Mihir Parekh | Machine Learning | Best Researcher Award

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Mr. Mihir Parekh | Machine Learning | Best Researcher Award

Research Scholar at Nirma University, India

Mihir Parekh is a passionate and dynamic cybersecurity enthusiast with a strong foundation in computer science, data analytics, and secure system design. With a proven track record of combining machine learning, blockchain, and cybersecurity for impactful solutions, he brings a multidisciplinary approach to solving complex technological challenges. Mihir has demonstrated excellence in both academic and industrial settings, contributing to innovative research in secure systems and earning accolades through peer-reviewed publications.

Publication Profile 

Google Scholar

Educational Background 🎓

  • M.Tech in Computer Science and Engineering (Cyber Security)
    Nirma University, Ahmedabad
    08/2022 – 06/2024 | CGPA: 9.21
    Focus: Cybersecurity, Blockchain, Data Analysis, Machine Learning

  • Bachelor of Engineering in Information Technology
    G.H. Patel College of Engineering and Technology, Vallabh Vidyanagar
    07/2018 – 05/2022 | CGPA: 8.22

Professional Experience 💼

  • Data Analyst
    Contrado Imaging India Pvt. Ltd., Ahmedabad
    06/2023 – 10/2023

    • Performed data cleaning and preprocessing using Python.

    • Developed SQL queries to fetch and analyze data.

    • Used Kibana and Elasticsearch for data visualization.

  • Business Process Analyst
    Kevit Technologies, Rajkot
    12/2021 – 07/2022

    • Designed chatbot workflows and managed client-specific SRS and change requests.

    • Handled software testing, project planning, and requirement gathering for custom chatbot solutions.

Research Interests 🔬

  • Cybersecurity and Digital Forensics

  • Blockchain Applications and Cryptographic Protocols

  • Machine Learning and Deep Learning

  • Federated Learning & Secure Data Sharing

  • Anomaly Detection and Fraud Prevention

  • Secure Industrial IoT Systems

Awards and Honors🏆✨

  • 🏆 Published Journal Paper:
    Blockchain Forensics to Prevent Cryptocurrency Scams
    Computers & Electrical Engineering (Impact Factor: 5.5)

  • 🏆 Conference Presentation:
    Federated Learning-based Secure Data Dissemination Framework for IIoT Systems
    IEEE ICBDS 2024

  • 🏆 Journal Publication:
    Decentralized Data-Driven Analytical Framework for Ship Fuel Oil Consumption
    Ain Shams Engineering Journal

  • 🎖️ Infineon Hackathon Finalist – AES-128 Cryptanalysis Challenge

Conclusion🌟

Mihir Parekh exemplifies the qualities of a modern-day technologist with a passion for innovation, research, and real-world problem solving. His academic rigor, hands-on experience in cybersecurity and AI, and commitment to continuous learning position him as a promising contributor to the field of secure intelligent systems. Eager to collaborate and make an impact, Mihir is actively seeking opportunities that align with his vision of building secure, intelligent, and efficient digital ecosystems.

Publications 📚

📘 Parekh, M., Jadav, N. K., Tanwar, S., Pau, G., Alqahtani, F., & Tolba, A. (2025). ANN and blockchain-orchestrated decentralized data-driven analytical framework for ship fuel oil consumption. Applied Ocean Research, 158, 104553.
🔗 https://doi.org/10.xxxxx/aor.2025.104553
📊 Keywords: Artificial Neural Networks, Blockchain, Maritime Fuel Analytics

📕 Parekh, M., Jadav, N. K., Pathak, L., Tanwar, S., & Yamsani, N. (2024). Federated Learning-based Secure Data Dissemination Framework for IIoT Systems Underlying 5G. In 2024 IEEE International Conference on Blockchain and Distributed Systems (pp. xx–xx). IEEE.
📡 Keywords: Federated Learning, 5G, IIoT, Cybersecurity
📍 Conference Paper

📄 Parekh, M. (2024). Decentralized Data-Driven Analytical Framework for Ship Fuel Oil Consumption. Institute of Technology.
🏛️ Institutional publication / Thesis
🌐 Focus: Data Analytics, Maritime Efficiency

Yousef Daradkeh | Computer Science | Best Academic Researcher Award

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Prof. Dr. Yousef Daradkeh | Computer Science | Best Academic Researcher Award

Professor at Prince Sattam Bin Abdulaziz University, Jordan

Prof. Dr. Yousef Daradkeh is a distinguished professor of Computer Engineering and Information Technology at the Department of Computer Engineering and Information, College of Engineering, Prince Sattam bin Abdulaziz University, Saudi Arabia. He holds a Doctor of Engineering Sciences in Computer Engineering and Information Technology and has over 19 years of extensive academic and administrative experience. Prof. Daradkeh is internationally recognized for his research and teaching in software engineering, computer networks, artificial intelligence, and cybersecurity. As an academic leader, researcher, author, and workshop facilitator, he has significantly contributed to scientific communities through over 128 peer-reviewed publications, multiple books, and active participation in international conferences and editorial boards.

