Umeshkumar KU | Bioinformatics | Best Researcher Award

Published-on by Indian Scientist

Dr. Umeshkumar KU | Bioinformatics | Best Researcher Award

Teerthanker Mahaveer university | India

Umeshkumar KU is an Innovation Architect, Registered Patent Agent, and Computational Biologist specializing in AI/ML-driven solutions for zoonotic threats and antimicrobial resistance. He has a robust academic foundation with advanced degrees in Biotechnology and Bioinformatics, complemented by a postgraduate diploma in Intellectual Property and postdoctoral training in Innovation and Technology Transfer. Umeshkumar has accumulated extensive professional experience across universities, startups, and research institutions, leading intellectual property portfolios, mentoring early-stage deeptech founders, and managing end-to-end patent filings and technology commercialization. His research interests focus on microbial genomics, pathogen risk prediction, antibiotic resistance mechanisms, zoonotic potential, and the development of computational pipelines and AI models for genomic analysis. He has authored multiple high-impact research papers and filed patents in biotechnology and life sciences, demonstrating a strong commitment to advancing scientific knowledge and translating research into practical applications. Umeshkumar’s contributions have been recognized with awards for innovative work and leadership in IP and biotechnology. Actively engaged in institutional innovation programs, workshops, and advisory roles, he drives the integration of research, technology transfer, and strategic intellectual property management, fostering a culture of innovation and excellence.

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Featured Publications


Descriptive genomic analysis of antibiotic resistance in Pasteurella multocida isolates from India

– Journal of Zoonotic Diseases, 9(2), 771–780 (2025) – Cited by 1 | DOI: 10.22034/jzd.2024.18654 :contentReference[oaicite:0]{index=0}


Genomic characterization of Pasteurellaceae strains: Resistance mechanisms, virulence factors, and HGT potential

– In Silico Research in Biomedicine, 1, 100015 (2025) – Cited by 1 | DOI not yet listed but indexed :contentReference[oaicite:1]{index=1}


Zoonoticus: A Machine Learning Model for Genomic Prediction of Zoonotic Bacterial Strains Using Virulence, Resistance, and Mobile Genetic Elements

– Computational Biology and Chemistry, 108760 (2025) – Cited: PubMed listing | DOI: 10.1016/j.compbiolchem.2025.108760 :contentReference[oaicite:2]{index=2}


META‑ANALYSIS OF MICROBIAL DIVERSITY IN YOUNG CATS USING T-BIOINFO SERVER

– Suranaree Journal of Science & Technology 31(6), 2024 – [DOI link requires journal confirmation] :contentReference[oaicite:3]{index=3}

Partha Majumder | Human Genetics | Lifetime achievement Award

Published-on by Indian Scientist

Prof. Partha Majumder | Human Genetics | Lifetime achievement Award

John C. Martin Center for Liver Research & Innovations/Indian Statistical Institute | India

Prof. Partha Majumder is a globally respected leader in human genetics, celebrated for shaping modern population genomics and advancing the scientific understanding of human diversity, disease risk, and evolutionary patterns. With an outstanding research record supported by 16,578+ citations, an h-index of 58, and 214+ indexed publications, his scholarly influence spans population-based genomic variation, statistical genetics, precision medicine, and computational modeling. He has authored foundational studies that transformed views on genetic structure across South Asian populations, and his contributions have been widely recognized through major scientific honors and memberships in premier academies. Prof. Majumder’s academic journey includes rigorous training in statistics and genetics, leading to prestigious appointments across India and internationally, where he has guided institutions, established key genomic research programs, and mentored several generations of scientists. His research interests center on human evolutionary genetics, disease genomics, biomedical statistics, and ethical frameworks for genomic data use. His experience encompasses leadership roles in national genome initiatives, advisory committees, and collaborative global consortia. Deeply committed to science-driven societal impact, Prof. Majumder continues to inspire through his relentless pursuit of knowledge, impactful discoveries, and enduring contributions to the growth and integrity of human genetics research.

