Ali Yousefi | medicinal chemistry | Best Researcher Award

Mr. Ali Yousefi | Medicinal Chemistry | Best Researcher Award

Ali Yousefi, an Iranian medicinal chemist born in 1998, is a Ph.D. scholar at Tabriz University of Medical Sciences and an emerging researcher at the University of Kashan’s Essential Oils Research Institute. With a strong foundation in pure and medicinal chemistry, his research explores the synthesis and biological evaluation of bioactive compounds, integrating AI and natural product chemistry. He has contributed to cutting-edge publications, presented at national conferences, and taken part in interdisciplinary collaborations. Ali is deeply invested in drug discovery, natural product isolation, and cancer-related research, aiming to bridge traditional remedies with modern medicinal approaches.

Profile

Scopus

🎓 Education 

Ali Yousefi earned a B.Sc. in Pure Chemistry (2017–2023) and an M.Sc. in Medicinal Chemistry (2021–2023) from the University of Kashan, Iran, through its Distinguished Talent Program. Currently, he is pursuing a Ph.D. in Medicinal Chemistry (2023–2027) at the Faculty of Pharmacy, Tabriz University of Medical Sciences. His educational focus spans organic synthesis, drug design, and biological screening of novel compounds. His academic trajectory reflects both rigorous training and an innovative outlook, particularly in linking medicinal chemistry with computational modeling and natural compound exploration for therapeutic applications.

💼 Experience 

Ali has served as a teaching assistant and lecturer in undergraduate and graduate courses, including Organic Chemistry, Medicinal Chemistry, and Analytical Chemistry. He is actively involved in industrial R&D at the Shahid Ardeshir Hosseinpour Incubation Center, contributing to the synthesis and localization of Sugammadex production. A key member of the Essential Oils Research Institute since 2007, he has also contributed to AI-healthcare integrations such as Pharm Chatbot AI. At Tabriz University, he supports research in marine-derived anticancer agents, merging pharmaceutical innovation with machine learning in biological predictions.

🏅 Awards and Honors 

Ali was selected for the Distinguished Talent Program at the University of Kashan for his M.Sc. studies in Medicinal Chemistry. He has earned national recognition through his publications in high-impact journals and presentations at prestigious chemistry and medical symposia. His work in AI-integrated drug development and radiation side-effect prediction has positioned him as a promising young scientist. His role in cross-institutional industrial collaborations also demonstrates his leadership in translational research and his early career distinction in medicinal chemistry and bioinformatics.

🔬 Research Focus 

Ali’s research centers on drug discovery through the design, synthesis, and evaluation of biologically active compounds such as resveratrol and bromophenol derivatives. He is deeply interested in antioxidant, anticancer, and antimicrobial agents from natural and marine sources. His work spans computational drug design, structure-activity relationship studies, and AI applications in predicting biological responses. He also explores electrochemical biosensing and nanomaterial interfaces for biomedical diagnostics. Overall, Ali’s interdisciplinary approach bridges chemistry, pharmacology, and data science for impactful advancements in precision medicine.

📝 Conclusion

Ali Yousefi is an excellent candidate for the Best Researcher Award, demonstrating a compelling blend of academic brilliance, innovative thinking, practical application, and multidisciplinary research expertise. His active contributions in medicinal chemistry, machine learning for healthcare, natural products, and industrial pharma solutions highlight both depth and breadth of scientific engagement. With enhanced international collaboration and greater focus on innovation outputs (patents, grants), he is poised to become a rising star in pharmaceutical and biomedical research. Given his early career accomplishments and forward-thinking approach, he is strongly recommended for recognition through this prestigious award.

Publication

  • Title: Design, Synthesis and Antioxidant, Anticancer and Antimicrobial Activity Evaluation of Novel Resveratrol Derivatives

  • Year: 2025

  • Authors: Ali A. Yousefi, Abdolrasoul H. Ebrahimabadi, Hourieh Sadat Oboudatian

Syed Luqman Ali | Drug Design | Best Researcher Award

Mr. Syed Luqman Ali | Drug Design | Best Researcher Award

Researcher, Abdul Wali Khan University Mardan KPK Pakistan, Pakistan

Mr. Syed Luqman Ali is an enthusiastic researcher specializing in bioinformatics, computational biology, vaccine design, cancer, and drug development. Currently pursuing an MPhil in Biochemistry at Abdul Wali Khan University Mardan (2025), he has published extensively on vaccine and drug design using advanced computational techniques like RNA-seq, molecular docking, and simulation. Mr. Ali is a skilled reviewer for several high-impact journals and a lecturer at Metanoia College of Nursing. With expertise in bioinformatics tools and programming languages, he is committed to advancing scientific knowledge in vaccine and drug research.

