Alain Bernard Djimeli Tsajio | Apprentissage Machine (IA) | Best Researcher Award

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Prof. Alain Bernard Djimeli Tsajio | Apprentissage Machine (IA) | Best Researcher Award

Senior lecturer at University of Dschang, Cameroon.

Prof. Alain Bernard Djimeli Tsajio is a physicist, AI researcher, and telecommunications expert specializing in computer vision, machine learning, and cybersecurity. He holds a Ph.D. in Electronics from the University of Dschang and has over 20 years of experience in academia and research. As a faculty member at IUT Fotso Victor, University of Dschang, he has significantly contributed to curriculum development, student mentorship, and applied research in artificial intelligence. His work has been published in high-impact journals, and he actively collaborates on international research projects in AI-driven diagnostics, wireless networks, and intelligent security systems.

Publication Profile

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Educational Details

  • Ph.D. in Physics (Electronics), 2016 – University of Dschang, Cameroon

  • Diplôme d’Études Approfondies (DEA) in Physics (Electronics), 2005 – University of Yaoundé I, Cameroon

  • Maîtrise in Physics (Electronics), 2003 – University of Yaoundé I, Cameroon

  • Licence in Physics, 2000 – University of Yaoundé I, Cameroon

  • Baccalauréat C, 1995 – Lycée Classique de Bangangté, Cameroon

Professional Experience

Prof. Djimeli Tsajio is a Senior Lecturer and Researcher in Telecommunications and Networks at the IUT Fotso Victor, University of Dschang, Cameroon. Since 2005, he has been responsible for course coordination, student mentoring, and curriculum development. His teaching expertise covers a broad range of topics, including:

  • Multimedia Protocols and Quality of Service

  • Wireless Networks and Emerging Technologies

  • Cybersecurity and Artificial Intelligence

  • Information Theory and Cryptography

  • Telecommunication Protocols and High-Speed Networks

He has also served as an instructor at the CISCO Networking Academy, a guest lecturer at multiple universities, and a thesis advisor for Master’s and Ph.D. students in AI and Cybersecurity. His administrative contributions include student academic counseling, exam grading, and research program coordination.

Research Interest

  • Precision Agriculture (disease detection in plants)

  • Medical Diagnostics (breast cancer detection, leukocyte counting)

  • Network Security and Cybersecurity

  • AI-Based Intelligent Agents

Top Noted Publication

  • Solitons and other solutions of the nonlinear fractional Zoomeron equation

    • Authors: E. Tala-Tebue, Z. I. Djoufack, A. Djimeli-Tsajio, A. Kenfack-Jiotsa

    • Journal: Chinese Journal of Physics

    • Volume: 56 (3), Pages: 1232-1246

    • Year: 2018

    • Citations: 26

    • Summary: This paper presents soliton solutions and other exact solutions to the nonlinear fractional Zoomeron equation, leveraging advanced mathematical techniques in nonlinear wave dynamics and fractional calculus.

  • Improved detection and identification approach in tomato leaf disease using transformation and combination of transfer learning features

    • Authors: A. B. Djimeli-Tsajio, N. Thierry, L. T. Jean-Pierre, T. F. Kapche, P. Nagabhushan

    • Journal: Journal of Plant Diseases and Protection

    • Volume: 129 (3), Pages: 665-674

    • Year: 2022

    • Citations: 14

    • Summary: This study introduces an AI-based method for plant disease detection, utilizing transfer learning and feature transformation techniques to improve tomato leaf disease identification.

  • Quantum breathers associated with modulational instability in 1D ultracold boson in optical lattices involving next-nearest neighbor interactions

    • Authors: Z. I. Djoufack, E. Tala-Tebue, F. Fotsa-Ngaffo, A. B. Djimeli-Tsajio, F. Kapche-Tagne

    • Journal: Optik

    • Volume: 164, Pages: 575-589

    • Year: 2018

    • Citations: 13

    • Summary: This work explores quantum breathers and modulational instability in ultracold bosonic systems under optical lattice constraints, contributing to quantum physics and nonlinear dynamics.

