Mr. Koagne Silas | Neural Networks | Pioneer Researcher Award

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Mr. Koagne Silas | Neural Networks | Pioneer Researcher AwardΒ 

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

πŸ… Summary of Suitability Pioneer Researcher AwardΒ 

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.

πŸŽ“ Education Background

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

    • 🧠 Research Focus: Analog Artificial Neural Networks

    • πŸ‘¨β€πŸ« Supervisor: Prof. Geh Wilson Ejuh

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

    • πŸ“˜ Thesis: Specification and implementation of multilayer perceptron analog artificial neural networks

    • πŸ‘¨β€πŸ« Supervisor: Dr. Djimeli Tsajio Alain B.

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

  • DIPET 2 in Electronics – University of Bamenda (πŸ“… July 2020)

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

  • DIPET 1 in Electronics – University of Bamenda (πŸ“… Aug 2018)

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

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

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

  • FSLC – Ecole Primaire Bilingue de la Promotion, Mbouda (πŸ“… June 2008)

πŸ’Ό Work Experience

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

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

  • Electronics Teacher – Government Technical High School Bambui (πŸ“… 2017–2018)

  • Internship – Electronics & Maintenance

    • πŸ“ HYTECHS, YaoundΓ© (πŸ“… 2019)

    • πŸ”§ Worked on printer maintenance & installation

  • Internship – Electrical Network Installation

    • πŸ“ MEECH CAM Sarl, YaoundΓ© (πŸ“… 2016)

    • ⚑ Focus on underground cable installation and high voltage network

πŸ† Achievements & Awards

  • βœ… Successfully designed and implemented:

    • πŸ€– An analog artificial neural network (M.Sc. Thesis)

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

    • πŸ›‚ An RFID-based attendance system with automated doors

  • πŸ“š Published and presented academic work in medical physics and embedded systems

  • πŸ‘¨β€πŸ« Contributed to higher education through teaching and mentoring roles across several institutions

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

  • πŸ’» Advanced skills in MATLAB, Arduino, MikroC, Cadence Virtuoso, PSPICE & Proteus

  • πŸ—£οΈ Bilingual in English and French – great asset for teaching and collaboration

PublicationΒ Top Notes:

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

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

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

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:Β 

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 πŸŽ“

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

Work Experience πŸ’Ό

  • 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 πŸ†

  • 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.

PublicationΒ 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

Prof. Jin Ho Suh | Deep Neural Network Awards | Best Researcher Award

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Prof. Jin Ho Suh | Deep Neural Network Awards | Best Researcher Award

Prof. Jin Ho Suh, Pukyong National University, South Korea

Dr. Jin-Ho Suh is a distinguished professor and expert in robotics, currently leading the Field Robotics Laboratory (FRLab) within the Major of Mechanical System Engineering at Pukyong National University, South Korea. With a Ph.D. in Control Engineering from the Tokyo Institute of Technology, Japan, and over two decades of academic and professional experience, Dr. Suh has significantly contributed to the fields of robotics and mechanical systems. He has held prominent roles, including Director of the Institute of Control, Robotics, and Systems, and is a Senior Member of IEEE. His leadership extends to national initiatives as the Chairman of the National Core Technology Committee for Robotics in South Korea and as an expert member of the Presidential Advisory Council on Science & Technology.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award: Prof. Jin-Ho Suh

Prof. Jin-Ho Suh, a distinguished researcher in the field of robotics and control engineering, holds a Ph.D. in Control Engineering from the Tokyo Institute of Technology and currently serves as a professor at Pukyong National University in South Korea. His extensive academic and professional experience, combined with significant contributions to the field, makes him an excellent candidate for the Best Researcher Award.

Education πŸŽ“

  • Ph.D. in Control Engineering
    Tokyo Institute of Technology, Japan (Dec 1998 – Mar 2002)
  • Master of Engineering
    Graduate School of Engineering, Pukyong National University, South Korea (Mar 1996 – Feb 1998)
  • Bachelor of Science in Mathematics
    Hanyang University, South Korea (Mar 1989 – Feb 1993)

Work Experience πŸ› οΈ

  • Professor (Sep 2018 – Present)
    Major of Mechanical System Engineering, Pukyong National University
  • Senior Member (Nov 2022 – Present)
    Institute of Electrical and Electronics Engineers (IEEE)
  • Director
    • Institute of Control, Robotics, and Systems (Jan 2022 – Present)
    • Korean Society for Precision and Engineering (Jan 2020 – Present)
    • Korea Robotics Society (Jan 2018 – Present)
    • Korean Society for Power System Engineering (Jan 2017 – Present)
  • Chairman of the National Core Technology Committee (Robot) (Nov 2017 – Present)
    Korean Association for Industrial Technology Security
  • Expert Member (Jan 2021 – Present)
    Presidential Advisory Council on Science & Technology, South Korea
  • Adjunct Professor (Dec 2013 – Aug 2018)
    Department of Mechanical Engineering, POSTECH
  • Director of R&D Division (Apr 2006 – Aug 2018)
    Korea Institute of Robotics and Convergence Technology (KIRO)
  • Post-Doctoral Fellow (Jun 2003 – Feb 2006)
    National Research Laboratory, Dong-A University

Achievements πŸ†

  • Patents
    • 28 patents (7 international PCT)
  • Publications
    • 14 papers in international journals (13 SCI)
    • 23 papers in domestic journals (15 SCOPUS)
    • 15 papers in international conferences
    • 60 papers in domestic conferences

Awards and Honors 🌟

  • Director Roles in Leading Engineering Societies
    • Institute of Control, Robotics and Systems
    • Korea Robotics Society
    • Korean Society for Precision and Engineering
  • Presidential Advisory Council Member
    • Significant contributions to national robotics and precision engineering strategies.
  • Chairman, National Core Technology Committee (Robot)
    • Recognized leader in industrial robotics technology and security.

