Assist. Prof. Dr. Hossein Bagherpour | Machine Learning Awards | Best Researcher Award

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Assist. Prof. Dr. Hossein Bagherpour | Machine Learning Awards | Best Researcher Award

Assist. Prof. Dr. Hossein Bagherpour, Department of Biosystems Engineering, Bu-Ali Sina Universit, Iran

Dr. Hossein Bagherpour is an accomplished Assistant Professor in the Department of Biosystems Engineering at Bu-Ali Sina University, where he has served since 2013. Holding a Ph.D. and M.Sc. in Biosystems and Agricultural Machinery Engineering from Tarbiat Modares University and a B.Sc. in Mechanical Engineering from the University of Tehran, his interdisciplinary expertise bridges advanced engineering with agricultural innovation. Dr. Bagherpour is a leading researcher in the application of artificial intelligence and machine vision in precision agriculture, with a focus on plant disease detection, crop quality assessment, and robotic harvesting. He has supervised multiple Ph.D. and M.Sc. theses on deep learning, image processing, and AI-driven diagnostics for crops like rose, wheat, hazelnut, and quince. His contributions significantly advance smart farming technologies, offering solutions for enhanced productivity and sustainable agriculture in small and large-scale systems.

Professional Profile:

GOOGLE SCHOLAR

ORCID

Summary of Suitability for Best Researcher Award – Dr. Hossein Bagherpour

Dr. Hossein Bagherpour is an exemplary candidate for the Best Researcher Award, recognized for his pioneering work at the intersection of biosystems engineering, artificial intelligence, and precision agriculture. As an Assistant Professor at Bu-Ali Sina University since 2013, Dr. Bagherpour has made significant contributions to the development and application of intelligent systems in agricultural automation and food quality assessment.

🎓 Education

  • 🧪 Ph.D. in Biosystems Engineering – Tarbiat Modares University, Tehran, Iran

  • 🚜 M.Sc. in Agricultural Machinery Engineering – Tarbiat Modares University, Tehran, Iran

  • ⚙️ B.Sc. in Mechanical Engineering (Design of Machinery) – University of Tehran, Tehran, Iran

🏢 Work Experience

  • 👨‍🏫 Assistant Professor, Department of Biosystems Engineering, Bu-Ali Sina University (2013–Present)

    • 📍 Faculty of New Agriculture, Room 207

    • 📍 Business Incubator Center No. 2, Room 7

🏆 Achievements & Contributions

  • 📊 Supervised numerous Ph.D. and M.Sc. theses focusing on AI, deep learning, and smart agricultural systems

  • 🤖 Developed algorithms for robotic harvesting, crop disease detection, and quality inspection using machine learning and computer vision

  • 📚 Published multiple research papers (see Google Scholar) in areas such as AI-based phenotyping, intelligent sensors, and agricultural robotics

🎖 Awards & Honors

  • 🌟 Recognized for advancing smart agriculture through AI integration

  • 🧠 Leader in AI-driven research in agricultural biosystems

Publication Top Notes:

Hyperparameter Optimization of ANN, SVM, and KNN Models for Classification of Hazelnuts Images Based on Shell Cracks and Feature Selection Method

Enhancing the Performance of YOLOv9t Through a Knowledge Distillation Approach for Real-Time Detection of Bloomed Damask Roses in the Field

Development and Optimization of a Novel Deep Learning Model for Diagnosis of Quince Leaf Diseases

Detection of different adulteration in cinnamon powder using hyperspectral imaging and artificial neural network method

Design, Construction, and Evaluation of a Precision Vegetable Reaper to Use in Small Plots

A New Method to Optimize Deep CNN Model for Classification of Regular Cucumber Based on Global Average Pooling

Mr. Koagne Silas | Neural Networks | Pioneer Researcher Award

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Mr. Koagne Silas | Neural Networks | Pioneer Researcher Award 