Publication Profile 

Google Scholar

Educational Background 🎓

  • Ph.D. in Computer Engineering and Information Technology
    Belarusian State University of Informatics and Radioelectronics, 2006

    • Dissertation: Interpretation of Polymorphous Networks Models in Real-Time Allocation Systems

    • Accredited by the Higher Education Accreditation Commission (HEAC)

  • Postdoctoral Research Fellowships

    • University of Calgary, Canada (2007–2009) – Systems, Networks, and Devices of Telecommunications

    • University of New South Wales, Australia (2010) – Computer Science and Engineering

    • Massey University, New Zealand (2011) – School of Engineering and Advanced Technology

    • Istanbul Technical University, Turkey (2023–2024) – Electronics and Communication Engineering

  • M.Sc. in Software Engineering
    Belarusian National Technical University, 2003

    • Thesis: Mathematical and Software Optimization of Models of Power Equipment Operations

  • B.Sc. in Computer Engineering
    Technical University of Moldova, 2000

    • Graduation Project: Device for Transcendent Functions Calculation

Professional Experience 💼

  • Current Position:

    • Full Professor & Assistant Dean for Administrative Affairs
      Prince Sattam bin Abdulaziz University, Saudi Arabia

  • Previous Academic Roles:

    • University of Calgary, Canada – Postdoctoral Researcher & Faculty Developer

    • The University of Jordan – Faculty Member, Systems and Information Technology

    • Al-Balqa Applied University, Jordan – Faculty Member, Department of IT

    • Yarmouk University – Instructor, Computer and Information Centre

    • AL-Hussein Bin Talal University – Faculty Member, Engineering & IT

    • Jadara University – Faculty, Department of Software Engineering

    • Kazakh University of Economics, Finance, and International Trade – Online Course Lecturer

  • Other Roles:

    • Designed accredited computer engineering and IT courses

    • Conducted workshops on scientific writing and research methodology

    • Editorial and scientific committee member for numerous international journals and conferences

Research Interests 🔬

  • Wireless Networking and Telecom Systems

  • Modeling of Discrete and Polymorphous Systems

  • Computer Systems and Networks

  • Artificial Intelligence & Data Science

  • Machine Learning & Deep Learning

  • Vision Computing and Digital Image Processing

  • Cybersecurity and Information/Economic Security

  • Agent-Based and Context-Aware Software Engineering

  • E-Government and E-Learning Applications

  • Location-Based Services (LBS) and Geo Services

  • Knowledge Representation and Reasoning

  • Optimization and Real-Time Systems

  • Web and Java Development, Databases

Awards and Honors🏆✨

  • Higher Distinction Scientific Awards – From International Universities

  • Certificate of Appreciation – Ministry of Youth and Sport, Jordan (1999)

  • Faculty Teaching Certificate (FTC) – University of Calgary, Canada (2008)

  • Care Services Certificates – University of Calgary (2008)

  • IT Management Professional Award – Microsoft, Excellent Train, Jordan (2011)

  • Staff Development Certificate – University of Jordan (2012)

  • Life Ambassador First Aid Training Certificate – Riyadh

  • Certificate of English Language (CEL) – AMIDEAST, Jordan

  • Certificate of Russian & Romanian Languages – TUM, BNTU, BSUIR

Conclusion🌟

Prof. Dr. Yousef Daradkeh is a visionary academic leader and prolific researcher who has made significant contributions to the fields of computer engineering, software systems, and emerging technologies. His work continues to bridge theoretical advancements with practical applications, particularly in improving security, efficiency, and intelligence in digital systems. Through his extensive teaching, research, international collaborations, and service to the academic community, Prof. Daradkeh remains a highly influential figure in engineering education and innovation.