  • Formalization method of the UML statechart by transformation toward Petri Nets

    • Authors: T. Noulamo, E. Tanyi, M. Nkenlifack, J. P. Lienou, A. Djimeli

    • Journal: IAENG International Journal of Computer Science

    • Volume: 45 (4), Pages: 32

    • Year: 2018

    • Citations: 8

    • Summary: This paper focuses on software modeling and verification, proposing a methodology for transforming UML statecharts into Petri Nets for improved formal verification of software systems.

  • Analysis of interest points of curvelet coefficients contributions of microscopic images and improvement of edges

    • Authors: A. Djimeli, D. Tchiotsop, R. Tchinda

    • Journal: arXiv preprint

    • Year: 2013

    • Citations: 8

    • Summary: This study investigates curvelet transform techniques for microscopic image analysis, improving edge detection in biological and medical imaging.

Conclusion

Prof. Alain Bernard Djimeli Tsajio is a strong candidate for the Best Researcher Award, given his significant contributions to AI, cybersecurity, and telecommunications. His work in AI-driven plant disease detection and medical diagnostics highlights both technical excellence and real-world impact. Strengthening his global presence, industry partnerships, and citation impact could further solidify his position as a leading researcher in his field.

 

Ayasha Malik | AI | Best Researcher Award

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Ms. Ayasha Malik | AI | Best Researcher Award

Assistant Professor at GL Bajaj Institute of Management and Research, Greater Noida, India.

A committed educator and researcher, Dr. Ayasha Malik specializes in Machine Learning and Information Security. With her expertise in artificial intelligence applications, she has made significant contributions to both teaching and research. Over the years, she has mentored students, published research in esteemed journals, and collaborated on projects focusing on AI-based cybersecurity solutions.

Her work aims to bridge theoretical advancements with real-world applications, making significant strides in secure AI technologies and human-computer interaction models.

Publication Profile

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Educational Details

Dr. Ayasha Malik holds a Ph.D. in Machine Learning from the School of Computer Science and Engineering, Sharda University (2021). She completed her M.Tech. in Information Security (2019) at the Ambedkar Institute of Advanced Communication Technologies and Research, Guru Gobind Singh Indraprastha University (NSIT), securing a CGPA of 8.65. Her B.Tech. in Computer Science & Engineering (2017) was awarded by Raj Kumar Goel Institute of Technology and Management, APJ Abdul Kalam Technical University, Lucknow, with a 71.68% score.

Dr. Malik completed her HSC (2013) in the Science stream from P.C School (CBSE) with 62.20% and her SSC (2011) from P.C Institute (CBSE) with a CGPA of 8.2.

Professional Experience

Dr. Malik has a strong academic background with over four years of teaching and research experience in reputed institutions:

  • GL Bajaj Institute of Management and Research, AKTU – Assistant Professor (Feb 2025–Present)
  • IIMT College of Engineering, AKTU – Assistant Professor (August 2023–Feb 2025)
  • Delhi Technical Campus (DTC), GGSIPU – Assistant Professor (Sept 2022–Aug 2023)
  • Noida Institute of Engineering and Technology (NIET), AKTU – Assistant Professor (Jan 2021–Aug 2022)
  • IEC Group of Institutions (IECGI), AKTU – Assistant Professor (Aug 2019–Nov 2020)
  • INMANTEC Institute, AKTU – Assistant Professor (Jan 2019–July 2019)

Research Interest

Dr. Malik’s research focuses on Machine Learning, Artificial Intelligence, and Information Security, with an emphasis on:

  • Deep learning applications in cybersecurity
  • Speech and image recognition models
  • AI-driven data privacy solutions
  • Human-computer interaction in intelligent systems

She is particularly interested in developing machine learning algorithms for secure computing environments, aiming to integrate AI into cybersecurity frameworks to enhance digital protection.

