Mrs. Ayesha Tasawar | Hydrometallurgical | Excellence in Research Award

Scientific Assistant at Institute of Process Metallurgy and Metal Recycling (IME), RWTH Aachen University | Germany

Mrs. Ayesha Tasawar is an emerging researcher in process metallurgy and sustainable materials engineering, with a strong focus on lithium-ion battery recycling and resource recovery. Her research addresses key challenges in circular economy technologies, particularly the hydrometallurgical processing of lithium iron phosphate (LFP) blackmass. She is the lead author of peer-reviewed journal articles in Resources, Conservation and Recycling and Metals, demonstrating original contributions to efficient lithium recovery through oxidative roasting and organic-acid-enabled leaching. Her work combines scientific rigor with industrial relevance, offering environmentally responsible solutions for advanced battery recycling. Scopus profile, 2 publications, emerging citation record, and emerging h-index.

Mr. Bilal Ahmad | Computational Metallurgy | Research Excellence Award

University of Johannesburg | South Africa

Mr. Bilal Ahmad demonstrates emerging excellence in data science and artificial intelligence, with scholarly focus on machine learning and deep learning applications for complex, real-world problems. Research contributions emphasize predictive analytics and intelligent modeling, including peer-reviewed work on epidemic outbreak analysis using advanced computational techniques. The research reflects methodological soundness, interdisciplinary relevance, and alignment with current global challenges in data-driven systems. According to the Scopus profile, the researcher has 1 indexed publication, 2 total citations, and an h-index of 1, indicating early academic visibility and growing research impact. These contributions highlight strong potential for continued advancement and research excellence.

Citation Metrics ( Google Scholar )

Citations
2

Documents
1

h-index
1

View Google Scholar Profile

View ORCID Profile

Featured Publications

Machine Learning for Drug–Target Interaction Prediction: A Comprehensive Review of Models, Challenges, and Computational Strategies
– Computational and Structural Biotechnology Journal, 2026

Exploration of Epidemic Outbreaks Using Machine and Deep Learning Techniques
– Advances in Cybersecurity, Cybercrimes, and Smart Emerging Technologies, 2023