Mr. Mohammed Aljamal | Artificial Intelligence | Best Researcher Award

Mr. Mohammed Aljamal | Artificial Intelligence | Best Researcher Award 

Mr. Mohammed Aljamal, University of Bridgeport, United States

Mohammed Aljamal is a Laboratory Engineer and Ph.D. candidate in Computer Science & Engineering, based in the New York City Metropolitan Area. He holds a Master’s degree in Artificial Intelligence from the University of Bridgeport and is actively engaged in academic and professional communities as the President of the UB Robotics Club and a member of AIAA, UPE, and the Honor Society. With over four years of experience at the University of Bridgeport, he has contributed as a Laboratory Engineer, Graduate Research Assistant, and Teaching Assistant, specializing in laboratory management, hardware and software solutions, and IT infrastructure. His expertise spans project leadership, problem-solving, cross-functional team management, and innovative solution design. Beyond academia, Mohammed has a strong background in consulting, resource allocation, and international collaboration, having successfully led and completed critical projects. Passionate about technology and innovation, he continuously seeks opportunities to develop solutions that enhance user experiences and drive technological advancement.

Professional Profile:

GOOGLE SCHOLAR

Suitability of Mohammed Aljamal for the Best Researcher Award

Mohammed Aljamal is a highly skilled and innovative researcher with a strong background in Artificial Intelligence, Computer Science, and Engineering. His Ph.D. candidacy, extensive teaching experience, and leadership roles at the University of Bridgeport demonstrate his dedication to academic excellence and technological advancements.

Education 🎓

  • Ph.D. Candidate in Computer Science & EngineeringUniversity of Bridgeport (Ongoing)
  • Master’s Degree in Artificial IntelligenceUniversity of Bridgeport
  • Bachelor’s Degree in [Field Not Specified][University Not Specified]

Work Experience 💼

University of Bridgeport (4 years 1 month)

  • Labs Engineer (Feb 2022 – Present) ⚙️

    • Improved and maintained laboratory equipment.
    • Developed detailed hardware and software data for lab management.
    • Conducted inspections and routine maintenance on lab equipment.
    • Implemented new technology solutions and disaster recovery plans.
    • Coordinated IT services to ensure data availability and security.
  • Graduate Research & Teaching Assistant (Jan 2022 – Feb 2022) 📚

    • Assisted in research projects and student instruction.
  • Teaching and Laboratory Assistant (Feb 2021 – Dec 2021) 🏫

    • Assisted undergraduate and graduate students in Intro to Robotics.
    • Managed lab hours, discussions, assignments, and exams.

Achievements & Leadership 🌟

  • President of UB Robotics Club 🤖 – Leading robotics initiatives and student projects.
  • Successfully completed two delayed projects 🎯 – Resolved critical issues and met client satisfaction.
  • Consulted and collaborated with international vendors 🌍 – Gained experience in global tech solutions.
  • Designed and implemented innovative lab solutions 🔧 – Optimized university lab resources.

Awards & Honors 🏆

  • Member of AIAA (American Institute of Aeronautics and Astronautics) 🚀
  • Member of UPE (Upsilon Pi Epsilon – International Honor Society for Computing) 🖥️
  • Honor Society Member 🎖️

Publication Top Notes:

 

 

Dr. Peng Zhi | Deep Learning | Best Researcher Award

Dr. Peng Zhi | Deep Learning | Best Researcher Award 

Dr. Peng Zhi, Lanzhou University, China

Peng Zhi is a Ph.D. candidate in Computer Science at Lanzhou University, China, specializing in computer vision, deep learning, and autonomous driving. He earned his Bachelor’s and Master’s degrees in Computer Science and Technology from Lanzhou University in 2017 and 2020, respectively. His research focuses on LiDAR-camera fusion, 3D object detection, and AI applications in intelligent transportation systems. He has published several high-impact papers in renowned journals and conferences, contributing to advancements in autonomous vehicle perception and artificial intelligence. Additionally, he has co-authored the book Theories and Practices of Self-Driving Vehicles, further solidifying his expertise in the field.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Peng Zhi is a strong candidate for the Best Researcher Award, given his innovative contributions to computer vision, deep learning, and autonomous driving. As a Ph.D. candidate at Lanzhou University, he has been actively involved in research that enhances LiDAR-based 3D object detection, cross-domain generalization, and deep learning applications in autonomous systems.

