Dr. Santosh Jagtap | AI and ML | Microsoft AI Award

Dr. Santosh Jagtap | AI and ML | Microsoft AI Award

Assistant Professor, Prof. Ramkrishna More Arts, Commerce & Science College, India

Dr. Santosh Jagtap, Assistant Professor at Prof. Ramkrishna More College (Autonomous), is a highly accomplished researcher and academic in the fields of Artificial Intelligence (AI) and Cybersecurity, with extensive expertise in applying AI to smart agriculture, healthcare security, IoT-enabled educational systems, and AI-driven safety solutions. Dr. Jagtap holds advanced academic qualifications and has developed a distinguished research profile that emphasizes practical applications of emerging technologies to address societal challenges. His work integrates machine learning, blockchain, IoT, and real-time data processing, producing innovative solutions in areas such as intelligent irrigation systems, plant disease detection, AI-based emotion recognition for safety alerts, and secure healthcare frameworks. Over his career, Dr. Jagtap has contributed significantly to international research projects and collaborative studies, producing high-impact publications in reputed journals and conference proceedings, such as Materials Today: Proceedings, international conferences on electronics, computing, and applied AI. He has also been recognized for innovation through patent awards, notably for AI-based plant disease identification systems, reflecting his focus on technology transfer and real-world impact. Dr. Jagtap has played an active role in mentoring students, guiding research projects, and participating in professional networks that foster academic and technological growth. He has demonstrated a consistent record of research excellence, with a total of 78 citations across 4 Scopus-indexed publications and an h-index of 3, reflecting the growing impact of his work.

Profile: GOOGLE SCHOLAR | SCOPUS

Featured Publications

  • Jagtap, S. T., Phasinam, K., Kassanu. (2022). Towards application of various machine learning techniques in agriculture. Materials Today: Proceedings, 51, 793–797. 70 citations.

  • Jagtap, S. T., Thakar, (2021). A framework for secure healthcare system using blockchain and smart contracts. Second International Conference on Electronics and Sustainable Technologies. 22 citations.

  • Jagtap, S. T., Jagdale, K. C., & Thakar, C. M. (2023). Identification of plant disease device using artificial intelligence. IN Patent 391523-001. –

  • Pratiksha Bhise, D. S. J., & Jagtap, S. T. (2024). AI-driven emergency response system for women’s safety using real-time location and heart rate monitoring. IJRPR. –

  • Keskar,  A., Jagtap, S. T., et al. (2021). Big data preprocessing frameworks: Tools and techniques. Design Engineering, 1738–1746.

Ali Ghulam | AI in Healthcare | Best Researcher Award

Dr. Ali Ghulam | AI in Healthcare | Best Researcher Award

Assistant Professor at Information Technology Centre, Sindh Agriculture University, Pakistan

Dr. Ghulam Ali is an accomplished academic and researcher specializing in artificial intelligence (AI) and bioinformatics. He earned his Ph.D. in Computer Software and Theory from Shaanxi Normal University, Xi’an, China, in 2020. Currently, he serves as an Assistant Professor at the Information Technology Centre, Sindh Agriculture University, Tandojam. His research focuses on human disease pathway network modeling, biological pathway database discovery, and AI-driven predictions related to proteins, drugs, and diseases. With over 20 published SCI articles in high-impact journals and extensive contributions to machine learning applications in bioinformatics, Dr. Ali is a recognized expert in his field.

Profile

Orcid

Education

Dr. Ali pursued his Ph.D. from Shaanxi Normal University, Xi’an, China, specializing in bioinformatics and AI. His thesis, titled “Prediction of Pathway Related Protein, Drug and Disease Association Based on Complex Network and Deep Learning,” was supervised by Prof. Xiujuan Lei. He completed his M.Phil. in Computer Science with a specialization in Search Engine Optimization from the University of Sindh, Jamshoro. His academic journey began with a Bachelor of Computer Science (BCS-Hons) from the same university. Additionally, he obtained various certifications and diplomas in information technology, further strengthening his expertise in computing and AI.

Experience

Dr. Ali has a strong academic and research background, currently holding the position of Assistant Professor at Sindh Agriculture University, Tandojam. His professional journey includes extensive work on bioinformatics, AI-based predictive models, and computational biology. He has contributed significantly to research in AI applications for human protein sequence analysis, disease detection, and biomedical data transformation. With a deep understanding of AI, deep learning, and machine learning techniques, he has played a pivotal role in advancing bioinformatics research and education.

Research Interests

Dr. Ali’s research primarily revolves around bioinformatics and artificial intelligence. He is particularly focused on human disease pathway modeling, drug-protein interaction prediction, and machine learning applications in genomics. His work involves utilizing AI to enhance precision diagnostics, early-stage disease detection, and advanced biomedical data analysis. By leveraging deep learning and AI-driven methodologies, Dr. Ali aims to improve healthcare analytics and disease treatment strategies. His research has practical implications in the fields of computational biology, digital health frameworks, and AI-driven medical solutions.

Awards and Recognitions

Dr. Ali has received numerous accolades for his contributions to AI and bioinformatics research. His high-impact factor publications and citations reflect his significant contributions to the scientific community. With an H-index of 12 on Google Scholar, an i10-index of 18, and a ResearchGate H-index of 11, his research has been widely recognized and cited. He has also been nominated for various research excellence awards, highlighting his influence in the field of computational biology and AI-driven biomedical advancements.

Publications

Ali, Ghulam, et al. (2025). “StackAHTPs: An explainable antihypertensive peptides identifier based on heterogeneous features and stacked learning approach.” IET Systems Biology, 19(1), e70002. (SCI, IF: 1.9, Cited by: X).