Mr. Koagne Silas, University of Dschang, Cameroon

KOAGNE LONGPA TAMO Silas is a Cameroonian researcher and Ph.D. student in Physics at Dschang State University, specializing in medical physics with a strong focus on automation and applied computer science. His academic background spans both physics and electrical engineering, with degrees from the University of Dschang and the University of Bamenda, where he developed expertise in embedded systems, analog artificial neural networks, and electronics. Silas has extensive experience in microcontroller programming, analog and digital circuit simulation, and tools such as MATLAB, Arduino, Proteus, and Cadence Virtuoso. In addition to his research, he has served as an electronics teacher at various technical colleges and as a junior lecturer in computer science. His hands-on experience includes internships in electronics maintenance and electrical network installation. A bilingual communicator in English and French, Silas is known for his leadership, creativity, and commitment to advancing applied technologies in medical physics.

Professional Profile:

SCOPUS

🏅 Summary of Suitability Pioneer Researcher Award 

KOAGNE LONGPA TAMO Silas is an emerging research talent in the field of medical physics and electronics, demonstrating a rare combination of early innovation, technical depth, and applied problem-solving across interdisciplinary domains. As a Ph.D. candidate with an M.Sc. specialization in analog artificial neural networks for medical applications, Silas is pioneering research at the intersection of electronics, embedded systems, and health technologies, aligning closely with the spirit of the Pioneer Researcher Award.

🎓 Education Background

  • Ph.D. in Physics (Medical Physics) – Dschang State University, Cameroon (📅 Dec 2022 – Present)

    • 🧠 Research Focus: Analog Artificial Neural Networks

    • 👨‍🏫 Supervisor: Prof. Geh Wilson Ejuh

  • M.Sc. in Physics, Electronics Speciality – Dschang State University, Cameroon (📅 July 2022)

    • 📘 Thesis: Specification and implementation of multilayer perceptron analog artificial neural networks

    • 👨‍🏫 Supervisor: Dr. Djimeli Tsajio Alain B.

  • B.Sc. in Physics – Dschang State University, Cameroon (📅 Aug 2021)

  • DIPET 2 in Electronics – University of Bamenda (📅 July 2020)

    • 🛰 Dissertation: Design and implementation of a digital breath alcohol detection system with SMS alert and vehicle tracking

  • DIPET 1 in Electronics – University of Bamenda (📅 Aug 2018)

    • 🚪 Project: RFID-based electronic attendance system with automatic door unit

  • GCE A/L – Government Bilingual High School, Mbouda (📅 July 2015)

  • GCE O/L – Government Bilingual High School, Mbouda (📅 June 2013)

  • FSLC – Ecole Primaire Bilingue de la Promotion, Mbouda (📅 June 2008)

💼 Work Experience

  • Electronics Teacher – Government Technical College Ngombo-ku, Cameroon (📅 Jan 2021 – Present)

  • Junior Lecturer in Computer Science – Higher Technical Teacher Training College Bambili (📅 2019–2020)

  • Electronics Teacher – Government Technical High School Bambui (📅 2017–2018)

  • Internship – Electronics & Maintenance

    • 📍 HYTECHS, Yaoundé (📅 2019)

    • 🔧 Worked on printer maintenance & installation

  • Internship – Electrical Network Installation

    • 📍 MEECH CAM Sarl, Yaoundé (📅 2016)

    • ⚡ Focus on underground cable installation and high voltage network

🏆 Achievements & Awards

  • ✅ Successfully designed and implemented:

    • 🤖 An analog artificial neural network (M.Sc. Thesis)

    • 🚘 A breath alcohol detection system with GPS and SMS alerts

    • 🛂 An RFID-based attendance system with automated doors

  • 📚 Published and presented academic work in medical physics and embedded systems

  • 👨‍🏫 Contributed to higher education through teaching and mentoring roles across several institutions

  • 🎓 Admitted to Ph.D. program based on excellent academic performance

  • 💻 Advanced skills in MATLAB, Arduino, MikroC, Cadence Virtuoso, PSPICE & Proteus

  • 🗣️ Bilingual in English and French – great asset for teaching and collaboration

Publication Top Notes:

Breast cancer detection and classification: A study on the specification and implementation of multilayer perceptron analog artificial neural networks

