Multimedia Computing, Communications, and Applications. His recent works explore advanced techniques in deepfake video detection, image captioning, and unsupervised models. Additionally, he has co-authored papers presented at international conferences, further demonstrating his expertise in applying artificial intelligence to multimedia security. Rui’s innovative contributions aim to enhance the detection and understanding of manipulated digital media.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award:

Rui Yang, a Ph.D. candidate at Guilin University of Electronic Science and Technology, is a promising and accomplished researcher specializing in deepfake detection, with an impressive academic background and significant contributions to the field. His research focuses on cutting-edge techniques in deepfake detection, image captioning, and small-scale face detection, making him highly qualified for the Best Researcher Award.

🎓 Education

  • 2021 – 2024: Ph.D., Guilin University of Electronic Science and Technology, School of Computer and Information Security
    Research direction: Deepfake detection
  • 2018 – 2021: M.E., Guilin University of Electronic Science and Technology, School of Computer and Information Security
    Thesis title: Small-scale Face Detection in Complex Backgrounds
  • 2014 – 2018: B.E., Yibin College, Computer Science and Technology
    Thesis title: Restoration of Gaussian Blurred Images

💼 Work Experience

  • Guilin University of Electronic Science and Technology
    Position: Ph.D. Student and Researcher in Computer and Information Security (Deepfake detection research)
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Dr. Samprit Banerjee | Sensor integration Awards | Excellence in Innovation

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Dr. Samprit Banerjee | Sensor integration Awards | Excellence in Innovation

Dr. Samprit Banerjee, Weill Medical College of Cornell University, United States

Dr. Samprit Banerjee is an Associate Professor of Biostatistics at the Weill Medical College of Cornell University, where he has held various academic appointments since 2011. He currently serves as an Associate Professor in both the Division of Biostatistics and the Department of Psychiatry, as well as the Director of the PhD program in Population Health Sciences. Dr. Banerjee’s expertise lies in biostatistics, data science, and epidemiology, with a focus on statistical methods for health research and healthcare policy. He is also a Special Government Employee at the FDA, contributing to the Center for Devices and Radiological Health. Dr. Banerjee has a distinguished academic background, holding a B.Stat and M.Stat from the Indian Statistical Institute, Kolkata, and a PhD in Biostatistics from the University of Alabama at Birmingham. His teaching experience includes directing multiple graduate-level courses in biostatistics, statistical learning, and big data in medicine. Throughout his career, he has mentored numerous junior researchers and contributed to the development of MS and PhD programs in Biostatistics and Data Science. Dr. Banerjee has also served as an elected representative for the Mental Health Statistics Section of the American Statistical Association.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Excellence in Innovation

Samprit Banerjee, PhD, is highly suitable for the “Research for Excellence in Innovation” award based on his extensive academic background, research contributions, and leadership roles in biostatistics, epidemiology, and data science. His expertise in high-dimensional data analysis, machine learning, and multivariate statistics, combined with his significant contributions to medical and healthcare research, makes him a standout candidate.

Education:

  • 1998-2001: B.Stat (Bachelors in Statistics), Indian Statistical Institute, Kolkata, India
  • 2001-2003: M.Stat (Masters in Statistics), Indian Statistical Institute, Kolkata, India
  • 2003-2008: PhD in Biostatistics, Department of Biostatistics, University of Alabama at Birmingham

Work Experience:

  • Jan 2020 – Present: Associate Professor, Division of Biostatistics, Department of Population Health Sciences, Weill Medical College, Cornell University, New York, NY
  • May 2023 – Present: Associate Professor of Biostatistics, Department of Psychiatry, Weill Medical College, Cornell University, New York, NY
  • Jan 2018 – Jan 2020: Associate Professor, Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Medical College, Cornell University, New York, NY
  • Jan 2018 – Present: Adjunct Associate Professor, Department of Statistics and Data Science, Cornell University, Ithaca, NY
  • Nov 2020 – Present: Director (Founding) of PhD Program in Population Health Sciences, Department of Population Health Sciences, Weill Medical College, Cornell University, New York, NY
  • 2014 – Present: Special Government Employee, Center for Devices and Radiological Health (CDRH), Food and Drug Administration (FDA), Silver Springs, MD
  • 2022 – 2024: Elected Council of Sections Representative for the Mental Health Statistics Section of American Statistical Association (ASA)

Past Positions:

  • 2016 – 2020: Director (Founding) of MS Program in Biostatistics & Data Science, Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Medical College, Cornell University, New York, NY
  • May 2011 – Dec 2017: Assistant Professor, Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Medical College, Cornell University, New York, NY
  • May 2011 – Dec 2017: Adjunct Assistant Professor, Department of Statistical Science, Cornell University, Ithaca, NY
  • Aug 2008 – May 2011: Instructor, Division of Biostatistics and Epidemiology, Department of Public Health, Weill Medical College of Cornell University, New York, NY
  • Jun 2005 – Aug 2008: Graduate Research Assistant, Department of Biostatistics, University of Alabama, Birmingham (Supervisor: Dr. Nengjun Yi) – Developed Bayesian methods for detecting gene by gene and gene by environment interactions for QTLs in inbred mice.
  • Aug 2003 – Jun 2005: Graduate Research Assistant, Department of Biostatistics, University of Alabama at Birmingham (Supervisor: Dr. Varghese George) – Worked on Marginal Structural Models to investigate genetic effects in AIDS and developed Bayesian methods for QTL detection in Human Genetics.

Publication top Notes:

Perioperative comparative effectiveness of anesthetic technique in orthopedic patients

CITED:581

Rearrangements of the RAF kinase pathway in prostate cancer, gastric cancer and melanoma

CITED:556

Mechanism-based epigenetic chemosensitization therapy of diffuse large B-cell lymphoma

CITED:219

Epigenetic repression of miR-31 disrupts androgen receptor homeostasis and contributes to prostate cancer progression

CITED:195

Elevated prefrontal cortex GABA in patients with major depressive disorder after TMS treatment measured with proton magnetic resonance spectroscopy

CITED:156

R/qtlbim: QTL with Bayesian interval mapping in experimental crosses

CITED:153

 

Mrs. Caroline Schio | Sensor-Enhanced Education | Best Researcher Award

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Mrs. Caroline Schio | Sensor-Enhanced Education | Best Researcher Award

Mrs. Caroline Schio, University of Lisbon, Portugal

Caroline Schio is a dedicated researcher and educator specializing in oceanography, environmental education, and agroecosystems. Currently pursuing a PhD in Science Didactics at Universidade de Lisboa, her work focuses on integrating ocean citizenship into basic education through innovative design-based research. With a strong background in socio-environmental education and practical learning, Caroline has led and participated in various research projects, including developing pedagogical models and guides for environmental literacy. Her professional experience spans roles as an educator and president at Instituto Monitoramento Mirim Costeiro in Brazil, and she has contributed to environmental education through numerous publications and conferences. Fluent in Portuguese, English, and Spanish, Caroline is committed to advancing environmental awareness and citizen science.

Professional Profile:

Orcid

Suitability Summary for Best Researcher Award

Researcher: Caroline Schio

Summary:

Caroline Schio is an exemplary candidate for the Best Researcher Award, recognized for her impactful research and dedication to advancing environmental education and oceanography. Her interdisciplinary approach, combining scientific research with practical education, underscores her significant contributions to the field.

🎓Education:

Caroline Schio is currently pursuing a PhD in Science Didactics at Universidade de Lisboa / Instituto de Educação, Portugal, starting in September 2020. She holds a Postgraduate Certificate in Agroecosystems from Universidade Federal de Santa Catarina, Brazil, awarded in April 2015. Additionally, Caroline completed a Postgraduate Certificate in Fisheries Economics and Management from Universitat Autònoma de Barcelona, Spain, in June 2009. Her academic journey began with a Bachelor in Oceanography from Universidade do Vale do Itajaí, Brazil, obtained in December 2007.

🏢Work Experience:

Caroline Schio has been awarded a PhD Scholarship by Fundação para a Ciência e a Tecnologia at Universidade de Lisboa, Portugal, from November 2023 to November 2025. Prior to this, she worked as a Technician for the Programa Maçarico de Literacia do Oceano at CoLab +ATLANTIC, Portugal, from March 2021 to October 2022. Caroline served as both an Educator and President at Instituto Monitoramento Mirim Costeiro in Brazil from February 2018 to February 2023. She also worked as an Editor and Columnist in the Socioenvironmental Area at Jornal da Praia, Brazil, from July 2011 to December 2012. Earlier in her career, Caroline volunteered as a Researcher at Parque Nacional Manuel Antônio in Costa Rica from December 2006 to February 2007 and worked as an Environmental Educator at Instituto Ambiental Kat Schürmann, Brazil, from December 2005 to March 2006.