Arif, Muhammad, et al. (2024). “StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features.” Methods, 230, 129-139. (SCI, IF: 4.02, Cited by: X).

Arif, Muhammad, et al. (2024). “DPI_CDF: Druggable protein identifier using cascade deep forest.” BMC Bioinformatics, 25(1), 1-18. (SCI, IF: 3.09, Cited by: X).

Talpur, Fauzia, et al. (2024). “ML-Based Detection of DDoS Attacks Using Evolutionary Algorithms Optimization.” Sensors, 24(5), 1672. (SCI, IF: 3.09, Cited by: X).

Ghulam, Ali, et al. (2024). “Assessment of Performance of Machine Learning Classification Techniques for Monkey Pox Disease Detection.” Journal of Innovative Intelligent Computing and Emerging Technologies, 1(1), 1-7. (Cited by: X).

Memon, Mukhtiar, et al. (2023). “AiDHealth: An AI-enabled Digital Health Framework for Connected Health and Personal Health Monitoring.” (Cited by: X).

Sikander, Rahu, et al. (2023). “Identification of cancerlectin proteins using hyperparameter optimization in deep learning and DDE profiles.” Mehran University Research Journal of Engineering & Technology, 42(4), 28-40. (WoS, Cited by: X).

Conclusion

Dr. Ghulam Ali is a distinguished researcher and academician in the field of artificial intelligence and bioinformatics. His contributions to AI-driven biomedical research, particularly in disease pathway modeling and predictive analytics, have significantly advanced the field. With a strong publication record, multiple citations, and a commitment to innovation, he continues to influence computational biology and digital health research. His work bridges the gap between AI and medical sciences, paving the way for future breakthroughs in bioinformatics and AI-driven healthcare solutions.

Hamza Kahri | AI in Healthcare | Best Researcher Award

Dr. Hamza Kahri | AI in Healthcare | Best Researcher Award

Researcher | Tours University | France

Dr. Hamza Kahri is a highly accomplished chemist specializing in materials chemistry, with a focus on the development of Metal-Organic Frameworks (MOFs), nanomaterials, and their applications in energy storage, CO2 capture, hydrogen storage, and catalysis. Through extensive research during his PhD and postdoctoral studies, Dr. Kahri has authored over 27 peer-reviewed journal articles and actively contributed to the scientific community through teaching, supervising graduate students, and reviewing for leading chemistry journals. His interdisciplinary expertise and collaborative projects have solidified his standing as an innovator in the field.

Profile

Scopus

Education

Dr. Kahri’s academic journey began at the University of Monastir, Tunisia, where he earned a BSc in Chemistry in 2011, followed by an MSc in Chemistry specializing in Electrochemistry in 2013. He completed his PhD in Materials Chemistry in 2017, focusing on hydrogen generation through chemical hydrides using metal-based nanocatalysts. His doctoral work under the guidance of Prof. Ridha Touati and Prof. Umit B. Demirci emphasized innovative approaches to catalysis, setting the foundation for his future contributions.

Professional Experience

Dr. Kahri’s career includes a range of academic and research roles. He currently serves as a temporary assistant professor at Université de Tours, France, where he contributes to teaching and advanced research in energy materials. His previous roles include assistant professorships at Université de Poitiers, France, and the University of Monastir, Tunisia. His postdoctoral research at institutions such as Bilkent University, Turkey, and Atatürk University focused on spectroelectrochemistry of conducting polymers and the use of mesoporous materials in catalysis, respectively.

Research Interests

Dr. Kahri’s research focuses on the synthesis and application of MOFs, nanomaterials, and advanced catalysts for energy and environmental solutions. His work explores innovative techniques in electrochemical sensors, supercapacitors, and wastewater treatment. Additionally, he delves into heterogeneous catalysis and chemical kinetics, aiming to develop sustainable technologies for energy storage and pollutant remediation.

Awards and Recognition

Dr. Kahri’s excellence in research has been acknowledged through prestigious academic fellowships, including those from the Turkish Academy of Sciences and the Ministry of Education in France and Germany. These awards facilitated his research stays at leading institutions, enhancing his global academic collaborations and contributions.

Publications

Dr. Kahri has an extensive publication record in high-impact journals. Below are seven representative works:

Enhanced Catalysis of Monodisperse AgPd Alloy Nanoparticles (Nano Research, 2017; IF 9.9) – This work focuses on ammonia borane dehydrogenation under sunlight.

Hydrogen Generation from Sodium Borohydride (RSC Advances, 2016; IF 3.9) – Discusses cobalt-copper catalysts in hydrolysis reactions.

Dopamine Detection via Modified Electrodes (Journal of Electrochemical Society, 2020; IF 3.9) – A study on advanced electrochemical sensors.

Simultaneous Detection of Catechol and Hydroquinone (IEEE Sensors Journal, 2021; IF 4.3) – Highlights the application of nanomaterial-modified electrodes.

Development of Non-Enzymatic Cholesterol Sensors (Journal of Iranian Chemical Society, 2021; IF 2.4) – Research on composite-based sensors.

Rapid Synthesis of Zeolitic Imidazolate Frameworks (Journal of Materials Science, 2022; IF 4.5) – Investigates CO2 and CH4 adsorption properties.

Cu-MOF Catalyst for 4-Nitrophenol Reduction (Reaction Chemistry & Engineering, 2022; IF 3.9) – Explores green catalysis approaches.

Conclusion

Dr. Hamza Kahri’s career reflects a deep commitment to advancing scientific knowledge in materials chemistry. His contributions to sustainable technologies and energy applications underscore his dedication to solving global challenges. As a mentor, researcher, and collaborator, Dr. Kahri’s work continues to inspire innovation in the scientific community.