Author Metrics

Dr. Malik has contributed to several international journal publications and conferences, particularly in speech emotion recognition, AI-based security systems, and machine learning for cybersecurity. Her research has been cited in prominent academic circles, reinforcing her impact in the fields of artificial intelligence and information security.

Top Noted Publication

Conference Paper: Harnessing Data Mining for Improved Hindi Isolated Speech Recognition

Authors: Ayasha Malik, Veena Parihar, Shrikant A. Mapari, Malathy Sathyamoorthy, Shilpa Saini
Publication Type: Conference Paper
Citations: 0
Abstract:
This research explores the application of data mining techniques to enhance Hindi isolated speech recognition. The study leverages machine learning models to improve accuracy and efficiency in recognizing isolated words in the Hindi language. The work focuses on feature extraction, classification, and the impact of data mining methodologies on speech processing. The findings contribute to the development of intelligent speech interfaces for Hindi language users in human-computer interaction systems.

Book Chapter: Harnessing the Power of Artificial Intelligence in Software Engineering for the Design and Optimization of Cyber-Physical Systems

Authors: Shubham Tiwari, Ayasha Malik
Publication Type: Book Chapter
Citations: Not available
Abstract:
This book chapter examines how Artificial Intelligence (AI) is revolutionizing software engineering in the design and optimization of Cyber-Physical Systems (CPS). The chapter highlights AI-driven methodologies, including machine learning, deep learning, and reinforcement learning, to enhance CPS performance and security. It discusses AI-based automation, fault detection, and predictive analytics, offering insights into next-generation smart systems that integrate computational intelligence with physical infrastructure.

Conclusion

Dr. Ayasha Malik is a highly qualified researcher with strong expertise in machine learning, AI security, and human-computer interaction. Her academic background, publications, and teaching contributions make her a strong candidate for the Best Researcher Award.

To further solidify her standing, she can increase citations, enhance industry collaborations, and gain more international research exposure. With these improvements, she could be a leading AI researcher in cybersecurity and intelligent systems.

Omar Soufi | Intelligence Artificial | Best Researcher Award

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Dr. Omar Soufi | Intelligence Artificial | Best Researcher Award

Doctorate at Mohammed V University of Rabat Mohammadia School of Engineering, Morocco

Summary:

Dr. Omar Soufi is an expert in artificial intelligence and data science, with a specialized focus on remote sensing and geographic information systems (GIS). He completed his Ph.D. in Computer Engineering with a concentration in Artificial Intelligence at EMI Rabat in 2023, where his research centered on enhancing satellite image quality using deep learning techniques. With extensive experience in both academia and industry, Dr. Soufi has led numerous projects in AI, data science, and business intelligence. His contributions to the field include developing geospatial platforms for natural disaster risk management and implementing innovative solutions for satellite image processing. Dr. Soufi is currently advancing his research and professional endeavors as a postdoctoral researcher at CRTS Rabat, where he continues to explore the frontiers of AI and remote sensing.

Professional Profile:

👩‍🎓Education:

  • Ph.D. in Computer Engineering: Artificial Intelligence (2023)
    • Institution: EMI Rabat
    • Dissertation: Approche par Deep Learning au profit de la télédétection spatiale : Amélioration de la qualité d’images satellites et du procédé du capteur d’étoile.
  • Engineering Degree in Computer Science (2020)
    • Institution: EMI Rabat
    • Option: Ingénierie et Qualité Logicielle.
  • Engineering Degree in Information Systems Engineering (2020)
    • Institution: Polytechnique Grenoble, ENSIMAG
  • Fundamental License in Mechanical Engineering (2014)
    • Institution: ARM Merkèns
  • Diplôme des Études Universitaires (2015)
    • Institution: ARM Merkèns
  • Baccalauréat (2011)
    • Institution: 1ER LMR
    • Option: Sciences de Vie et de Terre

🏢 Professional Experience:

Dr. Omar Soufi is currently a Postdoctoral Researcher in Computer Engineering at CRTS Rabat, a position he has held since February 2024. In this role, he leads projects focused on artificial intelligence and data science, particularly for satellite image processing and spatial data analysis. Since 2022, Dr. Soufi has also been the Head of the Geomatics & Decision-Making Tools Department at CRTS Rabat, where he manages geomatics projects, develops decision-making tools, and oversees the implementation of geospatial platforms.