Publication Profile

Google scholar

Education

Mr. Syed Luqman Ali is currently pursuing his MPhil in Biochemistry at Abdul Wali Khan University Mardan, Pakistan, with an expected graduation in 2025. He completed his Bachelor’s degree in Biochemistry from the same institution in 2022, laying the foundation for his research career. Additionally, he holds a Diploma in Digital Information Technology from the Board of Technical Education Peshawar, Pakistan, earned in 2021. This diverse educational background has equipped him with a strong interdisciplinary skill set, combining biochemistry, digital technology, and computational biology for cutting-edge research.

Research Experience

Mr. Syed Luqman Ali has been an Experimental and Computational Researcher at Abdul Wali Khan University Mardan since 2019. His research focuses on vaccine and drug design, utilizing advanced computational techniques like RNA-seq analysis, molecular docking, and simulation. With extensive experience in leading bioinformatics databases such as KEGG, MetaCyc, and HADDOCK, Mr. Ali is proficient in tools like SnapGene, Cytoscape, and DAVID. His work contributes to the development of innovative vaccines and drug therapies, advancing scientific knowledge in bioinformatics and computational biology.

Technical Certifications

Mr. Syed Luqman Ali has acquired several technical certifications that complement his research expertise. He completed a Data Analysis with R program through Mindluster, enhancing his data analysis skills. Additionally, he has obtained certifications in Data Analysis with Python and Linux from Udemy, further strengthening his computational abilities. Mr. Ali also completed a Content Writing course through the DigiSkills Training Program from Virtual University, Lahore, improving his communication and writing skills for scientific documentation. These certifications underscore his commitment to continuous learning and professional development in bioinformatics and computational biology.

Awards and Achievements

Mr. Syed Luqman Ali has made significant contributions to the scientific community, with multiple publications in high-impact journals, showcasing his research prowess in bioinformatics and computational biology. His work has been recognized by peers and researchers worldwide. Additionally, Mr. Ali serves as a reviewer for several reputed scientific journals, contributing his expertise to the advancement of research. These achievements reflect his dedication to scientific excellence and his active role in shaping future advancements in his field. 📚🖋️🔬

Research Focus

Mr. Syed Luqman Ali’s research spans multiple bioinformatics and computational biology domains, particularly in vaccine and drug design, cancer immunology, and genomics. His work includes multi-epitope vaccine development using immunoinformatics and reverse vaccinology approaches, along with genomic annotation for vaccine target identification. He has contributed significantly to disease diagnostics and drug discovery, especially in areas like tuberculosis, SARS-CoV-2, Leishmania, and autoimmune disorders. His expertise also extends to advanced data analysis, molecular docking, and RNA-seq analysis, employing tools like KEGG, MetaCyc, and HADDOCK. 🧬💻💉

Publication Top Notes

  • Mutational screening of GDAP1 in dysphonia associated with Charcot-Marie-Tooth disease: clinical insights and phenotypic effects
    Cited by: 20
    Year: 2023
  • Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica – a hierarchical subtractive proteomics and …
    Cited by: 15
    Year: 2023
  • Genomic annotation for vaccine target identification and immunoinformatics-guided multi-epitope-based vaccine design against Songling virus through screening its whole genome …
    Cited by: 12
    Year: 2023
  • Currently trending and futuristic biological modalities in the management of different types of diabetes: A comprehensive review
    Cited by: 9
    Year: 2023
  • Analysis of the capability of IgG antibodies and receptors with their relationships to food tolerance and autoimmune disorders
    Cited by: 6
    Year: 2023
  • Illuminating the Frontier of Drug Discovery: Unleashing the Power of Bioinformatics for Unprecedented Breakthroughs
    Cited by: 4
    Year: 2023
  • Leveraging computer-aided design and artificial intelligence to develop a next-generation multi-epitope tuberculosis vaccine candidate
    Cited by: 1
    Year: 2024
  • Genetic identification and determination of parasites (Babesia, Leptospira and Toxoplasma Gondi) in wild rats
    Cited by: 1
    Year: 2024
  • Placental histology for targeted risk assessment of recurrent spontaneous preterm birth
    Cited by: 1
    Year: 2024
  • Harnessing bioinformatics for the development of a promising multi-epitope vaccine against tuberculosis: The ZL9810L vaccine
    Cited by: 1
    Year: 2024
  • Promising vaccine models against astrovirus MLB2 using integrated vaccinomics and immunoinformatics approaches
    Cited by: 1
    Year: 2024
  • Multi-epitope-based vaccine models prioritization against Astrovirus MLB1 using immunoinformatics and reverse vaccinology approaches
    Cited by: 1
    Year: 2025
  • Exploring advanced genomic and immunoinformatics techniques for identifying drug and vaccine targets against SARS-CoV-2
    Cited by: 1
    Year: 2024
  • A Comprehensive Methodological Review of Major Developments in Bioinformatics Pipelines for Transcriptomic Data Analysis
    Cited by: –
    Year: 2024
Conclusion

Mr. Ali’s solid academic background, innovative research contributions, advanced technical skills, and role as a mentor, he is undoubtedly a strong candidate for the Research for Best Researcher Award. His work in bioinformatics, drug design, vaccine development, and cancer research showcases his dedication to advancing scientific knowledge and making a global impact.