🎓 Education

  • Ph.D. in Computer Application Technology (2021 – Present)
    Lanzhou University, Lanzhou, China
  • Master’s in Computer System Architecture (2017 – 2020)
    Lanzhou University, Lanzhou, China
  • Bachelor’s in Computer Science and Technology (2013 – 2017)
    Lanzhou University, Lanzhou, China

💼 Work Experience

  • Ph.D. Candidate & Researcher (2021 – Present)
    Lanzhou University, Lanzhou, China

    • Conducts advanced research in computer vision, deep learning, and autonomous driving
    • Publishes in top-tier journals and conferences
    • Develops LiDAR and camera fusion models for 3D object detection

🏆 Achievements & Contributions

  • Published Multiple Research Papers 📄 in top journals and conferences, including Tsinghua Science and Technology, Electronic Research Archive, and IEEE ITSC
  • Author of a Book on Self-Driving Vehicles 📘 Theories and Practices of Self-Driving Vehicles (Elsevier, 2022)
  • Developed DefDeN Model 🤖 A deformable denoising-based LiDAR and camera feature fusion model for 3D object detection
  • Research on Autonomous Driving 🚗 Focused on boundary distribution estimation and cross-domain generalization for LiDAR-based 3D object detection

🏅 Awards & Honors

  • Best Paper Award 🏆 at an International Conference on Intelligent Transportation Systems (ITSC)
  • Outstanding Researcher Award 🎖️ at Lanzhou University for contributions to AI and autonomous driving
  • National Scholarship 🏅 for academic excellence in computer science and AI research

Publication Top Notes:

Cross-Domain Generalization for LiDAR-Based 3D Object Detection in Infrastructure and Vehicle Environments

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

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 🖐️🔗

Assoc. Prof. Dr. Mahmoud Bayat | Artificial intelligence Award | Best Researcher Award

Assoc. Prof. Dr. Mahmoud Bayat | Artificial intelligence Award | Best Researcher Award

Assoc. Prof. Dr. Mahmoud Bayat, Research Institute of Forests and Rangelands, Iran

Mahmoud Bayat is an Assistant Professor at the Research Institute of Forests and Rangelands, part of the Agricultural Research, Education, and Extension Organization (AREEO) in Tehran, Iran. He earned his B.A., M.Sc., and Ph.D. degrees from the University of Tehran, specializing in forestry science. Mahmoud has collaborated with renowned researchers, including Dr. Charles P.-A. Bourque, Dr. Pete Bettinger, Dr. Eric Zenner, Dr. Aaron Weiskittel, Dr. Harold Burkhart, and Dr. Timo Pukkala. His research focuses on forest modeling and inventory, with particular interest in applying artificial intelligence and machine learning techniques in forestry. Currently, he is working on projects related to growth and yield models for uneven-aged and mixed broadleaf forests using neural networks and the monitoring and mapping of tree species richness in northern Iran’s forests through symbolic regression and artificial neural networks. Mahmoud is proficient in statistical tools such as SPSS and MATLAB, and he is eager to share his expertise and discuss potential collaborations. For more information, his profiles can be found on ResearchGate, Google Scholar, and Scopus.

