Dr. Longbin Jin | Signal Processing Awards | Best Researcher Award

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Dr. Longbin Jin | Signal Processing Awards | Best Researcher Award 

Dr. Longbin Jin, Konkuk University, South Korea

Longbin Jin, is a Ph.D. candidate in Computer Science at Konkuk University, Korea, with an expected graduation in February 2025. His research focuses on adaptive visual prompting for video action recognition in vision-language models under the guidance of Professor Eun Yi Kim. He holds a Master’s degree in Smart ICT Convergence and a Bachelor’s degree in Mechanical Engineering & Automation from Shanghai University, China. Throughout his academic career, Longbin has received numerous accolades, including winning the ICASSP 2023 SPGC Challenge and multiple Excellence and Encouragement Prizes at the Korea Software Congress. Currently, he serves as an AI Researcher at Voinosis in Seoul, where he develops AI models for early detection of hearing loss and cognitive impairment in the elderly. He is also an instructor at Konkuk University, teaching courses on Artificial Intelligence, Computer Vision, and Machine Learning. His project experience includes collaborations on medical imaging and virtual reality, demonstrating his expertise in applying AI technologies across diverse fields. Longbin is proficient in English, Chinese, and Korean, reflecting his international background and commitment to advancing technology in healthcare and education.

Professional Profile:

GOOGLE SCHOLAR

Research for Community Impact Award: Longbin Jin’s Suitability

Longbin Jin is a highly qualified candidate for the Research for Community Impact Award due to his significant contributions in the fields of artificial intelligence and healthcare, particularly in projects that directly benefit the community.

📚 Education

  • Ph.D. in Computer Science
    Konkuk University, Korea
    Expected: February 2025
    Thesis: Adaptive Visual Prompting for Video Action Recognition in Vision-Language Models
    Advisor: Prof. Eun Yi Kim
  • M.S. in Smart ICT Convergence
    Konkuk University, Korea
    Graduated: August 2020
    Thesis: E-EmoticonNet: EEG-based Emotion Recognition with Context Information
    Advisor: Prof. Eun Yi Kim
  • B.S. in Mechanical Engineering & Automation
    Shanghai University, China
    Graduated: August 2018

💼 Work Experience

  • AI Researcher
    Voinosis, Seoul, Korea
    December 2022 – Present

    • Researcher on AI models for early detection of hearing loss and cognitive impairment based on voice analysis for the elderly (VoiceCheck & BrainGuardDoctor Apps).
  • Instructor
    Konkuk University, Seoul, Korea
    March 2022 – Present

    • Teaching courses on Computer Vision, Artificial Intelligence, and Machine Learning.
  • AI Engineer
    Lulla, Seoul, Korea
    October 2022 – November 2022

    • Main researcher for an AI model for a child face-matching system to assist kindergarten teachers (Lulla App).

🏆 Achievements, Awards, and Honors

  • Winner of ICASSP 2023 SPGC Challenge: Multilingual Alzheimer’s Dementia Recognition through Spontaneous Speech (First Author) 🥇
  • Excellence Prize, Korea Software Congress 2023 🥇
  • Encouragement Prize, ACM Student Research Competition, Computer Human Interaction 2020 (First Author) 🎖️
  • Excellence Prize, Korea Software Congress 2019 (First Author) 🏅
  • Encouragement Prize, Korea Software Congress 2019 (First Author) 🎖️
  • Excellent Presentation, International Conference on Culture Technology 2018 🌟

Publication Top Notes:

Interpretable Cross-Subject EEG-Based Emotion Recognition Using Channel-Wise Features†

CITED:29

Consen: Complementary and simultaneous ensemble for alzheimer’s disease detection and mmse score prediction

CITED:15

Eeg-based user identification using channel-wise features

CITED:7

E-EmotiConNet: EEG-based emotion recognition with context information

CITED:2

Emotion Recognition based BCI using Channel-wise Features

CITED:1

 

Dr. Shuaa Alharbi | Deep learning Awards | Women Researcher Award

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Dr. Shuaa Alharbi | Deep learning Awards | Women Researcher Award 

Dr. Shuaa Alharbi, Qassim University, Saudi Arabia

Shuaa S. Alharbi is an Assistant Professor at the College of Computer Science, Qassim University, Saudi Arabia. She holds a B.Sc. and M.Sc. in Computer Science from Qassim University, and a Ph.D. in Computer Science from Durham University, UK. Her research expertise lies in machine learning, deep learning, and image processing, particularly in the biomedical domain. She specializes in developing novel deep learning architectures and techniques for analyzing medical images to enhance diagnostic accuracy. Her work focuses on curvilinear structure extraction and bioimage informatics, and she has published impactful research in esteemed journals, including Signal, Image and Video Processing and Methods. Dr. Alharbi has also contributed extensively to academic committees, curriculum development, and postgraduate supervision, reflecting her dedication to education and research excellence.