Previously, from 2020 to 2022, Dr. Soufi served as the Head of the Business Intelligence & Decision-Making Tools Department at CRTS Rabat. In this capacity, he directed business intelligence projects, developed data analytics solutions, and optimized decision-making processes. From 2017 to 2020, he was the Chief of Project at the Decision Support Center, managing decision support projects, implementing big data architectures, and developing e-learning platforms.

Dr. Soufi’s earlier professional experience includes serving as a Project Manager in the IT Department at CRTS Rabat from 2016 to 2017. He led IT projects, developed web applications, and implemented distributed data processing systems. His internships include a PFE internship on the super resolution of satellite images using deep learning (February 2020 – July 2020), an engineering internship on the development of a space station management platform at CRERS Rabat (July 2019 – August 2019), and an internship on the development of an agricultural campaign bulletin diffusion platform at CRTS Rabat (July 2019 – August 2019).

Research Interests

Dr. Omar Soufi’s research interests are centered on artificial intelligence, data science, remote sensing, and geographic information systems (GIS). His work focuses on applying deep learning techniques to improve the quality of satellite images and developing intelligent systems for spatial data analysis and geospatial applications. He is particularly interested in enhancing accessibility to high-resolution satellite imagery and advancing spacecraft attitude control using AI.

Top Noted Publication:

  • Study of Deep Learning-Based Models for Single Image Super-Resolution
    • Authors: O. Soufi, F.Z. Belouadha
    • Published in: Revue d’Intelligence Artificielle, 2022
    • Link: DOI: 10.18280/ria.360616
  • FSRSI: New Deep Learning-Based Approach for Super-Resolution of Multispectral Satellite Images
    • Authors: O. Soufi, F.Z. Belouadha
    • Published in: Ingénierie des Systèmes d’Information, 2023
    • Link: DOI: 10.18280/isi.280112
  • Deep Learning Technique for Image Satellite Processing
    • Authors: O. Soufi, F.Z. Belouadha
    • Published in: Intell Methods Eng Sci, 2023
  • Enhancing Accessibility to High-Resolution Satellite Imagery: A Novel Deep Learning-Based Super-Resolution Approach
    • Authors: O. Soufi, F.Z. Belouadha
    • Published in: Journal of Environmental Treatment Techniques, 2023
  • An Intelligent Deep Learning Approach to Spacecraft Attitude Control: The Case of Satellites
    • Authors: O. Soufi, F.Z. Belouadha
    • Status: Under review, 2023

Pablo Arnau González | Artificial Intelligence | Best Researcher Award

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Dr. Pablo Arnau González, Artificial Intelligence, Best Researcher Award

Doctorate at Universidad de Valencia, Spain

Summary:

Dr. Pablo Arnau González is a researcher with expertise in artificial intelligence and machine learning. He has made significant contributions to the fields of sentiment analysis, affective computing, and biometrics. Dr. González has conducted research on adapting conversational toolkits for sentiment analysis tasks and developing methodologies for identifying affect levels from EEG signals and visual stimuli. He has also contributed to the development of adaptive intelligent tutoring systems. With a background in computing and artificial intelligence, Dr. González has published several papers in reputable conferences and journals.

