Hussain Ahmad Madni | Hematology | Best Researcher Award

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Mr. Hussain Ahmad Madni | Hematology | Best Researcher Award

University of Udine | Italy

Author Profile

Scopus

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 HUSSAIN AHMAD MADNI: A DEDICATED PH.D. SCHOLAR IN COMPUTER SCIENCE

📚 EARLY ACADEMIC PURSUITS

Hussain Ahmad Madni began his academic journey with a strong foundation in computer science and engineering. His early education emphasized critical subjects like mathematics, physics, and chemistry, which paved the way for his future in technology and research.

  • Matriculation: Board of Intermediate and Secondary Education, D.G. Khan, Pakistan (2005–2007).
  • Intermediate (F.Sc. Pre-Engineering): Board of Intermediate and Secondary Education, D.G. Khan, Pakistan (2008–2010).
  • Bachelor’s Degree: B.Sc. in Computer System Engineering, The Islamia University of Bahawalpur, Pakistan (2010–2014).

Hussain advanced his expertise through postgraduate studies at COMSATS University Islamabad, Pakistan, earning an MS in Computer Science (2017–2018) with a thesis titled Introduction Detection System Using Deep Learning. He is now pursuing a Ph.D. in Computer Science and Artificial Intelligence at the University of Udine, Italy (2022–2024), focusing on Trust in Cloud Computing.

🧪 PROFESSIONAL ENDEAVORS

Hussain‘s career trajectory demonstrates his versatility and commitment to the field. His experience spans academia, research, and software engineering:

  • Research Assistant: COMSATS University Islamabad, Pakistan (2019–2021).
  • Senior Software Engineer: SK Technologies, Islamabad, Pakistan (2018–2019).
  • Software Engineer: Integrated Dynamic Solutions (IDS), Rawalpindi, Pakistan (2015–2017).

🔬 CONTRIBUTIONS AND RESEARCH FOCUS ON HEMATOLOGY

Hussain’s research centers on cutting-edge technologies such as:

  • Distributed Machine Learning
  • Federated Learning
  • Swarm Learning
  • Cybersecurity
  • Cloud Computing Trust

His innovative studies aim to enhance the security and privacy of data and models, tackling challenges in a rapidly evolving digital world.

🌍 IMPACT AND INFLUENCE

Hussain’s work is contributing significantly to technological advancements in distributed and federated learning. His studies on Blockchain-based Swarm Learning and Fully Homomorphic Encryption have addressed critical issues like gradient leakage and client security, showcasing his influence in the field.

📈 ACADEMIC CITATIONS AND PUBLICATIONS

Hussain’s dedication is evident in his extensive list of publications in prestigious journals and conferences:

  1. Exploiting Data Diversity in Multi-Domain Federated Learning (2024).
  2. Robust Federated Learning for Heterogeneous Model and Data (2024).
  3. Blockchain-Based Swarm Learning for Gradient Leakage Mitigation (2023).
  4. Swarm-FHE: Fully Homomorphic Encryption-Based Swarm Learning for Malicious Clients (2023).

🏅 HONORS & AWARDS

  • 2024: Oxford Machine Learning Summer School, UK.
  • 2023: International Computer Vision Summer School, Italy.
  • 2021: MIUR, Italy Scholarship for Ph.D. in Computer Science.
  • 2017: PEEF Scholarship, Pakistan for MS in Computer Science.
  • 2011: Merit Scholarship, ICT R&D Fund, Pakistan for B.Sc. in Computer System Engineering.

🌐 LEGACY AND FUTURE CONTRIBUTIONS

As a visionary researcher, Hussain’s contributions lay the groundwork for secure, scalable solutions in distributed systems. His innovative ideas are poised to impact industry practices and academic discourse for years to come.

🌠 FINAL NOTE

Hussain Ahmad Madni exemplifies dedication to advancing technology and solving complex problems in machine learning, cybersecurity, and cloud computing. His achievements reflect his commitment to shaping a secure, innovative future.

📑 NOTABLE PUBLICATIONS 

Exploiting Data Diversity in Multi-Domain Federated Learning
  • Authors: Ahmad Madni, H., Muhammad Umer, R.
  • Journal: International Journal of Neural Systems
  • Year: 2023
Swarm-FHE: Fully Homomorphic Encryption-based Swarm Learning for Malicious Clients
  • Authors: Madni, H.A., Umer, R.M., Foresti, G.L.
  • Journal: International Journal of Neural Systems
  • Year: 2023
Blockchain-Based Swarm Learning for the Mitigation of Gradient Leakage in Federated Learning
  • Authors: Madni, H.A., Umer, R.M., Foresti, G.L.
  • Journal: IEEE Access
  • Year: 2023
DAVS-NET: Dense Aggregation Vessel Segmentation Network for Retinal Vasculature Detection in Fundus Images
  • Authors: Raza, M., Naveed, K., Akram, A., Khan, M.A.U., Mui-Zzud-din
  • Journal: PLoS ONE
  • Year: 2021
Towards Automated Eye Diagnosis: An Improved Retinal Vessel Segmentation Framework Using Ensemble Block Matching 3D Filter
  • Authors: Naveed, K., Abdullah, F., Madni, H.A., Khan, T.M., Naqvi, S.S.
  • Journal: Diagnostics
  • Year: 2021
Machine Learning: Science and Technology
  • Authors: Luca Foresti, G.
  • Journal: Machine Learning: Science and Technology
  • Year: 2024
Robust Federated Learning for Heterogeneous Model and Data
  • Authors: Madni, H.A., Umer, R.M., Foresti, G.L.
  • Journal: International Journal of Neural Systems
  • Year: 2024