Professional Profile:

ORCID

 Suitability for the Women Researcher Award

Dr. Shuaa S. Alharbi has demonstrated substantial contributions in computer science, with a focus on machine learning, image processing, and medical image analysis. Her research is interdisciplinary, addressing key challenges in the fields of bioimage informatics, medical diagnostics, and AI-based deep learning applications. These align with global priorities in health technology and AI-driven innovation.

🎓 Education

  • B.Sc. in Computer Science (2007)
    📍 Qassim University, Saudi Arabia
  • M.Sc. in Computer Science (2014)
    📍 Qassim University, Saudi Arabia
  • Ph.D. in Computer Science (2020)
    📍 Durham University, United Kingdom
    🧑‍💻 Specialization: Bioimage Informatics, Machine Learning, and Image Processing

💼 Work Experience

  • Teaching Assistant (2008-2016)
    📍 Qassim University – College of Computer Science
  • Lecturer (2016-2020)
    📍 Qassim University – College of Computer Science
  • Assistant Professor (2020–Present)
    📍 Qassim University – College of Computer Science
  • Administrative Roles:
    • E-Content Supervisor (2020-2022)
    • IT Department Coordinator (2020-2022)
    • Member of various academic and examination committees

🏆 Achievements, Awards, and Honors

  • Published Research:
    • 📘 Sequential Graph-Based Extraction of Curvilinear Structures (2019)
      🔗 Signal, Image, and Video Processing Journal
    • 📘 The Multiscale Top-Hat Tensor (2019)
      🔗 Methods Journal
  • Research Contributions:
    🌟 Expertise in machine learning, deep learning, and medical image processing
    🌟 Development of novel architectures for analyzing curvilinear structures in biological and medical images
  • Committee Memberships:
    🏅 Standing Committees in the Scientific Council (2023-2024)
  • Supervision:
    🎓 Postgraduate Supervisor at the College of Computer Science

🌟 Areas of Interest

  • Machine Learning & Deep Learning 🤖
  • Medical Image Analysis 🏥
  • Computer Graphics and Signal Processing 🎨

Publication Top Notes:

Arabic Speech Recognition: Advancement and Challenges

Date Fruit Detection and Classification Based on Its Variety Using Deep Learning Technology

Exploring the Applications of Artificial Intelligence in Dental Image Detection: A Systematic Review

E-DFu-Net: An efficient deep convolutional neural network models for Diabetic Foot Ulcer classification

Integration of machine learning bi-modal engagement emotion detection model to self-reporting for educational satisfaction measurement

Dr. Cazac Alin Marian | Material Science awards | Best Researcher Award

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Dr. Cazac Alin Marian | Material Science awards | Best Researcher Award 

Dr. Cazac Alin Marian, Gheorghe Asachi Technical University of Iasi, Romania

Alin Marian Cazac is a Romanian academic and researcher specializing in materials engineering and industrial safety. he holds a Ph.D. in Materials Science and Engineering from the Gheorghe Asachi Technical University of Iași, where he is currently a Lecturer in the Faculty of Materials Science and Engineering, Department of Materials Engineering and Industrial Safety. His academic journey includes a Master’s degree in Occupational Safety and Health Engineering and a Bachelor’s degree in Industrial Safety Engineering, both from the same institution.

Professional Profile:

ORCID

Summary:

Cazac Alin Marian’s academic accomplishments, impactful publications, and leadership in groundbreaking research projects position him as an outstanding candidate for the “Best Researcher Award.” His work not only advances materials science but also contributes significantly to industrial safety and innovation, making him deserving of such recognition.

📚 Education

  • Doctorate (Ph.D.) in Material Science and Industrial Safety Engineering
    2011 – 2016
    Gheorghe Asachi Technical University of Iași

    • Faculty of Material Science and Industrial Safety Engineering
  • 🎓 Bachelor’s Degree in Industrial Safety Engineering
    2013 – 2016
    Gheorghe Asachi Technical University of Iași

    • Faculty of Material Science and Industrial Safety Engineering
  • 🎓 Master’s Degree in Occupational Safety and Health Engineering
    2013 – 2015
    Gheorghe Asachi Technical University of Iași

    • Faculty of Material Science and Industrial Safety Engineering
  • 📜 Certified Risk Assessor in Occupational Safety and Health
    2014
    Gheorghe Asachi Technical University of Iași
  • 🏆 Certified Specialist in Occupational Safety and Health
    2013
    S.C. METATECH-EDUCATION S.R.L. Iași
  • 👨‍🏫 Certified Trainer
    2013
    S.C. RODIS EDUCATION S.R.L., Iași
  • 🦷 Diploma in Dental Technology
    2007 – 2010
    Grigore T. Popa University of Medicine and Pharmacy Iași
  • 🎓 High School Diploma with Financial and Economic Certification
    2001 – 2005
    Technical College, Rădăuți, Suceava

💼 Professional Experience

  • 🔬 Lecturer
    2021 – Present
    Gheorghe Asachi Technical University of Iași

    • Faculty of Material Science and Industrial Safety Engineering
  • 🧑‍🏫 Assistant Professor (Dr. Eng.)
    2016 – 2021
    Gheorghe Asachi Technical University of Iași
  • 🦷 Dental Technician
    2007 – 2010
    Grigore T. Popa University of Medicine and Pharmacy Iași

🏅 Achievements, Projects, and Publications

  • 🌟 Member of Funded Projects:
    • Advanced Surface Technologies for Automotive Components (2012-2017)
    • Thermal Spray Technology Transfer for Magnetic Coatings on Plastic Materials (2017)
    • Corrosion-Resistant Ni-Cr Coatings Development (2018)
    • ROSE Program for Successful University Integration (2019)
  • 📖 Publications:
    • Co-author of over 40 scientific papers, including oral presentations at international conferences, focused on material science and industrial safety engineering.