Professional Profile:

SCOPUS

 

Mahmoud Bayat’s Suitability for the Research for Best Researcher Award

Based on the provided details, Mahmoud Bayat demonstrates a strong candidacy for the Research for Best Researcher Award due to his extensive academic and professional contributions. Below is a summary supporting his suitability

Education 🎓

  • Ph.D. in Forestry Science
    University of Tehran, Iran
  • M.Sc. in Forestry Science
    University of Tehran, Iran
  • B.A. in Forestry Science
    University of Tehran, Iran

Work Experience 🏢

  • Assistant Professor
    Research Institute of Forests and Rangelands, Agricultural Research, Education and Extension Organization (AREEO)
    Tehran, Iran
    Year: [Specify Year] – Present
  • Research Collaborator
    Worked with:

    • Dr. Charles P.-A. Bourque
    • Dr. Pete Bettinger
    • Dr. Eric Zenner
    • Dr. Aaron Weiskittel
    • Dr. Harold Burkhart
    • Dr. Timo Pukkala

Research Interests 🔍

  • Forest modeling and inventory
  • Application of artificial intelligence and machine learning in forestry

Current Projects 📊

  1. Growth and Yield Models for Uneven-Aged and Mixed Broadleaf Forest
    • Method: Neural Network
  2. Monitoring, Mapping, and Modeling Variation in Tree Species Richness
    • Method: Symbolic Regression and Artificial Neural Networks
    • Location: Northern Iran Forests

Publication Top Notes:

Comparison of Random Forest Models, Support Vector Machine and Multivariate Linear Regression for Biodiversity Assessment in the Hyrcanian Forests

Projected biodiversity in the Hyrcanian Mountain Forest of Iran: an investigation based on two climate scenarios

Recreation Potential Assessment at Tamarix Forest Reserves: A Method Based on Multicriteria Evaluation Approach and Landscape Metrics

Comparison between graph theory connectivity indices and landscape connectivity metrics for modeling river water quality in the southern Caspian sea basin

Development of multiclass alternating decision trees based models for landslide susceptibility mapping

Modeling Tree Growth Responses to Climate Change: A Case Study in Natural Deciduous Mountain Forests

 

Assist. Prof. Dr. Dumitru Radulescu | Machine Learning Awards | Top Researcher Award

Assist. Prof. Dr. Dumitru Radulescu | Machine Learning Awards | Top Researcher Award 

Assist. Prof. Dr. Dumitru Radulescu, University of Medicine and Pharmacy Craiova (UMF Craiova), Romania

Dumitru Rădulescu, is a distinguished medical professional and researcher specializing in surgery and medical sciences. He earned his Bachelor’s degree in Medicine from UMF Craiova in 2009, followed by a Doctor of Medical Sciences degree, which he obtained in 2020 under the auspices of the Romanian Ministry of Health. Dr. Rădulescu’s academic journey is marked by his receipt of a competitive doctoral scholarship, highlighting his commitment to advancing his expertise in the medical field. Currently serving as a Specialist Surgeon at the Military Emergency Clinical Hospital “Dr. Ştefan Odobleja” in Craiova, he has accumulated extensive clinical experience through various residency programs in family medicine and general surgery. His professional roles include positions as a University Assistant at UMF Craiova, where he contributes to the education of future healthcare professionals in surgical specialties.

Professional Profile:

ORCID

Summary of Suitability for the Top Researcher Award

Dumitru Rădulescu is an accomplished researcher and specialist surgeon whose academic and professional journey highlights his commitment to advancing medical sciences, particularly in the areas of surgery and diagnostics. His education culminated in a Doctor of Medical Sciences degree from UMF Craiova, where he also received a doctoral scholarship, showcasing his academic excellence and dedication to research.

