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

Aurélie Cools | Deep Neural Networks | Best Researcher Award

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Aurélie Cools | Deep Neural Networks | Best Researcher Award

Ms. Aurélie Cools, University of Mons, Belgium.

Aurélie Cools is a Ph.D. candidate in Engineering Sciences at the University of Mons (UMons), specializing in deep neural networks and dimensionality reduction for CBIR search engines. She holds dual Master’s degrees: Civil Engineering in Computer Science and Management (Summa Cum Laude) and Management Engineering (Magna Cum Laude), showcasing her expertise in software engineering, business analytics, and optimization. Alongside her research, she contributes as a teaching assistant at UMons. With a strong foundation in Python, SQL, and PyTorch, Aurélie is multilingual and adept at problem-solving, team management, and communication. 🌟👩‍💻📚

Publication Profile

Orcid

Education and Experience

Education 📘

  • Ph.D. in Engineering Sciences
    • Institution: University of Mons (UMons), Polytechnic Faculty
    • Thesis Topic: CBIR search engine with deep neural networks and dimensionality reduction methods
    • Duration: 2021 – Present
  • Master’s in Civil Engineering (Summa Cum Laude)
    • Institution: UMons, Polytechnic Faculty
    • Specialization: Software Engineering and Business Intelligence
    • Duration: 2018 – 2021
  • Master’s in Management Engineering (Magna Cum Laude)
    • Institution: UCL Mons
    • Specialization: Business Analytics – Logistics and Transportation
    • Duration: 2015 – 2017
  • Bachelor’s in Management Engineering (Cum Laude)
    • Institution: UCL Mons
    • Duration: 2012 – 2015

Experience 💼

  • Teaching Assistant & Ph.D. Student
    • Institution: UMons
    • Duration: September 2021 – Present
  • Credit Analyst
    • Institution: CPH Bank, La Louvière
    • Duration: July 2017 – August 2021
  • Student Worker
    • Institution: Colruyt Group, Mons
    • Duration: March 2013 – December 2016

Suitability For The Award

Ms. Aurélie Cools is an outstanding candidate for the Best Researcher Award, combining academic excellence with impactful research. Currently pursuing a Ph.D. in Engineering Sciences at the University of Mons, her work on CBIR systems using deep neural networks and dimensionality reduction demonstrates innovation and technical expertise. With dual Master’s degrees in Civil and Management Engineering earned with high honors, Aurélie excels in both research and practical applications. Her proficiency in programming, data analysis, and problem-solving, coupled with strong communication skills, makes her a deserving nominee.

Professional Development

Aurélie excels in the realms of engineering and management, leveraging cutting-edge techniques like deep neural networks and dimensionality reduction. 📊💡 Her research bridges technical and analytical fields, emphasizing CBIR technologies for efficient image retrieval. With years of experience as a teaching assistant, she fosters innovation and critical thinking among students. Aurélie’s blend of programming skills in Python, SQL, and PyTorch, coupled with proficiency in tools like MongoDB and Excel, enhances her adaptability in diverse challenges. A polyglot and skilled communicator, she thrives in team management, problem-solving, and delivering impactful solutions. 🚀🌍✨

Research Focus

Aurélie’s research focuses on developing advanced Content-Based Image Retrieval (CBIR) systems, leveraging deep neural networks and cutting-edge dimensionality reduction techniques to enhance image search and analysis efficiency. Her interdisciplinary approach combines software engineering, artificial intelligence, and data science for innovative solutions. 🖼️🤖📊 With a keen interest in the practical applications of CBIR, such as medical imaging or multimedia management, Aurélie contributes to expanding the potential of machine learning in real-world scenarios. Her expertise lies at the intersection of engineering precision and computational intelligence, making her a significant contributor to AI-driven image processing. 🌟🔍📈

Publication Top Notes

  • A New Comparative Study of Dimensionality Reduction Methods in Large-Scale Image Retrieval (2022) 📚 | Published: 2022-05-13
  • A Comparative Study of Reduction Methods Applied on a Convolutional Neural Network (2022) 📖 | 🗓️ Published: 2022-04-28

Mr. Seyed matin malakouti | Deep learning Awards | Best Researcher Award

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Mr. Seyed matin malakouti | Deep learning Awards | Best Researcher Award

Mr. Seyed matin malakouti, University of Rijeka, Croatia

Seyed Matin Malakouti is an accomplished electrical engineer and researcher specializing in control systems engineering and machine learning. He completed his Master of Science in Electrical Engineering from the University of Tabriz, Iran, after earning his Bachelor’s degree from Isfahan University of Technology. His research spans various applications of machine learning, including wind power generation prediction, heart disease classification using ECG data, and solar farm power generation forecasting. Seyed’s work has resulted in several high-impact publications in prestigious journals, with his research on wind energy and machine learning techniques receiving significant citations. He has also been involved in cutting-edge projects such as predicting global temperature change and advancing renewable energy solutions. In recognition of his contributions, Seyed has received multiple awards, including the Best Researcher Award at the International Conference on Cardiology and Cardiovascular Medicine in 2023, and nominations for Best Paper and Best Researcher Awards in other international conferences. Additionally, he actively contributes to the scientific community as a peer reviewer for numerous journals in the fields of artificial intelligence, environmental sciences, and electrical engineering.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Seyed Matin Malakouti is a highly qualified and accomplished researcher in the field of Electrical Engineering, specializing in Control Systems, Machine Learning, and Data Science. His impressive academic background includes a Master’s degree in Electrical Engineering from the University of Tabriz and a Bachelor’s degree from Isfahan University of Technology.

Education & Training 🎓

  • 2020 – 2022: M.Sc. in Electrical Engineering – Control System Engineering, University of Tabriz, Iran
  • 2014 – 2019: B.Sc. in Electrical Engineering, Isfahan University of Technology, Iran

Awards & Honors 🏆

  • 2023: Best Researcher, International Conference on Cardiology and Cardiovascular Medicine
  • 2023: Nominated for Best Paper Award, International Research Awards on Mathematics and Optimization Methods
  • 2024: International Young Scientist Awards, Best Researcher Category

Technical Skills 🛠️

  • Machine Learning 🤖
  • Data Science 📊
  • Programming Languages: MATLAB, Python 💻

Peer Review Activities 🧐

Seyed has reviewed articles for prestigious journals, such as:

  • IEEE Access
  • Artificial Intelligence Review
  • BMC Public Health
  • Environmental Monitoring and Assessment 🌱

Publication top Notes:

Machine learning and transfer learning techniques for accurate brain tumor classification

ML: Early Breast Cancer Diagnosis

Advanced techniques for wind energy production forecasting: Leveraging multi-layer Perceptron + Bayesian optimization, ensemble learning, and CNN-LSTM models

Babysitting hyperparameter optimization and 10-fold-cross-validation to enhance the performance of ML methods in predicting wind speed and energy generation

Discriminate primary gammas (signal) from the images of hadronic showers by cosmic rays in the upper atmosphere (background) with machine learning

Estimating the output power and wind speed with ML methods: A case study in Texas