🌟 Awards and Honors

  • 🏆 Research Fellow Scholarship (MECTS) during doctoral studies
  • 🎓 Recognition for Contribution to International Scientific Conferences
  • 📜 Certificates in Safety Engineering and Risk Assessment

Publication Top Notes:

Microstructural and Mechanical Properties Analysis of Phosphate Layers Deposited on Steel Rebars for Civil Constructions

Comparative Biomechanical Analysis of Kirschner Wire Fixation in Dorsally Displaced Distal Radius Fractures

Investigation of CuTi Alloy for Applications as Non-Sparking Material

Electrochemical Corrosion Resistance of Al2O3–YSZ Coatings on Steel Substrates

Mechanical Properties and Wear Resistance of Biodegradable ZnMgY Alloy

Juan Carlos Antolin Urbaneja | Vision Sensing | Best Researcher Award

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Dr. Juan Carlos Antolin Urbaneja | Vision Sensing | Best Researcher Award

Dr. Juan Carlos Antolin Urbaneja, TECNALIA, Basque Research and Technology Alliance, BRTA, Spain.

Juan Carlos Antolín Urbaneja is a Senior Researcher at TECNALIA, part of the Basque Research & Technology Alliance (BRTA). With over 25 years of experience in robotics and automation, Juan Carlos specializes in 3D vision, 3D reconstruction, robotized inspection, and image analysis. He has worked on diverse technologies, including surface treatment, water quality identification, robots, and additive manufacturing. His contributions extend to various industrial sectors such as biomedical, automotive, and aeronautical, where he develops custom software and hardware solutions. He has led numerous public and private research projects and co-authored a European patent.

Professional Profile

ORCID

Suitability of Juan Carlos Antolín Urbaneja for the Best Researcher Award

Juan Carlos Antolín Urbaneja, I believe he is highly suitable for the Best Researcher Award. He has successfully managed and executed around 40 research projects, including both public and private funding, indicating a strong ability to drive innovative research initiatives.

Education 🎓

Juan Carlos holds a degree in Industrial Engineering with an electrical specialty (2000) from Bilbao Faculty of Engineering, Basque Country University. He also completed a degree in Innovation and Technology Management (2004) from Deusto Faculty (ESIDE). His academic journey culminated in a Ph.D. in Control Engineering, Automation, and Robotics from the University of the Basque Country in 2017. This foundation in engineering and management has propelled him into an influential career in robotics and automation, blending theoretical knowledge with practical applications in cutting-edge technologies.

Experience 💼

With a robust career spanning 25 years, Juan Carlos has been deeply involved in the research, development, and execution of advanced robotic systems. He has participated in over 40 projects, both public and private, and has contributed significantly to the development of innovative machines used in various industries. His expertise includes electrical and electronic design, where he applies programming tools like Matlab-Simulink and LabVIEW. Juan Carlos is also a peer reviewer and co-author of scientific papers, contributing to the field’s growth. His notable contributions include robotic inspection systems and advanced additive manufacturing techniques.

Research Interests 🔬

Juan Carlos’s research interests are centered around robotics, automation, and additive manufacturing. His work explores the development of systems for robotized inspection and 3D scanning, with applications in large-scale parts inspection and dimensional qualification. He is particularly interested in enhancing the capabilities of robots to interact with complex materials and environments, such as biomedical and automotive sectors. His research also spans innovations in wave energy and surface treatment, continuously striving for breakthroughs that bridge the gap between theoretical research and practical industrial solutions.

Awards 🏆

Juan Carlos has received numerous accolades throughout his career. He is the recipient of more than 20 awards, including recognition for his contributions to robotics, automation, and innovation. His work in additive manufacturing and robotized inspection has earned him widespread recognition in scientific communities. As a testament to his contributions, he was nominated for several prestigious awards, including the Distinguished Scientist Award and the Outstanding Scientist Award. These honors reflect his excellence in both research and industrial applications, highlighting his impact on technological advancements.

Publications Top Notes📚

Automated MOLDAM Robotic System for 3D Printing: Manufacturing Aeronautical Mould Preforms

Robotized 3D Scanning and Alignment Method for Dimensional Qualification of Big Parts Printed by Material Extrusion

Experimental Characterization of Screw-Extruded Carbon Fibre-Reinforced Polyamide: Design for Aeronautical Mould Preforms with Multiphysics Computational Guidance

Coordination of Two Robots for Manipulating Heavy and Large Payloads Collaboratively: SOFOCLES Project Case Use

Robot Coordination: Aeronautic Use Cases Handling Large Parts

 

Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

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Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

Dr. Akmal Jahan Mohamed Abdul Cader, South Eastern University, Sri Lanka.