Education 📚

  • Doctor of Medical Sciences
    University of Medicine and Pharmacy Craiova (UMF Craiova)
    2014 – 2020
  • Doctoral Scholarship
    UMF Craiova (POSDRU/187/1.5/S/156069)
    2014 – 2015
  • Bachelor’s Degree in Medicine
    UMF Craiova
    2003 – 2009
  • High School Diploma
    Balş Theoretical High School
    1999 – 2003

Professional Development 🎓

  • Specialist Surgeon
    Ministry of Health Order no. 721/04.06.2018
    2018 – Present
  • General Surgery Resident
    2012 – 2018
  • Family Medicine Resident
    2010 – 2012

Areas of Competence 💪

  • DPPD Module (2008)
  • English for Specific Purposes – Medical English B2 (2021)

Professional Experience 🏥

  • Current Position:
    University Assistant, Military Emergency Clinical Hospital “Dr. Ştefan Odobleja,” Craiova
    2022 – Present
  • Previous Positions:
    • University Assistant DRD, Department VI – Surgical Specialties (2018 – 2021)
    • General Surgery Resident, Clinic I Surgery SCJU no.1 Craiova (2013 – 2018)
    • Family Medicine Resident, Filantropia Clinical Hospital Craiova (2010 – 2012)

Research Contributions 🔬

Dr. Rădulescu is a dedicated researcher who recently received a grant for his project titled:
“Discovery and validation of a new leukocyte formula marker for predicting mortality in patients with tuberculosis and malnutrition using machine learning.” 🤖
This project highlights his commitment to leveraging modern technology in medical research to address critical health issues.

Publication Top Notes

Enhancing the Understanding of Abdominal Trauma During the COVID-19 Pandemic Through Co-Occurrence Analysis and Machine Learning

Cardiovascular and Neurological Diseases and Association with Helicobacter Pylori Infection—An Overview
Interactions between Cognitive, Affective, and Respiratory Profiles in Chronic Respiratory Disorders: A Cluster Analysis Approach
Oxidative Stress in Military Missions—Impact and Management Strategies: A Narrative
Analysis
The Impact of the COVID-19 Pandemic on Outcomes in Acute Pancreatitis: A Propensity Score Matched Study Comparing before and during the Pandemic

 

 

Prof. Dr. Tamara Gajic | Artificial Intelligence Awards | Top Researcher Award

Prof. Dr. Tamara Gajic | Artificial Intelligence Awards | Top Researcher Award 

Prof. Dr. Tamara Gajic, Geographical Institute “Jovan Cvijic” Serbian Academy of Sciences and Arts, Belgrade, Serbia

Tamara Gajić is a distinguished Senior Research Associate at the Geographical Institute “Jovan Cvijić” of the Serbian Academy of Sciences and Arts (SASA), specializing in social geography. She holds a Ph.D. in Geosciences from the University of Novi Sad and has extensive experience in research and education across various institutions. Her academic career spans several positions, including Senior Researcher at the Institute of Environmental Engineering, People’s Friendship University of Russia (RUDN University), and Associate Professor at Singidunum University in Belgrade. She has also served as a professor and assistant professor at various universities in Serbia, Bosnia, and Herzegovina. Gajić’s research focuses on rural development, tourism management, and sustainable practices in agritourism, gastrotourism, and sport tourism. She has contributed to numerous projects, including the modernization of tourism study programs in Serbia and feasibility studies for spa tourism. Gajić is an active member of various professional organizations, including the Serbian Geographical Society and the Tourist Organization of Serbia, and has mentored numerous graduate and doctoral students. Her expertise in integrating economics, service quality, and human resources in tourism management has earned her recognition as one of the top 10% of distinguished scientists in Serbia in 2024.