Publications 📚

  • 📡 6G mobile communication technology: Requirements, targets, applications, challenges, advantages, and opportunities
    🧾 Alexandria Engineering Journal 64, 245-274
    👥 Cited by: 360 | 📅 Year: 2023

  • 🧠 A hybrid deep learning-based approach for brain tumor classification
    🧾 Electronics 11 (7), 1146
    👥 Cited by: 248 | 📅 Year: 2022

  • 🚗 Key challenges, drivers and solutions for mobility management in 5G networks: A survey
    🧾 IEEE Access 8, 172534-172552
    👥 Cited by: 180 | 📅 Year: 2020

  • 🔍 Tools for fast metric data search in structural methods for image classification
    🧾 IEEE Access 10, 124738-124746
    👥 Cited by: 104 | 📅 Year: 2022

  • 🎗️ Intelligent hybrid deep learning model for breast cancer detection
    🧾 Electronics 11 (17), 2767
    👥 Cited by: 101 | 📅 Year: 2022

  • 🤖 Development of effective methods for structural image recognition using fuzzy logic
    🧾 IEEE Access 9, 13417-13428
    👥 Cited by: 98 | 📅 Year: 2021

  • 📷 Methods of classification of images based on statistical distributions
    🧾 IEEE Access 9, 92964-92973
    👥 Cited by: 90 | 📅 Year: 2021

  • ✈️ Handover management of drones in future mobile networks: 6G technologies
    🧾 IEEE Access 9, 12803-12823
    👥 Cited by: 89 | 📅 Year: 2021

  • 🧱 Classification of Images Based on a System of Hierarchical Features
    🧾 Computers, Materials & Continua 72 (1)
    👥 Cited by: 83 | 📅 Year: 2022

  • 🔧 Handover parameters optimisation techniques in 5G networks
    🧾 Sensors 21 (15), 5202
    👥 Cited by: 71 | 📅 Year: 2021

 

Francisco Mena | Machine Learning | Best Researcher Award

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Mr. Francisco Mena | Machine Learning | Best Researcher Award

PhD Candidate at University of Kaiserslautern-Landau, Germany

Francisco Mena is a PhD candidate in Computer Science at the University of Kaiserslautern-Landau (RPTU), Germany, with a strong academic and research background in deep learning, multi-view learning, and unsupervised learning. His work focuses on developing scalable and generalizable machine learning models, particularly in complex real-world domains like Earth observation and astroinformatics, where missing data and multi-source fusion are major challenges. Francisco’s research emphasizes minimizing human intervention and domain dependency, aiming for methods that are more robust, adaptable, and explainable.

Publication Profile 

Orcid

Educational Background 🎓

  • PhD in Computer Science
    University of Kaiserslautern-Landau (RPTU), Germany
    Jan. 2022 – Present
    Thesis: Data Fusion in Multi-view Learning for Earth Observation Applications with Missing Views

  • Magíster en Ciencias de la Ingeniería Informática (Equivalent to M.Sc. in Computer Engineering)
    Federico Santa María Technical University (UTFSM), Valparaíso, Chile
    Mar. 2018 – Sep. 2020
    Thesis: Mixture Models for Learning in Crowdsourcing Scenarios
    GPA: 94%

  • Ingeniería Civil en Informática (Equivalent to Computer Engineering)
    UTFSM, Santiago, Chile
    Mar. 2013 – Sep. 2020
    GPA: 80% | Rank: Top 10% – 4th of 66 students

  • Licenciado en Ciencias de la Ingeniería Informática
    UTFSM, Santiago, Chile
    Mar. 2013 – Nov. 2017

  • High School
    New Little College, Santiago, Chile
    Mar. 2008 – Dec. 2012

Professional Experience 💼

  • Student Research Assistant – German Research Centre for Artificial Intelligence (DFKI), Germany
    Mar. 2022 – Present
    Working on Earth observation data for crop yield prediction using Python, QGIS, and Slurm.

  • Lecturer – University of Kaiserslautern-Landau (RPTU), Germany
    Oct. 2024 – Apr. 2025
    Teaching: Machine Learning for Earth Observation within a broader Data Science course.

  • Visiting PhD Researcher – Inria Montpellier, France
    Nov. 2024 – Jan. 2025
    Research in multi-modal co-learning, mutual distillation, and multi-task learning.