Prof. Dr. Cedric Sueur | Artificial intelligence | Best Researcher Award

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Prof. Dr. Cedric Sueur | Artificial intelligence | Best Researcher Award 

Prof. Dr. Cedric Sueur, Université de Strasbourg, France

Cédric Sueur is a French ethologist and primatologist renowned for his contributions to the study of animal behavior and social ecology. He is a Full Professor at the University of Strasbourg and a Fellow of the Institute for Advanced Study, as well as a member of the French Academic Institute. He holds a Ph.D. in Ethology from Louis Pasteur University, Strasbourg, and the Free University of Brussels, along with an HDR qualification to supervise doctoral theses. Throughout his career, he has held prestigious academic positions, including Associate Professor at the University of Strasbourg, Visiting Professor at Kyoto University, Sun Yat-sen University, and Lille Catholic University. His research has been widely recognized, earning him numerous accolades such as the Changjiang Scholar Program award, the Adolphe Wetrems Award from the Royal Academies for Science and the Arts of Belgium, and recognition among the world’s top 2% of scientists by Stanford University. With a strong academic and research background, Sueur continues to contribute significantly to the field of ethology and primatology.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award – Cédric Sueur

Cédric Sueur is a highly accomplished researcher in Ethology and Primatology, making him a strong contender for the Best Researcher Award. His outstanding academic background, extensive research contributions, prestigious honors, and leadership in the scientific community establish him as an influential figure in his field.

🎓 Education

  • 2014: HDR, Habilitation to Supervise Doctoral Theses

  • 2008: PhD in Ethology – Primatology, Louis Pasteur University, Strasbourg & Free University of Brussels

  • 2005: Master’s Degree, University Louis Pasteur, Strasbourg (With Honours)

  • 2003: Bachelor’s in Organisms’ Biology, University 14USTL, Lille (With Honours)

💼 Work Experience

  • Since 2024: Full Professor, University of Strasbourg

  • Since 2021: Invited Professor, Lille Catholic University

  • 2011-2024: Associate Professor, University of Strasbourg (Outstanding since 2022)

  • 2022 (Jan-Mar): Invited Professor, Kyoto University Institute for Advanced Study

  • 2016 (Jul-Aug): Invited Professor, Sun-Yat Sen University, China (Changjiang Scholar Program award)

  • 2008-2012: Research Associate, Unit of Social Ecology, Free University of Brussels

  • 2010-2011: Research Fellow, Primate Research Institute, Kyoto University

  • 2009-2010: Research Associate, Ecology & Evolutionary Biology, Princeton University

  • 2007-2008: Lecturer in Ethology, Strasbourg University

🏆 Awards & Honors

  • 2025: Selected for the Lumexplore Prize by the French Society of Explorers 🏅

  • 2025: Selected for the François Sommer Prize 🏆

  • 2024-2029: Member of the “Institut Universitaire de France” 🎖️

  • 2023: Best Communication Prize at Aramos Congress 🏅

  • 2023: Named Best Scientist by Research.com 🌍

  • 2022: Listed among the World’s Top 2% of Scientists by Stanford University 📊

  • 2022: Named Best Scientist by Research.com 🏅

  • 2019: Adolphe Wetrems Award from the Royal Academies for Science and the Arts of Belgium 🏆

  • 2019-2024: Fellow of the Institut Universitaire de France 🎖️

  • 2017: Primates Social Impact Award 🏅

  • 2016: Changjiang Scholar Program Award (Visiting Professor at Sun-Yat Sen University, China) 🇨🇳

  • 2014: Excellence Award from the French Minister of Higher Education and Research 🎓

  • 2013: Young Scientist Award from the French Society for the Study of Animal Behaviour (SFECA) 🏅

  • 2012: 3 papers among the Top 5 Cited Papers in International Journal of Primatology 📜

  • 2012: Fellow of the University of Strasbourg Institute for Advanced Study (USIAS) 🎓