Professional Profile:

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👩‍🎓Education & Qualification:

PhD in Computing and Artificial Intelligence

  • University of the West of Scotland, 2020

Graduado o Graduada en Ingeniería Informática de Gestión y Sistemas de Información

  • Universitat de València, 2015

Professional Experience:

Dr. Pablo Arnau González has a diverse professional background, including positions in consulting, industry, and academia. Here is a summary of his previous professional positions:

  • 2022 – 2023: Postdoctoral Fellow (Margarita Salas) at Universitat de València.
  • 2021: Senior Consultant at SDG Consulting.
  • 2019 – 2021: Analyst at Cecotec Innovaciones, S.L.
  • 2019: Technologist in Digital Health at the University of the West of Scotland.

Research Interest:

Artificial Intelligence: Exploring AI algorithms and techniques for various applications such as sentiment analysis, affective computing, and intelligent tutoring systems.

Machine Learning: Investigating machine learning models and methodologies for processing EEG signals and visual stimuli to identify affect levels and subject identification.

Natural Language Processing: Adapting conversational toolkits and architectures for tasks like sentiment analysis, chatbots, and conversational agents.

Biometrics: Researching the use of EEG signals and image-evoked affect for biometric authentication and identification systems.

Adaptive Intelligent Tutoring Systems: Developing systems that can assess affective and behavioral responses to adaptively tailor educational content and interactions.

Publication Top Noted:

On adapting the DIET architecture and the Rasa conversational toolkit for the sentiment analysis task

  • Authors: M Arevalillo-Herráez, P Arnau-González, N Ramzan
  • Journal: IEEE Access
  • Year: 2022
  • Volume: 10
  • Pages: 107477-107487
  • Citation count: 11

A Method to Identify Affect Levels from EEG signals using two-dimensional Emotional Models

  • Authors: P Arnau-González, N Ramzan, M Arevalillo-Herráez
  • Conference: The 2016 European Simulation and Modelling Conference
  • Year: 2016
  • Pages: 299-303
  • Citation count: 8

Image-evoked affect and its impact on EEG-based biometrics

  • Authors: P Arnau-González, S Katsigiannis, M Arevalillo-Herráez, N Ramzan
  • Conference: 26th IEEE International Conference on Image Processing
  • Year: 2019
  • Citation count: 7

Single-channel EEG-based subject identification using visual stimuli

  • Authors: S Katsigiannis, P Arnau-González, M Arevalillo-Herráez, N Ramzan
  • Conference: 2021 IEEE EMBS International Conference on Biomedical and Health Informatics
  • Year: 2021
  • Citation count: 5

Affective and Behavioral Assessment for Adaptive Intelligent Tutoring Systems

  • Authors: L Marco-Giménez, M Arevalillo-Herráez, FJ Ferri, S Moreno-Picot, …
  • Conference: UMAP (Extended Proceedings)
  • Year: 2016
  • Citation count: 5

 

 

Jatin Pal Singh | Artificial Intelligence | Industry Insightful Paper Award

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Mr. Jatin Pal Singh, Artificial Intelligence, Industry Insightful Paper Award

Jatin Pal Singh at Amazon Web Services INC, United States

Summary:

Jatin Pal Singh is a seasoned professional in the technology sector, currently serving as the Principal Solutions Architect at Amazon Web Services (AWS) in Seattle, WA. With a career spanning over two decades, he has showcased his expertise and leadership in various roles within AWS, starting as a Database Engineer and progressing to Senior Solutions Architect before assuming his current position.

Jatin holds a Bachelor of Technology degree, earned from his studies between 2000 and 2004. His commitment to professional development is evident through certifications such as AWS Certified SA Professional, AWS Certified Devops Assoc, and Oracle Certified Professional in Database Administration. Additionally, he has pursued certifications in Generative AI, Apache Spark, and DataBricks through Coursera, showcasing his dedication to staying at the forefront of technological advancements.

Professional Profile:

Google Scholar Profile 

👩‍🎓Education & Qualification:

Jatin Pal Singh’s educational and professional development background is outlined as follows:

Bachelor of Technology (2000-2004): Jatin Pal Singh earned a Bachelor of Technology degree, completing his undergraduate studies between 2000 and 2004.