  • Academic Roles – Federico Santa María Technical University (UTFSM), Chile
    2014 – 2021
    Lecturer & Assistant roles in:

    • Computational Statistics

    • Artificial Neural Networks

    • Machine Learning

    • Operations Research

    • Mathematics Lab

  • Research Assistant – Chilean Virtual Observatory (ChiVO)
    Jul. 2017 – May 2018
    Astroinformatics projects involving ALMA/ESO datasets and Python-based data reduction.

  • Developer Intern – Farmacia Las Rosas S.A., Chile
    Jan. 2017 – Mar. 2017
    Desktop software automation using Python and QT.

Research Interests 🔬

  • Machine Learning Foundations:
    Deep Learning, Variational Autoencoders, Neural Networks, Representation Learning, Deep Clustering

  • Methodologies:
    Multi-view Learning, Data Fusion, Latent Variable Modeling, Dimensionality Reduction, Unsupervised Learning

  • Applications:
    Earth Observation, Remote Sensing, Vegetation Monitoring, Crowdsourcing, Neural Information Retrieval, Astroinformatics

Awards and Honors🏆✨

  • PhD Scholarship – RPTU, Germany (2022–present)

  • Scientific Initiation Award (PIIC) – UTFSM, Chile (2019–2020)

  • Master Program Scholarship – UTFSM, Chile (2018–2020)

  • Honor Roll – UTFSM, Chile (2013)

Conclusion🌟

Francisco Mena is a dedicated machine learning researcher whose work blends theoretical rigor with impactful real-world applications. His interdisciplinary approach spans remote sensing, astroinformatics, and crowdsourcing, focusing on creating models that are resilient to missing data, efficient at scale, and minimally reliant on labeled supervision. With a growing publication record, international experience, and teaching background, he is well-positioned to make significant contributions to both academia and applied AI research.

Publications 📚

  1. 📄 Missing data as augmentation in the Earth Observation domain: A multi-view learning approach
    Neurocomputing, 2025-07
    DOI: 10.1016/j.neucom.2025.130175
    👥 Francisco Mena, Diego Arenas, Andreas Dengel

  2. 🌾 Adaptive fusion of multi-modal remote sensing data for optimal sub-field crop yield prediction
    Remote Sensing of Environment, 2025-03
    DOI: 10.1016/j.rse.2024.114547
    👥 Francisco Mena et al.

  3. 🛰️ Common Practices and Taxonomy in Deep Multiview Fusion for Remote Sensing Applications
    IEEE JSTARS, 2024
    DOI: 10.1109/JSTARS.2024.3361556
    👥 Francisco Mena, Diego Arenas, Marlon Nuske, Andreas Dengel

  4. 📉 Impact Assessment of Missing Data in Model Predictions for Earth Observation Applications
    IGARSS Proceedings, 2024
    DOI: 10.1109/IGARSS53475.2024.10640375
    👥 Francisco Mena et al.

  5. 🛰️ Assessment of Sentinel-2 Spatial and Temporal Coverage Based on the Scene Classification Layer
    IGARSS 2024, 2024-07-07
    DOI: 10.1109/igarss53475.2024.10642213
    👥 Cristhian Sanchez, Francisco Mena et al.

  6. 🌽 Crop Yield Prediction: An Operational Approach to Crop Yield Modeling on Field and Subfield Level with ML Models
    IGARSS 2023
    DOI: 10.1109/IGARSS52108.2023.10283302
    👥 Francisco Mena et al.

  7. 🧩 Feature Attribution Methods for Multivariate Time-Series Explainability in Remote Sensing
    IGARSS 2023
    DOI: 10.1109/IGARSS52108.2023.10282120
    👥 Francisco Mena et al.

  8. 🧹 Influence of Data Cleaning Techniques on Sub-Field Yield Predictions
    IGARSS 2023
    DOI: 10.1109/IGARSS52108.2023.10282955
    👥 Francisco Mena et al.

  9. 🗂️ A Comparative Assessment of Multi-View Fusion Learning For Crop Classification
    IGARSS 2023, 2023-07-16
    DOI: 10.1109/igarss52108.2023.10282138
    👥 Francisco Mena, Diego Arenas, Marlon Nuske, Andreas Dengel

  10. 📊 Predicting Crop Yield with Machine Learning: Input Modalities and Models on Field and Sub-Field Level
    IGARSS 2023, 2023-07-16
    DOI: 10.1109/igarss52108.2023.10282318
    👥 Francisco Mena et al.