  • 2010: JSPS Alumni (Japan Society for the Promotion of Science) 🇯🇵

  • 2009: Fulbright Alumni 🇺🇸

  • 2009: Prize of the Society of Biology of Strasbourg for Best Thesis 📜

  • 2009: “Le Monde de la Recherche Universitaire” Prize for Best Thesis 🎓

  • 2006-2010: Member of the European Doctoral College of Strasbourg 🌍

Publication Top Notes:

GITED:775
GITED:364
GITED:278
GITED:262
GITED:192
GITED:179
GITED:168

Mr. Mohammed Aljamal | Artificial Intelligence | Best Researcher Award

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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 & Engineering – University of Bridgeport (Ongoing)
  • Master’s Degree in Artificial Intelligence – University 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:

 

 

Mr. Fangzhou Lin | Deep Learning | Best Scholar Award

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Mr. Fangzhou Lin | Deep Learning | Best Scholar Award 

Mr. Fangzhou Lin, Hong Kong University of Science and Technology, Hong Kong

Fangzhou Lin is a Ph.D. researcher in Civil Engineering at the Hong Kong University of Science and Technology (HKUST), specializing in deep learning, machine vision, construction robots, and multimodal data fusion. He holds a Bachelor’s degree in Civil Engineering from Fuzhou University (2015-2019) and a Master’s degree in Structural Engineering from Southeast University (2019-2022). Fangzhou Lin’s research focuses on the integration of artificial intelligence and robotics in construction automation, with applications in fire safety inspection, resource management, visual measurement, and quality assessment. His work has been published in leading journals such as Automation in Construction, Computer-Aided Civil and Infrastructure Engineering, and Advanced Engineering Informatics. He has contributed to multiple cutting-edge studies on robotic systems for construction site management, vision-based measurement techniques, and reinforcement learning-based scheduling for electric concrete vehicles. As an emerging scholar in construction automation and AI-driven inspection technologies, Fangzhou Lin actively collaborates on multi-disciplinary research projects to enhance efficiency, safety, and sustainability in the built environment. His contributions to automated reality capture, rebar positioning, and construction robotics are shaping the future of intelligent construction and infrastructure development.

Professional Profile:

SCOPUS

Suitability of Fangzhou Lin for the Best Scholar Award

Fangzhou Lin is an outstanding early-career scholar with a strong background in deep learning, machine vision, construction robotics, and multimodal data fusion within the field of civil engineering. His academic trajectory, research productivity, and innovative contributions make him a compelling candidate for the Best Scholar Award. Below is a detailed assessment of his suitability based on key criteria.

🎓 Education

  • 2015.09 – 2019.06 | Fuzhou University – Bachelor’s Degree in Civil Engineering
  • 2019.09 – 2022.06 | Southeast University – Master’s Degree in Structural Engineering
  • 2022.09 – Present | Hong Kong University of Science and Technology – Ph.D. in Civil Engineering

🏗️ Work & Research Experience

  • Expertise in: Deep learning, machine vision, construction robots, multimodal data fusion
  • Published in top journals such as Automation in Construction and Computer-Aided Civil and Infrastructure Engineering
  • Conducting research on:
    • 🔥 Fire Safety Inspection using AI-driven visual inspection
    • 🤖 Robotics for Construction Management with multi-task planning and automatic grasping
    • 🏗️ BIM-integrated Reality Capture for indoor inspection using multi-sensor quadruped robots
    • 🎯 Vision-based Monitoring for assembly alignment of precast concrete bridge members

🏆 Achievements & Awards

  • Published multiple high-impact journal papers 📚
  • Lead researcher on innovative construction technology projects 🔍
  • Contributed to advanced AI-driven automation for civil engineering 🤖
  • Research works under review in prestigious engineering journals 🏅
  • Collaborated with leading experts in civil engineering and robotics 🤝

Publication Top Notes:

Efficient visual inspection of fire safety equipment in buildings

 

Dr. Peng Zhi | Deep Learning | Best Researcher Award

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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

Ms. Saleha Kamal | Pattern Recognition Awards | Best Researcher Award

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Ms. Saleha Kamal | Pattern Recognition Awards | Best Researcher Award 