Certifications:

AWS Certified SA Professional

AWS Certified Devops Assoc

Oracle Certified Professional – 8i/9i/10g/11g Database Administrator

Coursera Certifications:

  • Generative AI Certification
  • Apache Spark Certification
  • DataBricks Certification

ITIL Certification

Six Sigma Certification

These certifications reflect Jatin Pal Singh’s commitment to continuous learning and professional development, covering a range of relevant areas such as cloud services, database administration, artificial intelligence, big data processing, and IT service management methodologies. These qualifications demonstrate his expertise and proficiency in various domains, aligning with contemporary technology trends and best practices.

Experience:

Jatin Pal Singh’s professional work experience showcases a progressive journey in the technology sector:

Principal, Solutions Architect | Amazon Web Services, Seattle, WA August 2022 – Present

Senior Solutions Architect | Amazon Web Services, Seattle, WA April 2019 – August 2022

Solutions Architect | Amazon Web Services, Seattle, WA April 2018 – April 2019

Database Engineer | Amazon Web Services, Seattle, WA April 2018 – April 2019

Associate Consultant | Tata Consultancy Services, St Paul, MN September 2004 – August 2014

Throughout his tenure, Jatin Pal Singh has played pivotal roles, progressively advancing from Associate Consultant at Tata Consultancy Services to his current position as Principal Solutions Architect at Amazon Web Services. His extensive experience in various roles within Amazon Web Services underscores his expertise in the field.

Accomplishments:

Jatin Pal Singh has demonstrated exceptional achievements and leadership in the following areas:

Practice Development:

Instrumental in scaling partner business from $1M to $25M within a year. Established relationships with key business and technical decision-makers, created practice frameworks, and developed collaterals such as sales battle cards, offerings, differentiators, proof of concept, and demos. Specialized in AWS Cloud solutions, particularly in Database, Analytics, and AI/ML services.

Thought Leadership:

Generated impactful technical collateral, including blogs and whitepapers, reaching an extensive audience of 50,000+ views. Played a pivotal role in closing multiple deals, addressing challenges in AWS services implementation through innovative architecture solutions. Led technical presales thought leadership in diverse domains such as Healthcare, Artificial Intelligence, Analytics, Migrations, Resilience, and Replication. Produced AWS ReInvent YouTube videos and chalk talks widely utilized by clients for tier1 workloads.

Solution Architecture:

Developed tools, accelerators, and solution architecture frameworks to address custom customer challenges. Created repeatable solutions and blueprints for broader adoption. Resolved technical blockers for customer opportunities by providing best practices, managing escalations, and offering hands-on troubleshooting or workarounds.

Trusted Advisor:

Collaborated with internal stakeholders, including engineering, product, and sales teams, to build strong relationships with customer and partner technical specialists. Implemented a structured feedback mechanism program across multiple teams, influencing product roadmaps based on customer requirements. Jatin Pal Singh’s expertise lies in being a trusted advisor and facilitator of effective collaboration within the organization.

Publication Top Noted:

“An integrative perspective on the role of touch in the development of intersubjectivity”

  • Published in Brain and Cognition, 2022
  • Volume 163, Page 105915
  • Citation Count: 6

“Testing the Magnitude of Correlations Across Experimental Conditions”

  • Published in Frontiers in Psychology, 2022
  • Volume 13 (860213), Pages 1-9
  • Citation Count: 6

“Brain and behavioral contributions to individual choices in response to affective–cognitive persuasion”

  • Published in Cerebral Cortex, 2022
  • Volume 5
  • Citation Count: 5

“Probabilistically Weighted Multilayer Networks disclose the link between default mode network instability and psychosis-like experiences in healthy adults”

  • Published in NeuroImage, 2022
  • Volume 257 (119291), Pages 1-11
  • Citation Count: 3

“Appropriately tuning stochastic-psychometric properties of the Balloon Analog Risk Task”

  • Published in Frontiers in Psychology, 2022
  • Volume 13
  • Citation Count: 3