Dr. Akmal Jahan Mohamed Abdul Cader is a distinguished academic and researcher currently serving as a Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka. With extensive experience in higher education, he is a Visiting Research Fellow at QUT, Australia. His research interests include artificial intelligence, data science, and document image analysis. Dr. Cader has published numerous high-impact articles and is actively involved in academic development and curriculum design. He is committed to advancing education and research in the field of computer science. 📚💻🌍

Publication Profiles 

Googlescholar

Education and Experience

  • Visiting Research Fellow – QUT Momentum Visiting Fellow, QUT, Australia (2021 – Present) 🎓
  • Senior Lecturer (Computer Science) – South Eastern University of Sri Lanka (2020 – Present) 🏫
  • Sessional Academic – School of Electrical Engineering & Computer Science, QUT (2016 – 2019) 📖
  • Lecturer (Computer Science) – South Eastern University of Sri Lanka (2012 – 2015) 🧑‍🏫
  • Assistant Lecturer – South Eastern University of Sri Lanka (2010 – 2012) 🔍
  • Demonstrator in Computer Science – South Eastern University of Sri Lanka (2009 – 2010) 👨‍🔬

Suitability For The Award

Dr. Mac Akmal Jahan Mohamed Abdul Cader, Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka, is a highly accomplished academic and researcher, making him an exemplary candidate for the Best Researcher Award. With a career spanning over a decade, Dr. Cader has consistently demonstrated leadership in research, teaching, and academic development, particularly in the fields of artificial intelligence, computer science, and digital technologies. His research contributions, coupled with his active involvement in academic service, professional organizations, and international collaborations, solidify his standing as a leading figure in his domain.

Professional Development

Dr. Cader has participated in several professional development programs focused on effective communication, teaching and learning, and project-based learning. He has completed various certifications at QUT, enhancing his skills in pedagogy and curriculum development. His commitment to continuous improvement in education is evident in his active engagement in workshops and training sessions aimed at promoting best practices in teaching. As a Fellow of the Higher Education Academy, he champions high standards in academic instruction and student engagement. 🏅📈📚

Research Focus

Dr. Cader’s research primarily focuses on artificial intelligence, data science, and document image analysis. He explores the synthesis and application of synthetic metals, aiming to develop innovative solutions in electronics and energy storage. His work on TCNQ chemistry has significant implications for biotechnology and medicine, including the construction of electrochemical sensors and drug delivery systems. By synthesizing novel compounds, he contributes to advancements in both theoretical and practical aspects of computer science and materials research. 🔬⚙️🌐

Awards and Honors

  • Senate Honours Award for High Impact Publications – SEUSL (2022 & 2023) 🏆
  • Queensland University of Technology Postgraduate Award (QUTPRA) (2015) 📜
  • Faculty Write Up (FWU) Scholarship – QUT, Australia (2019) 📚
  • Effective Communication in Teaching and Learning – QUT, Australia (2019) 🗣️
  • Foundation of Teaching and Learning – QUT (2018) 🎓

Publication Top Notes 

  • Locating tables in scanned documents for reconstructing and republishing | Cited by: 46 | Year: 2014 📄🔍
  • Plagiarism Detection on Electronic Text based Assignments using Vector Space Model (ICIAfS14) | Cited by: 37 | Year: 2014 📊✏️
  • AntiPlag: Plagiarism Detection on Electronic Submissions of Text Based Assignments | Cited by: 34 | Year: 2014 📄🛡️
  • Plagiarism detection tools and techniques: A comprehensive survey | Cited by: 23 | Year: 2021 🔎📚
  • Fingerprint Systems: Sensors, Image Acquisition, Interoperability and Challenges | Cited by: 11 | Year: 2023 🖐️📷
  • Contactless finger recognition using invariants from higher order spectra of ridge orientation profiles | Cited by: 10 | Year: 2018 ✋📏
  • Accelerating text-based plagiarism detection using GPUs | Cited by: 10 | Year: 2015 ⚡💻
  • Contactless multiple finger segments based identity verification using information fusion from higher order spectral invariants | Cited by: 9 | Year: 2018 🖐️🔗

Tetiana Starodub | Synthetic Metals | Best Researcher Award

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Tetiana Starodub | Synthetic Metals | Best Researcher Award

Dr. Tetiana Starodub,Institute of Chemistry, Jan Kochanowski University in Kielce, Poland.

