SNA Shah
KR Mangalam University, Galgotias University, Jamia Millia Islamia, Islamic University of Science and Technology
0000-0002-3189-4217
About
Dr. Syed Naseer Ahmad Shah is an Assistant Professor of Computer Science in the School of Engineering and Technology at K.R. Mangalam University, Gurgaon (Delhi NCR). He holds a Ph.D. from Jamia Millia Islamia, New Delhi, where his doctoral research focused on leveraging deep learning frameworks to address complex challenges in computational cancer biology.
His primary research interests lie at the forefront of AI in healthcare, with a specific focus on bioinformatics, genomics, transcriptomics, and explainable deep learning. Driven by a mission to create tangible biomedical impacts, his work focuses on developing interpretable machine learning models to decode complex biological systems and improve diagnostic and therapeutic outcomes.
An active contributor to the academic community, Dr. Shah has authored over 20 peer-reviewed publications in leading journals and conferences, earning accolades including a Best Paper Award. Alongside his research, he is dedicated to teaching and mentoring the next generation of engineers and scientists in artificial intelligence, data science, bioinformatics and core computer science disciplines.
Employment
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KR Mangalam University Assistant Professor (Data Science and AI)2025 - Present
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Galgotias University Assistant Professor (AI and Data Science)2025 - 2026
Education
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Jamia Millia Islamia PhD2021 - 2024
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Islamic University of Science and Technology MCA (Masters in Computer Science)2017 - 2020
Projects & Funding
Projects & funding information is unavailable.
Publications (16)
- A hybrid feature extraction framework combining PCA and mutual information for gene expression based lung cancer classification Save
- Deep Learning Approaches to Enhance Lung Cancer Diagnosis Using Next Generation Sequencing: State of the Art Save
- Large language models for automated drug target discovery and literature mining Save
- Large language models for automated drug target discovery and literature mining Save
- Machine learning for genomic profiling and drug discovery in personalised lung cancer therapeutics Save
- AI for Disease Management, Medication Management, and Rehabilitation Care Save
- Personalized Healthcare Services for Assisted Living in Healthcare 5.0 Save
- An extensive review on infectious disease diagnosis using machine learning techniques and next generation sequencing: State-of-the-art and perspectives Save
- Differential gene expression analysis and machine learning identified structural, TFs, cytokine and glycoproteins, including SOX2, TOP2A, SPP1, COL1A1, and TIMP1 as potential drivers of lung cancer Save
- Wellness Management Powered by AI Technologies Save