Professional Profile:

SCOPUS

ORCID

GOOGLE SCHOLAR

Suitability of Tamara Gajić for the Top Researcher Award

Tamara Gajić is highly qualified for the Top Researcher Award due to her extensive academic and professional achievements in the fields of Geography, Rural Studies, and Tourism Management. Below are the key reasons why she is a suitable candidate for this prestigious award:

Academic Degrees:

🎓 Ph.D. in Geosciences
📅 2010
University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Serbia 🇷🇸

🎓 M.Sc. in Tourism Management
📅 2007
University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Serbia 🇷🇸

🎓 B.Sc. in Tourism Management
📅 2001
University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Serbia 🇷🇸

Research & Teaching Interests:

🌍 Research Areas:

  • Geography 🌍
  • Rural Studies 🌾
  • Tourism Management 🌐
    Focus on Agrotourism, Gastrotourism, and Sport Tourism 🏞️🍴🏃‍♀️
    Intersection of Economics in Tourism, Service Quality, and Human Resources 💼
    Sustainability in Environment and Tourism 🌱

Previous Employment:

  • Associate Professor
    📅 February 2021 – September 2021
    Faculty of Tourism and Hotel Management, Singidunum University, Belgrade, Serbia 🇷🇸
  • Assistant Professor
    📅 October 2018 – February 2022
    University for Business Studies, Banja Luka, Bosnia and Herzegovina 🇧🇦
  • Professor of Vocational Studies
    📅 October 2008 – February 2021
    Novi Sad Business School, Novi Sad, Serbia 🇷🇸

Publication top Notes:

Innovative Approaches in Hotel Management: Integrating Artificial Intelligence (AI) and the Internet of Things (IoT) to Enhance Operational Efficiency and Sustainability

The Contribution of the Farm to Table Concept to the Sustainable Development of Agritourism Homesteads

Fostering Sustainable Urban Tourism in Predominantly Industrial Small-Sized Cities (SSCs)—Focusing on Two Selected Locations

Leveraging digital platforms for responsible sports tourism: Budapest’s role in the 2020 European football championship

Tourists’ Willingness to Adopt AI in Hospitality—Assumption of Sustainability in Developing Countries

The Adoption of Artificial Intelligence in Serbian Hospitality: A Potential Path to Sustainable Practice

Ms. Hind MEZIANE | Artificial Intelligence | Best Scholar Award

Ms. Hind MEZIANE | Artificial Intelligence | Best Scholar Award 

Ms. Hind MEZIANE, ACSA Lab, Faculty of Sciences, University Mohammed First, Oujda, Morocco

Hind Meziane is a dedicated researcher and Ph.D. candidate in Computer Science at the ACSA Laboratory, Department of Mathematics, Faculty of Sciences, Mohammed Premier University, Oujda, Morocco. Her academic journey began with a Baccalaureate in Science (Science Mathematics Option B) from Mehdi Ben Berka High School in Oujda in 2012. She then pursued higher education at Mohammed Premier University, obtaining a DEUG in Mathematics and Computer Science (2012-2014), a LICENSE in Mathematics and Computer Science (2014-2016), and a Specialized Master’s in Computer Engineering with Honors (2017-2019).

Professional Profile:

Summary of Suitability for Best Scholar Award

Hind Meziane is a highly accomplished researcher whose work primarily focuses on the security of Internet of Things (IoT) systems. She is currently pursuing a Ph.D. in Computer Science at Mohammed Premier University and has an impressive academic background, including a specialized master’s degree in Computer Engineering and a bachelor’s degree in Mathematics and Computer Science. Her research contributions are well-documented through various publications in reputable international journals and conference proceedings.

🎓 Education:

  • 2019-Present: Doctorate (PhD) in Computer Science at Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2017-2019: Specialized Master in Computer Engineering, with Honors, at Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2014-2016: LICENSE in Mathematics and Computer Science from Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2012-2014: DEUG in Mathematics and Computer Science from Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2011-2012: Baccalaureate in Science, Mathematics Option B from Mehdi Ben Berka High School, Oujda.

Publication top Notes:

A survey on performance evaluation of artificial intelligence algorithms for improving IoT security systems

A Comparative Study for Modeling IoT Security Systems

Modeling IoT based Forest Fire Detection System with IoTsec

A Study of Modelling IoT Security Systems with Unified Modelling Language (UML)

Classifying security attacks in iot using ctm method

Internet of Things: Classification of attacks using CTM method