Dr. Tetiana Starodub is an accomplished chemist specializing in synthetic metals and coordination chemistry. She graduated with honors from the National University of Vasyl Karazin and later pursued advanced research at the Institute of Technology in Karlsruhe, Germany. Currently an assistant professor at the Institute of Chemistry of the Jan Kochanowski University in Kielce, Poland, Dr. Starodub focuses on the synthesis and testing of 7,7′,8,8′-tetracyanoquinodimethane (TCNQ) derivatives for applications in electronics, biotechnology, and medicine. Her innovative research contributes significantly to modern materials science. 🎓🔬📚

Publication Profiles 

Scopus
Orcid

Education and Experience

  • 1998: Graduated with honors from the National University of Vasyl Karazin in Kharkov, Ukraine. 🎓
  • 1998-2000: Began education at the Theoretical and Organic Chemistry Department of KhNU. 📖
  • 2000-2001: Worked in laboratories at the Institute of Technology in Karlsruhe, Germany. 🏭🇩🇪
  • 2000-2014: Conducted research on isotrithionedithiolate transition metal complexes and TCNQ anion-radical salts. 🔬
  • 2018-Present: Assistant Professor at the Institute of Chemistry, Jan Kochanowski University, Kielce, Poland. 👩‍🏫🇵🇱

Suitability For The Award

Dr. Tetiana Starodub, Assistant Professor at the Institute of Chemistry, Jan Kochanowski University, Kielce, Poland, is a highly deserving candidate for the Best Researcher Award due to her significant and ongoing contributions to the fields of synthetic metals, organic and coordination chemistry, and the development of innovative materials for modern electronics, biotechnology, and medicine. With an extensive career in scientific research and a focus on materials that promise to revolutionize numerous industries, Dr. Starodub exemplifies the qualities of a pioneering and impactful researcher.

Professional Development

Dr. Tetiana Starodub is dedicated to continuous professional development, engaging in various research initiatives and collaborations. Since 2018, she has focused on synthetic metals and coordination chemistry, particularly the synthesis and application of TCNQ compounds. Her commitment to academic excellence includes publishing research findings and presenting at international conferences, fostering connections within the scientific community. Through her work, Dr. Starodub aims to enhance the understanding of electrochemical properties and the potential applications of TCNQ materials in electronics and biotechnology. 🌍📈🔬

Research Focus

Dr. Tetiana Starodub’s research centers on the synthesis and characterization of 7,7′,8,8′-tetracyanoquinodimethane (TCNQ) and its derivatives. Her work encompasses the development of anion-radical salts for use in various fields, including electronics, biotechnology, and medicine. She investigates the electrochemical properties of TCNQ salts to explore their applications in electrochemical sensors, organic batteries, gas storage, and drug delivery systems. Dr. Starodub has synthesized over two hundred TCNQ-based compounds, contributing to advancements in modern materials science and sustainable technologies. 💡⚛️🔋

Awards and Honors

  • Best Research Presentation at the International Chemistry Conference, 2022. 🏆
  • Grant Recipient for Innovative Research in Synthetic Metals, 2021. 💰
  • Recognition Award from the Jan Kochanowski University for Excellence in Teaching, 2020. 🎖️
  • Publication Award for outstanding contributions to the field of Coordination Chemistry, 2019. 📜
  • Scholarship Recipient for International Research Collaboration, 2018. 🌐

Publication Top Notes 

  • TCNQ and Its Derivatives as Electrode Materials in Electrochemical Investigations—Achievement and Prospects: A Review (2024) 📅🔋
  • Crystal Structure of Anion-Radical Salts of 7,7,8,8-tetracyanoquinodimethane with N-xylyl-pyridinium and N-xylyl-isoquinolinium Cations (2022) 📅🔍
  • Structure, optical and electro-physical properties of tetramerized anion-radical salt (N-Xy-Qn)(TCNQ)₂ (2022) 📅🔬
  • Crystal and Molecular Structure of Anion Radical Salt (N-Me-DABCO)(TCNQ)₂ (2022) 📅🔬
  • New radical-cation salts based on the TMTTF and TMTSF donors with iron and chromium bis(dicarbollide) complexes: Synthesis, structure, properties (2021) 📅🔬
  • Structure and Properties of Anion-Radical Salt of 7,7,8,8-Tetracyanoquinodimethane with N-Methyl-2,2′-dipyridyl Cation (2021) 📅🔬
  • The Crystal Structure of a RAS (N–CH3-2-NH2-5-Cl–Py)(TCNQ)(CH3CN) Solvate (2020) 📅🔍
  • Optical properties of RAS (N–CH3-2-NH2-5Cl-Py)(TCNQ)(CH3CN) solvate (2020) 📅🔬
  • Stabilization of Pancake Bonding in (TCNQ)₂.− Dimers in the Radical-Anionic Salt (N−CH3−2-NH2−5Cl−Py)(TCNQ)(CH3CN) Solvate and Antiferromagnetism Induction (2019) 📅🔬

Shakir Khan | Politeness | Best Researcher Award

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Prof. Shakir Khan | Politeness | Best Researcher Award

Prof. Shakir Khan, Imam Mohammad Ibn Saud Islamic University, Saudi Arabia.