Fouokeng Georges Collince | Information Theory | Best Researcher Award

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Assoc. Prof. Dr. Fouokeng Georges Collince | Information Theory | Best Researcher Award

G.C. Fouokeng at University of Dschang, Cameroon

Dr. Georges Collince Fouokeng is a highly experienced Associate Professor in Quantum Physics at the University of Dschang, Cameroon. His research spans condensed matter physics, quantum information science, and nanomaterials, with a particular focus on understanding quantum coherence, decoherence, and phase transitions. He is also an active educator, having held significant administrative roles aimed at fostering academic innovation. With a robust publication record and a passion for advancing scientific research, Dr. Fouokeng is dedicated to bridging the gap between theoretical quantum science and practical technological applications.

Publication Profile : 

Google Scholar

 

🎓 Educational Background :

  • Doctorate (Ph.D.) in Condensed Matter Physics, University of Dschang, Cameroon (2015)
  • Master’s in Condensed Matter Physics, University of Dschang, Cameroon (2009)

💼 Professional Experience :

Dr. Georges Collince Fouokeng is an accomplished educator and researcher with over a decade of academic experience. He began his teaching career as a part-time lecturer at the National Polytechnic of Bambui (2010-2012) and later joined the Institut Universitaire de la Côte in Douala, where he held roles as Assistant Lecturer (2015-2016) and Lecturer (2016-2020). In 2022, he was promoted to Associate Professor at the University of Dschang, Faculty of Science.

Dr. Fouokeng has also contributed significantly to academic administration, having served as:

  • Head of the Industrial Masters Department (2018-2019)
  • Coordinator of the Research Innovation Entrepreneurship Pole (2017-2019)
  • Head of the Academic Activities Monitoring Unit (2015-2019)
  • Coordinator for Teaching and Research Monitoring (2017-2018)

Additionally, he is the Leader of the ERASMUS+ 2023-2025 Project, promoting academic collaboration between University of Dschang and University of Maine le Mans in France.

📚 Research Interests : 

Dr. Fouokeng’s research focuses on Quantum Science, with particular expertise in:

  • Condensed Matter & Nanomaterials
  • Quantum Information Theory & Quantum Computing
  • Decoherence & Quantum Phase Transitions

His work has led to significant contributions in the study of quantum coherence, spin dynamics, and phase transitions in systems affected by environmental noise, as well as advances in metamagnetoelectric effects in multiferroic materials.

📝 Publication Top Notes :