Ms. Saleha Kamal, Air University, Pakistan

Saleha Kamal is an accomplished AI and Computer Vision professional based in Rawalpindi, Pakistan, with expertise in image processing, silhouette detection, segmentation, and feature classification. She is currently pursuing an MS in Computer Science at Air University, Islamabad, Pakistan (2023-2025). Saleha’s research focuses on human interaction analysis and the development of advanced algorithms for computer vision tasks. Her work has been published in esteemed international conferences, including IEEE ICECT 2024 and IEEE ICET 2024, showcasing her innovative contributions to multi-feature descriptors and composite feature-based classifiers for human interaction recognition.

Professional Profile:

GOOGLE SCHOLAR

Suitability of Saleha Kamal for the Best Researcher Award

Saleha Kamal demonstrates exceptional potential and achievements in AI, machine learning, and computer vision research, making her a compelling candidate for the Best Researcher Award. Her dedication to advancing knowledge in human interaction recognition, along with her technical and academic accomplishments, positions her as a rising star in the research community.

Education 🎓

  • MS in Computer Science (2023 – 2025)
    Air University, Islamabad, Pakistan

Work and Research Experience 💼

  • Research Experience
    • Co-authored research papers published in international conferences:
      • “Multi-Feature Descriptors for Human Interaction Recognition in Outdoor Environments” – IEEE ICECT, 2024.
      • “A Novel Human Interaction Recognition via Composite Features and Max Entropy Classifier” – IEEE ICET, 2024.

Achievements and Certifications 🏆

  • Published research in prestigious IEEE conferences.
  • Certifications:
    • Advanced Computer Vision with TensorFlow – Coursera, 2023.
    • Machine Learning Specialization – Coursera, 2023.

Publication Top Notes:

A Novel Human Interaction Recognition via Composite Features and Max Entropy Classifier

CITED:8

CITED:6

Mr. Shiraz Kaderuppan | Deep Learning Awards | Best Researcher Award

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Mr. Shiraz Kaderuppan | Deep Learning Awards | Best Researcher Award 

Mr. Shiraz Kaderuppan, Newcastle University, Singapore

Shiraz is a Singaporean educator and data analytics enthusiast with extensive experience in enhancing deep neural network (DNN) architectures for feature recognition and extraction in image processing applications. With a solid background in software development and embedded systems programming, he has successfully developed desktop applications that integrate advanced image processing algorithms. Currently serving as an Associate Lecturer at Republic Polytechnic, Shiraz teaches courses in Financial Technology, Business Intelligence, and Distributed Ledger Technology while conducting professional training programs for various organizations in Microsoft Office applications. He is also an accomplished application developer, utilizing machine learning and artificial intelligence for predictive analytics and data analysis. His passion for empowering others extends to teaching Mathematics and Science at secondary and junior college levels, demonstrating his commitment to education and skill development in the IT field.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award: 

Shiraz S/O Kaderuppan stands out as a highly suitable candidate for the Best Researcher Award due to his extensive experience and impressive contributions to the field of data analytics and deep learning, particularly in image processing applications. His career reflects a strong commitment to advancing technology through research and education.

Education 🎓

  • Republic Polytechnic
    Diploma in Financial Technology, Business Intelligence & Distributed Ledger Technology
    Mar 2023 – Present

Work Experience 💼

  • Associate Lecturer
    Republic Polytechnic
    Mar 2023 – Present

    • Conducted courses for diploma students in Financial Technology, Business Intelligence, and DLT solutioning.
  • Corporate Trainer
    Self-Employed
    Jul 2014 – Present

    • Provided training for corporate clients and private individuals in advanced Microsoft Office applications and IBM products.
  • Application Developer
    Self-Employed
    May 2012 – Present

    • Developed desktop applications using C# .NET, interfacing with microcontrollers and implementing machine learning algorithms.
  • ML/AI Developer
    Self-Employed
    Sep 2008 – Present

    • Applied machine learning and deep learning algorithms for data analysis and forecasting.
  • Educator
    Self-Employed
    Aug 2010 – Present

    • Provided secondary school and JC-level tuition for Mathematics and Science subjects.
  • General Education Officer (Teacher)
    Ministry of Education
    Sep 2007 – Jan 2009

    • Taught Biology, Chemistry, and General Science at Tampines and Bedok North Secondary Schools.
  • Founder & Business Development Manager
    Self-Employed
    Jan 2005 – Jun 2007

    • Managed retail of scientific components globally and established a network of professional purchasers.