 

Abhimanyu Kumar Gond | Environment | Best Researcher Award

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Mr. Abhimanyu Kumar Gond | Environment | Best Researcher Award

IIT BHU VARANASI , INDIA

Author Profile

🌟 BIOGRAPHY: MR. ABHIMANYU KUMAR GOND 

📚 EARLY ACADEMIC PURSUITS

Born on January 18, 1996, in Siwan, Bihar, Mr. Abhimanyu Kumar Gond exhibited academic excellence from an early age. He achieved significant milestones, including a Bachelor’s in Civil Engineering (2017) with an impressive 84.2%. His passion for geospatial technologies led him to pursue an M.Tech in GIS and Remote Sensing from MNNIT Allahabad, which he completed in 2019. Currently, he is a dedicated Ph.D. Scholar at the Indian Institute of Technology (IIT) BHU, Varanasi, specializing in air quality prediction and its impact on mining environments.

🧪 PROFESSIONAL ENDEAVORS

Mr. Gond‘s professional journey reflects his commitment to education and research. With hands-on experience as a Teaching Assistant during his Ph.D., he has guided undergraduate and postgraduate students in remote sensing, GIS, and image processing. He also worked as a Junior Project Fellow at the Institute of Forest Productivity, Ranchi, contributing to environmental research.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS ON ENVIRONMENT

Mr. Gond‘s research aims to mitigate environmental and public health challenges posed by mining activities. His Ph.D. work focuses on developing a machine learning model integrating satellite and ground data for monitoring air quality. This research aids stakeholders in proactive decision-making for environmental management. Additionally, his M.Tech thesis on digital watermarking in satellite images addressed data security issues, showcasing his multidisciplinary expertise.

🌍 IMPACT AND INFLUENCE

Through conference presentations, journal publications, and workshops, Mr. Gond has consistently shared his insights with the academic and scientific community. His publications in esteemed journals like Remote Sensing Applications: Society and Environment and Atmospheric Pollution Research highlight his innovative approach to air quality assessment using machine learning and geospatial techniques.

📈 ACADEMIC CITATIONS AND PUBLICATIONS

Mr. Gond has co-authored several impactful publications that underscore his expertise in environmental monitoring and geospatial analytics:

  1. “Spatio-temporal trend analysis of air pollutants during COVID-19 over Korba district” (Remote Sensing Applications: Society and Environment).
  2. “Developing a Machine Learning Model Using Satellite Data to Predict the AQI Over Korba Coalfield” (Atmospheric Pollution Research).
  3. “Prediction of Spectral Indices Using LSTM Model” (Remote Sensing for Sustainable Future).

His scholarly work has been cited in prominent research platforms, including Google Scholar and ResearchGate.

🏅 HONORS & AWARDS

  • Certificate of Excellence in Article Writing.
  • Recognition for outstanding teaching assistance during his Ph.D.
  • Multiple certifications in short-term courses such as “Recent Advancement in GIS Engineering” and “Numerical and Optimization Techniques.”
  • Awarded “Student of the Year” during his undergraduate studies for leadership and academic achievements.

🌐 LEGACY AND FUTURE CONTRIBUTIONS

Mr. Gond aspires to further contribute to the fields of GIS, remote sensing, and environmental engineering. His future work promises to influence policy-making, enhance public health strategies, and support sustainable development initiatives.

🌠 FINAL NOTE

Mr. Gond’s unwavering dedication to research, teaching, and environmental sustainability makes him a promising scholar in the field of geospatial analytics and environmental engineering. He has consistently demonstrated the ability to address real-world challenges through academic rigor and technical expertise.

📑 NOTABLE PUBLICATIONS 

“Developing a machine learning model using satellite data to predict the Air Quality Index (AQI) over Korba Coalfield, Chhattisgarh (India)”
  • Authors: Abhimanyu Kumar Gond, Aarif Jamal, Tarun Verma
  • Journal: Atmospheric Pollution Research
  • Year: 2025
“Spatio-temporal trend analysis of air pollutants during COVID-19 over Korba district, Chhattisgarh (India) using Google Earth Engine”
  • Authors: Abhimanyu Kumar Gond, Aarif Jamal, Tarun Verma
  • Journal: Remote Sensing Applications: Society and Environment
  • Year: 2024