PublicationΒ Top Notes

Artificial Neural Network for Glider Detection in a Marine Environment by Improving a CNN Vision Encoder

Development of a Multi-Robot System for Pier Construction

Model-Free RBF Neural Network Intelligent-PID Control Applying Adaptive Robust Term for Quadrotor System

Development of Fishcake Gripping and Classification Automation Process Based on Suction Shape Transformation Gripper

Estimation and Control of a Towed Underwater Vehicle with Active Stationary and Low-Speed Maneuvering Capabilities

Adaptive Robust RBF-NN Nonsingular Terminal Sliding Mode Control Scheme for Application to Snake Robot’s Head for Image Stabilization

Development of Recovery System for Underwater Glider

Dr. Seyed Reza Nabavi | Nueral Network Awards | Best Researcher Award

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Dr. Seyed Reza Nabavi | Nueral Network Awards | Best Researcher AwardΒ 

Dr. Seyed Reza Nabavi, University of Mazandaran, Iran

Dr. Seyed Reza Nabavi is an Associate Professor of Applied Chemistry in the Department of Applied Chemistry at the University of Mazandaran, Babolsar, Iran. he earned his Ph.D. in Applied Chemistry from the University of Tabriz in 2009, focusing on hybrid modeling and artificial intelligence applications for olefin process optimization. As a visiting scholar at the National University of Singapore in 2008, Dr. Nabavi further honed his expertise in chemical and biomolecular engineering. His teaching repertoire spans diverse topics, including transport phenomena, chemical reactor design, and chemical process modeling at both undergraduate and postgraduate levels. A prolific researcher, his interests lie in polymer nanotechnology, catalytic processes, machine learning in chemical process optimization, and pyrolysis. Notably, he has collaborated on significant projects, such as studying coke formation and inhibitors in naphtha thermal cracking at the bench scale, bridging academia and industry. Married and based in Iran, Dr. Nabavi has received recognition for his academic excellence, including being the top-ranked B.Sc. graduate.

Professional Profile:

ORCID

Suitability for Best Researcher Award: Seyed Reza Nabavi

Based on the provided curriculum vitae, Dr. Seyed Reza Nabavi demonstrates exceptional qualifications that make him a strong candidate for the Best Researcher Award. Below is a summary of his key accomplishments and attributes supporting his suitability for this recognition

πŸŽ“ Educational Background

  • Ph.D. in Applied Chemistry (2009), University of Tabriz 🧬
    Thesis: Application of Hybrid Modeling and Artificial Intelligence in Modeling and Optimization of Olefin Processes.

    • Visiting Scholar: National University of Singapore (Apr-Dec 2008).
  • M.Sc. in Applied Chemistry (2003), University of Tabriz 🧡
    Thesis: Preparation and Characterization of Conducting Polyaniline/Nylon-6 Composite Fibers.
  • B.Sc. in Applied Chemistry (2000), University of Sistan and Baluchestan πŸ›οΈ
    • πŸŽ–οΈ First Rank among graduate students.

πŸ‘¨β€πŸ« Teaching Experience

  • Expertise in teaching at M.Sc. and B.Sc. levels πŸ“š, including advanced courses:
    • Transport Phenomena, Design of Experiments (DOE), Chemical Reactors, Process Control, and Petrochemical Processes.
    • Proficient in Modeling and Simulation and Unit Operation Laboratories.

πŸ”¬ Research Interests

  • Nanotechnology of Polymers: Electrospinning and Nanofiber Membranes 🧡.
  • Catalytic Processes: Ozonation, Photocatalysts, and Reaction Engineering βš—οΈ.
  • Modeling and Optimization: Applying Machine Learning and Evolutionary Algorithms πŸ€–.
  • Thermal Cracking & Pyrolysis: Exploring Coke Formation and Mitigation πŸ”₯.

πŸ… Academic Positions

  • Associate Professor: 2022 – Present, University of Mazandaran 🏫.
  • Assistant Professor: 2012 – 2022, University of Mazandaran.

πŸ§ͺ Research Highlights

  • Lead researcher in projects like Coke Formation and Inhibitors in thermal cracking of naphtha (collaboration with Tabriz Petrochemical Company) πŸ›’οΈ.
  • Published impactful research on polymers, reaction engineering, and optimization using cutting-edge AI techniques.

Publication top Notes:

Multi-Criteria Decision Making in Chemical and Process Engineering: Methods, Progress, and Potential

A liter scale synthesis of hierarchically mesoporous UiO-66 for removal of large antibiotics from wastewater

Data-Based Modeling, Multi-Objective Optimization and Multi-Criteria Decision Making of a Catalytic Ozonation Process for Degradation of a Colored Effluent

A bacterial cellulose-based LiSrVO4:Eu3+ nanosensor platform for smartphone sensing of levodopa and dopamine: point-of-care diagnosis of Parkinson’s disease

Parametric optimization of poly(ether sulfone) electrospun membrane for effective oil/water separation

Deep Learning Aided Multi-Objective Optimization and Multi-Criteria Decision Making in Thermal Cracking Process for Olefines Production