Dr. Shakir Khan is a renowned professor in the Information Technology Department at Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia. He is listed in the World’s Top 2% Scientists for 2024, as per Stanford University and Elsevier. With over 18 years of national and international experience, Dr. Khan has contributed extensively to the fields of Machine Learning, Data Science, AI, and E-Learning. He has published over 100 research papers, including 76 indexed in Web of Science. He has also been involved in numerous academic leadership roles, including committee memberships for ABET and NCAAA accreditation processes. Dr. Khan is an active part-time consultant for the King Abdulaziz Public Library and a celebrated academic mentor, having supervised many master’s students in various computer science disciplines. 🧑‍🏫💻

Professional Profile

Google Scholar

Suitability of Shakir Khan for the Best Researcher Award

Dr. Shakir Khan is undoubtedly a strong contender for the Best Researcher Award. His research spans key areas in technology, including Machine Learning, AI, Data Science, Bioinformatics, and IoT, which have wide applications across industries such as healthcare, education, and security.

Education

Dr. Shakir Khan holds a Ph.D. in Computer Science from CSJM University, Kanpur, India, where he researched Cloud Computing and Data Mining for E-Learning applications. He also earned an MSc in Computer Science from Jamia Hamdard, New Delhi, India, focusing on SMS Automation Systems. His academic journey includes a Post Graduate Diploma in Computer Applications (PGDCA) from Pondicherry University and a BSc from Delhi University. These qualifications have laid a solid foundation for his research and professional expertise in emerging technologies like AI, IoT, and Cloud Computing. His doctoral dissertation, exploring Cloud Computing and Data Mining, remains highly regarded for its impact on the development of service-oriented architectures in e-learning systems. 🎓📚

Experience

Dr. Shakir Khan’s career spans over 18 years, during which he has held various prestigious academic positions. He currently serves as a Professor in the Information Technology Department at IMSIU, Riyadh, where he has taught a wide range of undergraduate and postgraduate courses, such as Data Science, Big Data, Cloud Computing, and Data Visualization. Prior to this, he worked as a Researcher/Assistant Professor at King Saud University, Riyadh. Dr. Khan also has consulting experience with the King Abdulaziz Public Library and Kwarim Ltd, Riyadh. He has been involved in the delivery of several workshops on data mining, machine learning, and big data, contributing to the professional development of IT professionals across Saudi Arabia. His career also includes roles as a software engineer and IT manager in India. 💼🌍

Research Interest

Dr. Shakir Khan’s research interests lie in the domains of Machine Learning, AI, Data Science, Bioinformatics, Cloud Computing, and IoT. He is particularly focused on developing innovative AI and machine learning models to improve healthcare systems, enhance e-learning platforms, and address challenges in smart cities through IoT applications. His work in bioinformatics seeks to advance data-driven solutions for health issues such as disease prediction and prevention. Furthermore, his research explores the application of big data analytics in diverse sectors, aiming to streamline processes and improve decision-making. Dr. Khan’s interdisciplinary research approach continues to inspire future advancements in both academia and industry. 🤖🔬

Awards

Dr. Shakir Khan has received numerous prestigious awards, including recognition as one of the World’s Top 2% Scientists for 2024. He has also been honored with the Research Excellence Reward for 2022 and 2023 by Imam Mohammad Ibn Saud Islamic University, Riyadh. In 2022, he led a team to win the ACM Programming JAM 7.0 competition at Prince Sultan University, securing third place out of 40 teams. His achievements also include winning the DTEDUHACK 2023 with a project on virtual history museums. These accolades underscore Dr. Khan’s leadership and innovation in the fields of IT and research. 🏆🌟

Publication

AI student success predictor: Enhancing personalized learning in campus management systems

CITED: 27

A secure data transmission framework for IoT enabled healthcare

CITED: 01

Modified M‐RCNN approach for abandoned object detection in public places

CITED: 10

SA-Bi-LSTM: Self Attention With Bi-Directional LSTM based Intelligent Model for Accurate Fake News Detection to ensured information integrity on social media platforms

CITED: 04

Hybrid machine learning models to detect signs of depression

CITED: 14

Wall Net: Hierarchical Visual Attention-Based Model for Putty Bulge Terminal Points Detection

CITED: 01

Kim Bjerge | Signal Processing | Best Researcher Award

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Kim Bjerge | Signal Processing | Best Researcher Award

Mr. Kim Bjerge, Aarhus University, Denmark.

Kim Bjerge is an Associate Professor at Aarhus University in the Department of Electrical and Computer Engineering, specializing in Signal Processing and Machine Learning. With a Ph.D. focused on Computer Vision and Deep Learning for Insect Monitoring, Kim combines academic expertise with significant industry experience. He has held various teaching and leadership positions at Aarhus University and has contributed to research projects in computer vision. His work has resulted in a notable H-index of 14 and 1080 citations on Google Scholar. Kim is dedicated to advancing technology in engineering education and research. 🎓💻📈

Publication Profiles 

Googlescholoar

Education and Experience

  • Ph.D. in Computer Vision and Deep Learning for Insect Monitoring (Aarhus University, 2022 – present) 📚
  • M.Sc. Eng. in Information Technology (Aarhus University, 2013) 📖
  • B. Eng. in Electronics Engineering (Engineering College of Aarhus, 1989) 🔧
  • Associate Professor and Group Leader (Aarhus University, 2021 – present) 🎓
  • Associate Professor and Group Leader, Signal Processing (Aarhus University, 2009 – 2020) 📊
  • Senior Consultant, IT-Development (Danish Technological Institute, 2007 – 2009) 🛠️
  • Software Development Manager (TC Electronic A/S, 1999 – 2007) 🎶
  • System Developer (Crisplant A/S, 1996 – 1999) 📦
  • System Manager (Sam-system A/S, 1989 – 1996) 💼

Suitability For The Award

Mr. Kim Bjerge, Associate Professor at Aarhus University’s Department of Electrical and Computer Engineering, is an exemplary candidate for the Best Researcher Award due to his outstanding contributions to computer vision, deep learning, and signal processing. With a remarkable career spanning academia and industry, he has made groundbreaking advancements in the fields of artificial intelligence, embedded systems, and digital signal processing, impacting both research and application development globally.