Publication Top Notes:

  • Design of a Pedagogical Model to Foster Ocean Citizenship in Basic Education
  • Cultura Oceânica para a Economia Azul
  • Ocean Literacy for the Blue Economy
  • Criaturas da Barra e das Demais Praias da Região de Garopaba-SC
  • Monitoramento Mirim Costeiro

 

 

 

 

Ms. Xinlu Bai | Sensing Awards | Best Researcher Award

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Ms. Xinlu Bai | Sensing Awards | Best Researcher Award

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.

Publication Top Notes:

Title: Dense Pedestrian Detection Based on GR-YOLO

 

 

 

Dr. Hebat-Allah S. Tohamy | Chemical sensors | Best Researcher Award

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Dr. Hebat-Allah S. Tohamy | Chemical sensors | Best Researcher Award 

Dr. Hebat-Allah S. Tohamy, National Research Centre, Egypt

Dr. Hebat-Allah Sarhan Abd-Allah Tohamy, born on November 17, 1989, in Egypt, is an accomplished chemist with a strong academic and professional background. She earned her B.Sc. in Chemistry and Biochemistry with honors in 2011 and her M.Sc. in Organic Chemistry in 2017 from Helwan University. She completed her Ph.D. in Organic Chemistry in 2020 at the same institution, focusing on the preparation, characterization, and applications of carbon allotropes derived from agricultural wastes. Since 2012, Dr. Tohamy has been affiliated with the National Research Center’s Cellulose and Paper Department, where she has gained extensive experience in cellulose chemistry, nanomaterials, sustainability, and drug delivery systems. She has conducted scientific missions in Prague and has been involved in numerous research projects and international collaborations. Her work has earned her recognition, including the best M.Sc. thesis award at the National Research Centre in 2017. Dr. Tohamy is also a member of professional organizations such as the Egyptian Society of Polymer Science and Technology and the Organization for Women in Science for the Developing World (OWSD).

Professional Profile:

ORCID 

 

SCOPUS

 

Education:

  • Ph.D. in Organic Chemistry
    Faculty of Science, Helwan University, 2020
    Thesis Title: Preparation, characterization, and applications of carbon allotropes derived from agricultural wastes
  • M.Sc. in Organic Chemistry
    Faculty of Science, Helwan University, 2017
    Thesis Title: Preparation, characterization, and applications of cellulose-based amphiphilic materials
  • B.Sc. in Chemistry and Biochemistry
    Faculty of Science, Helwan University, 2011
    Graduated with Very Good with honors (among the top ten students)

Work Experience:

  • Teaching Assistant with Ph.D.
    Chair of Erosion and Torrent Control, Department of Ecological Engineering for Soil and Water Resources Protection, University of Belgrade – Faculty of Forestry, June 2022 – Present
    Responsible for teaching and research activities related to erosion control and soil and water conservation.
  • Teaching Assistant
    Chair of Erosion and Torrent Control, Department of Ecological Engineering for Soil and Water Resources Protection, University of Belgrade – Faculty of Forestry, April 2016 – June 2022
    Assisted in teaching and research, focusing on erosion control and ecological engineering.
  • Volunteer and Demonstrator
    University of Belgrade – Faculty of Forestry, November 2015 – April 2016
    Gained practical experience in teaching and laboratory work, contributing to various projects in ecological engineering.
  • Researcher
    National Research Center (NRC), Cellulose and Paper Department, since 2012
    Conducted extensive research in cellulose chemistry, recycling agricultural wastes, sustainability, kinetics, thermal analysis, hydrogels, nanomaterials, and amphiphilic polymers. Specialized in carbon-based materials, graphene oxide, carbon nanotubes, carbon quantum dots, drug delivery, water treatment, adsorption, and sensors.

Publication top Notes:

Biodegradable carboxymethyl cellulose based material for sustainable/active food packaging application

Fluorescence ‘Turn-on’ Probe for Chromium Reduction, Adsorption and Detection Based on Cellulosic Nitrogen-Doped Carbon Quantum Dots Hydrogels

Antibacterial activity and dielectric properties of the PVA/cellulose nanocrystal composite using the synergistic effect of rGO@CuNPs

Potential application of hydroxypropyl methylcellulose/shellac embedded with graphene oxide/TiO2-Nps as natural packaging film

Applications of propolis-based materials in wound healing

Oil dispersing and adsorption by carboxymethyl cellulose–oxalate nanofibrils/nanocrystals and their kinetics