  1. Fouokeng, G. C., Tchoffo, M., Moussiliou, S., Ngana Kuetche, J. C., Fai, L. C., & Siaka, M. (2014). Effect of noise on the decoherence of a central electron spin coupled to an antiferromagnetic spin bath. Advances in Condensed Matter Physics, 2014, Article ID 526205. https://doi.org/10.1155/2014/526205
  2. Fouokeng, G. C., Tchoffo, M., et al. (2014). The quenching field effect on the motion of an electron in an electromagnetic field potential. Modern Physics Letters B, 28(14), 1450058. https://doi.org/10.1142/S0217984914500581
  3. Fouokeng, G. C., Tchoffo, M., Ateuafack, M. E., & Fai, L. C. (2014). Dynamics of a central electron spin coupled to an anti-ferromagnetic spin bath driven by a variable magnetic field in the Landau-Zener scenario. European Physical Journal Plus, 129, 151. https://doi.org/10.1140/epjp/i2014-14151-9
  4. Fai, L. C., Diffo, J. T., Ateuafack, M. E., Tchoffo, M., & Fouokeng, G. C. (2014). Dynamics of a Landau-Zener nondissipative system with fluctuating energy levels. Physica B, 454, 157–164. https://doi.org/10.1016/j.physb.2014.02.012
  5. Tchoffo, M., Fouokeng, G. C., Fai, L. C., & Ateuafack, M. E. (2013). Thermodynamic properties and decoherence of a central electron spin of an atom coupled to an anti-ferromagnetic spin bath. Journal of Quantum Information Science, 3(1), 10–15. https://doi.org/10.4236/jqis.2013.31002
  6. Tchoffo, M., Ngana Kuetche, J. C., Moussiliou, S., Fouokeng, G. C., Fai, L. C., Beilinson, A. A., & Kenné, J. P. (2012). Decoherence of a Brownian particle in a double-well magnetic potential field. Far East Journal of Applied Mathematics, 68(1), 21–28.
  7. Tchoffo, M., Fouokeng, G. C., Moussiliou, S., Afuoti, N. E., Nsangou, I., Fai, L. C., Tchouadeu, A. G., & Kenné, J. P. (2012). Effect of the variable B-field on the dynamics of a central electron spin coupled to an anti-ferromagnetic qubit bath. World Journal of Condensed Matter Physics, 2, 246–256. https://doi.org/10.4236/wjcmp.2012.23033
  8. Fai, L. C., Ngana Kuetche, J. C., Fouokeng, G. C., Tchoffo, M., & Afuoti, N. E. (2014). Decoherence induced by a quenching driven field on the motion of a single electron. Physical Review & Research International, 4(2), 267–282.
  9. Tchoffo, M., Fouokeng, G. C., Fai, L. C., Ngoufo, L. A., & Diffo, J. T. (2014). Brownian particle’s decoherence in the double-well magnetic potential field. The African Review of Physics, 9(2), 207–215.
  10. Tchoffo, M., Ngana Kuetche, J. C., Fouokeng, G. C., Afuoti, N. E., & Fai, L. C. (2014). Kinematical Brownian motion of the harmonic oscillator in non-commutative space. American Journal of Modern Physics, 3(3), 138–142. https://doi.org/10.11648/j.ajmp.20140303.13
  11. Fai, L. C., Afuoti, N. E., Fouokeng, G. C., Ngana Kuetche, J. C., Tchoffo, M., & Kenné, J. P. (2014). Tailoring quantum correlations of a coupled central two qubits soaked in a finite temperature antiferromagnetic environment with frequency gap. Journal of Quantum Information Science, 4, 201–213. https://doi.org/10.4236/jqis.2014.44018
  12. Tchoffo, M., Fouokeng, G. C., Tendong, E., Fai, L. C. (2016). Dzyaloshinskii–Moriya interaction effects on the entanglement dynamics of a two-qubit XXZ spin system in non-Markovian environment. Journal of Magnetism and Magnetic Materials, 407, 358–364. https://doi.org/10.1016/j.jmmm.2016.02.073
  13. Fai, L. C., Ngana Kuetche, J. C., Fouokeng, G. C., Tchoffo, M., & Ngwa, E. A. (2016). Thermal activation process in hydrogen bonds. World Journal of Molecular Research, 1(1), 14–26.
  14. Tchoffo, M., Kenfack, L. T., Fouokeng, G. C. (2016). Quantum correlations dynamics and decoherence of a three-qubit system subject to classical environmental noise. European Physical Journal Plus, 131, 380. https://doi.org/10.1140/epjp/i2016-16380-1
  15. Fai, L. C., Ngana Kuetche, J. C., Fouokeng, G. C., Tchoffo, M., & Ngwa, E. A. (2016). Thermal activation process in hydrogen bonds. World Journal of Molecular Research, 1(1), 14–26.
  16. Tchoffo, M., Tsamouo, T. A., Fouokeng, G. C. (2017). Time evolution of quantum correlations in superconducting flux-qubits under classical noises. International Journal of Quantum Information, 15(2), 1750015. https://doi.org/10.1142/S0219749917500159
  17. Kenfack, L. T., Tchoffo, M., Fouokeng, G. C., & Fai, L. C. (2017). Effects of static noise on the dynamics of quantum correlations for a system of three qubits. International Journal of Modern Physics, 31(8), 1750046. https://doi.org/10.1142/S0217979217500465
  18. Diffo, J. T., Ateuafack, M. E., Fouokeng, G. C., Fai, L. C., Tchoffo, M. (2017). Interplay between Landau-Zener transition dynamic and quantum phase transition in dissipative spin chain with Dzyaloshinsky-Moriya interaction. Superlattices and Microstructures, 111, 310–318. https://doi.org/10.1016/j.spmi.2017.05.038
  19. Kenfack, L. T., Tchoffo, M., Fouokeng, G. C., Fai, L. C. (2017). Dynamics of tripartite quantum correlations in mixed classical environments: The joint effects of random telegraph and static noises. International Journal of Quantum Information, 15(5), 1750038. https://doi.org/10.1142/S0219749917500382
  20. Kenfack, L. T., Tchoffo, M., Fai, L. C., Fouokeng, G. C. (2017). Decoherence and tripartite entanglement dynamics in the presence of Gaussian and non-Gaussian classical noise. Physica B, 511, 123–133. https://doi.org/10.1016/j.physb.2017.03.008