Achievements 🌟

  • Successfully conducted numerous training programs for companies and government bodies, focusing on advanced features of Microsoft Office for business intelligence and data analysis.
  • Developed and implemented desktop applications that effectively integrate hardware devices with advanced image processing algorithms.
  • Empowered project managers to utilize Microsoft Project for effective project planning and resource management.

Awards & Honors 🏆

  • Recognized for excellence in teaching and training methodologies at Republic Polytechnic and in corporate training programs.
  • Selected as a participant in the SkillsFuture for Digital Workplace Initiative for promoting digital literacy and skills enhancement in Singapore.

Publication Top Notes:

Θ-Net: A Deep Neural Network Architecture for the Resolution Enhancement of Phase-Modulated Optical Micrographs In Silico

O-Net: A Fast and Precise Deep-Learning Architecture for Computational Super-Resolved Phase-Modulated Optical Microscopy

Smart Nanoscopy: A Review of Computational Approaches to Achieve Super-Resolved Optical Microscopy

Masoud DANESHTALAB | deep learning | Best Researcher Award

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Prof. Masoud DANESHTALAB | deep learning | Best Researcher Award 

Prof. Masoud DANESHTALAB, Mälardalen University, Sweden.

Masoud Daneshtalab, Ph.D., Docent, Full Professor
Masoud Daneshtalab is a globally recognized scholar and Full Professor at Mälardalen University (MDU), Sweden. With over two decades of academic and professional excellence, he has made significant contributions to computer science and engineering, specializing in dependable systems, AI, and hardware/software co-design. A prolific researcher with an H-index of 35 and over 5,100 citations, Dr. Daneshtalab is included in the prestigious World’s Top 2% Scientists Ranking. He serves as the Scientific Director of Fundamental AI at MDU and collaborates internationally, holding adjunct professorships and contributing to cutting-edge research initiatives.

Professional Profile:

Google Scholar

Suitability of Masoud Daneshtalab for the Best Researcher Award

Dr. Masoud Daneshtalab is a highly suitable candidate for the “Research for Best Researcher Award,” based on his exceptional academic achievements and professional contributions. Here are the key reasons

Education

🎓 Academic Journey

  • Docent (2018): Qualified in Computer Science and Electronics, Mälardalen University, Sweden.
  • Ph.D. (2008–2011): Information and Communication Technology, University of Turku, Finland. Dissertation: Adaptive Implementation of On-Chip Networks under Prof. Hannu Tenhunen.
  • M.Sc. (2004–2006): Computer Engineering, University of Tehran, Iran. Thesis: Low Power Methods in Network-on-Chips under Prof. Ali Afzali-Kusha.
  • B.Sc. (1998–2002): Computer Engineering, Shahid Bahonar University of Kerman, Iran.

Experience

💼 Professional Contributions

  • Scientific Director (2024–Present): Fundamental AI, Mälardalen University, Sweden.
  • Full Professor (2020–Present): Innovation, Design & Engineering, MDU.
  • Adjunct Professor (2019–Present): Computer Systems, Tallinn University of Technology, Estonia.
  • Previous Roles: Associate Professor at MDU (2016–2020), EU Marie Curie Fellow at KTH Royal Institute of Technology (2014–2016), Lecturer at the University of Turku (2011–2014), and Researcher at the University of Tehran (2006–2008).

Research Interests

🔬 Key Areas

  • Optimization and robustness in deep learning models.
  • HW/SW co-design and heterogeneous computing.
  • Dependable systems, memory architectures, and interconnection networks.
  • Cutting-edge projects include sustainable AI, federated learning, and reliable autonomous systems.