Professional Development

Kim Bjerge has pursued extensive professional development through various programs. He completed the Pedagogical Programme in Engineering at the Center for Engineering Education Research and Development, earning 10 ECTS credits. Additionally, he participated in project management training at Provinu and various management courses at Aarhus Business College, enhancing his skills in human resources, organizational strategy, and software engineering. His commitment to ongoing learning ensures that he remains at the forefront of engineering education and technology. 📚🔧🌱

Research Focus

Kim Bjerge’s research focuses on the intersection of computer vision, deep learning, and machine learning, particularly in the context of insect monitoring. His work aims to develop innovative solutions that enhance the understanding and management of ecological systems through advanced image analysis and artificial intelligence techniques. By leveraging his expertise in signal processing, he contributes to the development of cutting-edge technologies that have practical applications in various fields, including agriculture and environmental science. 🌱🔍🤖

Publication Top Notes 

  • Deep learning and computer vision will transform entomology – Cited by: 362, Year: 2021 📖
  • Towards the fully automated monitoring of ecological communities – Cited by: 141, Year: 2022 🌱
  • An automated light trap to monitor moths (Lepidoptera) using computer vision-based tracking and deep learning – Cited by: 119, Year: 2021 🦋
  • Real-time insect tracking and monitoring with computer vision and deep learning – Cited by: 110, Year: 2021 📹
  • A computer vision system to monitor the infestation level of Varroa destructor in a honeybee colony – Cited by: 85, Year: 2019 🐝
  • Accurate detection and identification of insects from camera trap images with deep learning – Cited by: 61, Year: 2023 🔍
  • A living laboratory exploring mobile support for everyday life with diabetes – Cited by: 40, Year: 2010 📱
  • Hierarchical classification of insects with multitask learning and anomaly detection – Cited by: 26, Year: 2023 📊
  • Enhancing non-technical skills by a multidisciplinary engineering summer school – Cited by: 19, Year: 2017 🎓

Claudia Lopes | Biopotential electrodes | Best Researcher Award

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Dr. Claudia Lopes | Biopotential electrodes | Best Researcher Award

Dr. Claudia Lopes, University of Minho, Portugal.

Cláudia Lopes, a Portuguese researcher, has been at the forefront of Materials Science since 2011, specializing in nanostructured thin films for sensing applications. She is currently a research scientist at the Centre of Physics at the Universities of Minho and Porto, focusing on developing flexible and dry sensors for wearable technology in the biomedical field. Cláudia is a leader in interdisciplinary research, managing both national and international projects, including pre-clinical trials for sensor validation. Her expertise extends to teaching, as she imparts knowledge on materials science, physics, and biomedical technologies to students, fostering the next generation of scientists.

Professional Profile

Scopus

ORCID

Suitability of Claudia Lopes for the Best Researcher Award

Cláudia Lopes is undoubtedly a deserving candidate for the Best Researcher Award. Her contributions to the Materials Science and Biomedical Engineering fields, through cutting-edge research, leadership in national and international projects, and her mentorship of young scientists, reflect her dedication to advancing science and technology.

Education 🎓

Cláudia earned her Ph.D. in Physics from the University of Minho (2015-2018), where she developed Ti-based intermetallic thin films for biomedical sensing, with her thesis receiving the classification “Very Good.” Prior to that, she completed a Master’s in Physics at the same university (2007-2009), focusing on Ti-Si-C thin films, also earning a “Very Good” classification. She furthered her knowledge with a B.Sc. in Physics and Chemistry Teaching in 2003. Her education was supplemented with certifications in Hygiene, Health, and Safety at work (2006-2007).

Experience 🧑‍🔬

Cláudia’s career spans various prestigious institutions, with notable roles such as a Researcher at CF-UM-UP University of Minho since 2020. Previously, she held positions at INEGI and Instituto Pedro Nunes. Her career began in teaching physics and chemistry in high school from 2003 to 2011, which laid the foundation for her later academic roles. Her experience in both research and teaching underscores her leadership in the scientific community, particularly in developing wearable biomedical sensors. Cláudia also leads several interdisciplinary projects and collaborates with both national and international research teams.