Awards

🏆 Recognitions

  • Best Paper Awards: IEEE ECBS (2019), IEEE MCSoC (2018), and multiple HiPEAC Paper Awards (2013–2017).
  • Research Grants: Marie Skłodowska-Curie Fellowship (2014), Nokia Foundation (2009), and others.
  • Top Reviewer: IEEE Transactions on Computers (2013).
  • Fellowships: GETA, Helsinki University of Technology (2008–2011).

Publications

A review on deep learning methods for ECG arrhythmia classification

CITIED: 490

Time-Sensitive Networking in automotive embedded systems: State of the art and research opportunities

CITIED: 147

Routing algorithms in networks-on-chip

CITIED: 136

Smart hill climbing for agile dynamic mapping in many-core systems

CITIED: 125

EDXY–A low cost congestion-aware routing algorithm for network-on-chips

CITIED: 124

Deep Maker: A multi-objective optimization framework for deep neural networks in embedded systems

CITIED: 122

 

Prof. Yuguo Yu | Artificial Neural Awards | Best Researcher Award

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Prof. Yuguo Yu | Artificial Neural Awards | Best Researcher Award  

Prof. Yuguo Yu, Fudan University, China

Yuguo Yu, Ph.D., is a distinguished professor in Brain-inspired Artificial Intelligence and Computational Neuroscience at Fudan University, where he has been a faculty member since 2011. He currently serves as a professor at both the Research Institute of Intelligent Complex Systems and the National Key Laboratory of Medical Neurobiology. Yu obtained his Bachelor’s degree in Physics from Lanzhou University in 1995 and completed his Ph.D. in Condensed Matter Physics at Nanjing University in 2001. He pursued postdoctoral training in Computational/Behavior Neuroscience at Carnegie Mellon University from 2001 to 2004 and was an Associate Research Scientist at Yale University from 2005 to 2011, where he continues to contribute as a visiting Research Scientist since 2021. Yu has been recognized for his academic excellence through prestigious awards, including the Shanghai Eastern Scholar Professorship in 2013 and the Shanghai Excellent Academic Leader award in 2021. He is an active member of the Chinese Society of Computational Neuroscience and serves as an associate editor for several prominent journals, including IEEE Transactions on Cognitive and Developmental Systems and Frontiers in Computational Neuroscience. His research interests encompass brain-inspired neural networks, cellular mechanisms of energy-efficient cortical dynamics, synaptic learning mechanisms, and large-scale cortical network modeling, with over 100 publications in leading journals such as Nature and Neuron. Yu has also led or participated in numerous national foundation projects, advancing the field of computational neuroscience.

Professional Profile:

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Research for Best Researcher Award

Candidate Overview: Dr. Yuguo Yu is a prominent researcher and professor in Brain-inspired artificial intelligence and computational neuroscience at Fudan University. With extensive academic and research experience, he is a strong candidate for the Best Researcher Award due to his significant contributions to the field, impactful publications, and leadership roles.

Education

  • B.Sc. in Physics
    Lanzhou University, 1995
  • Ph.D. in Condensed Matter Physics
    Nanjing University, 2001
  • Postdoctoral Researcher in Computational Neuroscience
    Carnegie Mellon University, 2001–2004
  • Research Scientist in Neurobiology
    Yale University, 2005–2011

Work Experience

  • Professor
    Research Institute of Intelligent Complex Systems, Fudan University, 2020–Present
  • Professor
    National Key Laboratory of Medical Neurobiology, Fudan University, 2013–Present
  • Visiting Research Scientist
    Yale University School of Medicine, 2021–Present
  • Associate Research Scientist
    Department of Neuroscience, Yale University, 2005–2011

Research Interests:

  • Brain-inspired Intelligence and Computational Neuroscience
  • Neural Computation Model
  • Neural Coding Theory
  • Network Topology Analysis
  • Sensory Fusion Mechanism
  • Brain Connectome Atlas
  • Self-organizing Learning Algorithm
  • Multi-sensory Fusion Model
  • Low-power Mechanism of the Human Brain 🔍

Publication Top Notes

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