Research Interests 🔬

Cláudia’s research interests are centered on the development of advanced materials, specifically nanostructured thin films for biomedical applications. She specializes in Physical Vapour Deposition (PVD) processes to create thin films for sensing applications, focusing on dry and flexible sensors for wearable technologies. Her work includes exploring functionalization of materials, nanoplasmonic sensors, and biopotential monitoring. She is also interested in the development of smart materials, CFRP composites, and nanomaterials for various applications, particularly in health, energy harvesting, and sustainable development.

Awards 🏆

Throughout her career, Cláudia has received recognition for her contributions to materials science and biomedical engineering. She has received multiple grants for her innovative research, including funding from the FCT and various international programs. Notably, she has been involved in several high-impact projects like the EUROSTARS Eureka NeMoRehab and FLEX-HEALTH initiatives. Her scientific work has also garnered attention from the European Commission’s innovation radar, highlighting her excellence in research and development of novel sensing materials.

Publications 📚

Asymmetrical magnetoimpedance on Permalloy/Ag multilayer for high-frequency sensor applications

The influence of the nanostructure design on the corrosion behaviour of TiN thin films prepared by glancing angle deposition

Evaluation of Performance and Longevity of Ti-Cu Dry Electrodes: Degradation Analysis Using Anodic Stripping Voltammetry

Enhancing thermoelectric effect with BaTiO3-doped ZrO2 tapes and ferromagnetic nanostructures

Nanostructured ZnO thin film to enhance gutta-percha’s adhesion to endodontic sealers

Smart Carbon Fiber-Reinforced Polymer Composites for Damage Sensing and On-Line Structural Health Monitoring Applications

PAVLOS TSOUVALTZIS | Plant physiology | Best Researcher Award

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Dr. PAVLOS TSOUVALTZIS | Plant physiology | Best Researcher Award 

Dr. PAVLOS TSOUVALTZIS, University of Florida, United States

Dr. Pavlos Tsouvaltzis, an accomplished horticulturist, specializes in vegetable crops and postharvest technology. He currently serves as an Assistant Professor of Vegetable Horticulture at the Southwest Florida Research and Education Center, University of Florida. With a strong academic foundation from Aristotle University of Thessaloniki (AUTh), his expertise lies in enhancing vegetable production and postharvest quality using innovative techniques. He has authored numerous peer-reviewed publications and supervised graduate theses internationally. Dr. Tsouvaltzis actively contributes as a reviewer for scientific journals and serves on editorial boards, emphasizing sustainable and technologically advanced horticultural practices. 🌍🌿

Professional Profile

Scopus

ORCID

Suitability of PAVLOS TSOUVALTZIS for the Best Researcher Award

Pavlos Tsouvaltzis exhibits a remarkable track record in the field of vegetable horticulture, with an impressive academic and research career spanning several prestigious institutions, including the University of Florida and Aristotle University of Thessaloniki.

Education 🎓

Dr. Tsouvaltzis pursued his BSc in Agriculture (2001), MSc in Horticultural Science (2003), and Ph.D. in Vegetable Horticulture (2008) from AUTh. His Ph.D. dissertation explored the physiology and quality of minimally processed leek. He furthered his education through sabbaticals and short courses in postharvest technologies and molecular techniques at renowned institutions, including the University of Florida and UC Davis. His interdisciplinary training underscores his dedication to advancing horticultural science. 🧬📘

Experience 💼

Dr. Tsouvaltzis has held various academic positions, progressing from Lecturer to Associate Professor at AUTh before joining the University of Florida in 2023. He has also served as a postdoctoral associate at UF’s Horticultural Sciences Department. His international collaborations include research in Italy and mentoring visiting scholars from Turkey and Argentina. His academic leadership extends to advising numerous graduate theses and contributing to global agricultural research. 🌎📚

Research Interests 🔬

Dr. Tsouvaltzis is passionate about vegetable crop production, postharvest biology, and sustainable horticulture. His research emphasizes improving the nutritional quality of vegetables, employing non-destructive techniques, and understanding the impacts of environmental stresses. He also explores innovative cultivation systems like hydroponics to optimize yield and quality. His work bridges fundamental research and practical applications for global food security. 🌾🌱

Awards 🏆

Dr. Tsouvaltzis has received recognition for his significant contributions to horticulture, including nominations for prestigious awards. His efforts have been acknowledged by international conferences and organizations, reflecting his dedication to advancing sustainable agricultural practices. 🌟🎖

Publications 📚

Non-Destructive Detection of Pesticide-Treated Baby Leaf Lettuce During Production and Post-Harvest Storage Using Visible and Near-Infrared Spectroscopy

Effect of Salinity on the Growth and Biochemical Profile of Hedypnois cretica and Plantago coronopus Plants in Relation to the Cropping System and Growth Environment

Quality Traits and Nutritional Components of Cherry Tomato in Relation to the Harvesting Period, Storage Duration and Fruit Position in the Truss

The Impacts of the Emerging Climate Change on Broccoli (Brassica oleracea L. var. italica Plenck.) Crop

Nutritional composition changes in bell pepper as affected by the ripening stage of fruits at harvest or postharvest storage and assessed non-destructively

Improvement of the quality in hydroponically grown fresh aromatic herbs by inducing mild salinity stress is species-specific