Profile: Google Scholar

Featured Publications

Regev, A., Teichmann, S. A., Lander, E. S., Amit, I., Benoist, C., Birney, E., … Human Cell Atlas. (2017).
The human cell atlas. eLife, 6, e27041. https://doi.org/10.7554/eLife.27041

HUGO Pan-Asian SNP Consortium, Abdulla, M. A., Ahmed, I., … Majumder, P. P. (2009). Mapping human genetic diversity in Asia. Science, 326(5959), 1541–1545. https://doi.org/10.1126/science.1177074

Sengupta, S., Zhivotovsky, L. A., King, R., Mehdi, S. Q., Edmonds, C. A., Chow, C. E. T., … Majumder, P. P. (2006). Polarity and temporality of high-resolution Y-chromosome distributions in India identify both indigenous and exogenous expansions and reveal minor genetic influence of Central Asia. The American Journal of Human Genetics, 78(2), 202–221. https://doi.org/10.1086/499411

Basu, A., Mukherjee, N., Roy, S., Sengupta, S., Banerjee, S., Chakraborty, M., … Majumder, P. P. (2003).
Ethnic India: A genomic view, with special reference to peopling and structure. Genome Research, 13(10), 2277–2290. https://doi.org/10.1101/gr.1413403

Underhill, P. A., Myres, N. M., Rootsi, S., Metspalu, M., Zhivotovsky, L. A., King, R. J., … Majumder, P. P. (2010). Separating the post-Glacial coancestry of European and Asian Y chromosomes within haplogroup R1a. European Journal of Human Genetics, 18(4), 479–484. https://doi.org/10.1038/ejhg.2009.194

Sajja Tulasi Krishna | Computer Science | Research Excellence Award

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Dr. Sajja Tulasi Krishna | Computer Science | Research Excellence Award

Koneru Lakshmaiah Education Foundation | India

Dr. Sajja Tulasi Krishna is a distinguished researcher and academician in Computer Science and Engineering, currently serving as an Assistant Professor at Koneru Lakshmaiah Education Foundation. She has extensive teaching experience in areas including CI/CD, Cloud DevOps, Python Full Stack Development, MERN Stack Web Development, Deep Learning, and Data Structures. Dr. Krishna earned her Ph.D. in Computer Science and Engineering and holds advanced degrees in M.Tech and B.Tech, reflecting a strong academic foundation. Her research focuses on deep learning, machine learning, biomedical image processing, and intelligent systems, with contributions in multi-omics integration, lung cancer detection, COVID-19 diagnosis, and medicinal plant classification. She has published 18 research articles in SCIE, Scopus, and IEEE journals, achieving a total of 488 citations with an h-index of 5 and an i10-index of 5. Dr. Krishna has presented her work at multiple national and international conferences, serving as a reviewer for reputed journals and conferences. She has received multiple awards recognizing her excellence in teaching, research, and technical contributions, including Best Teacher, International Excellence, and Young Researcher Awards. With her expertise, she continues to advance innovative research while mentoring students and contributing to the academic community globally.

Profiles: Google Scholar | Scopus | Orcid

Featured Publications

Krishna, S. T., & Kalluri, H. K. (2019). Deep learning and transfer learning approaches for image classification. International Journal of Recent Technology and Engineering (IJRTE), 7(5S4), 427–432.

Sajja, T. K., Devarapalli, R. M., & Kalluri, H. K. (2019). Lung cancer detection based on CT scan images by using deep transfer learning. Traitement du Signal, 36(4), 339–344.

Sajja, T. K., & Kalluri, H. K. (2020). A deep learning method for prediction of cardiovascular disease using convolutional neural network. Revue d’Intelligence Artificielle, 34(5), 601–606.

Sajja, T. K., & Kalluri, H. K. (2021). Image classification using regularized convolutional neural network design with dimensionality reduction modules: RCNN–DRM. Journal of Ambient Intelligence and Humanized Computing, 12(10), 9423–9434.

Sajja, T. K., & Kalluri, H. K. (2019). Gender classification based on face images of local binary pattern using support vector machine and back propagation neural networks. Advances in Modelling and Analysis B, 62(1), 31–35.

Satyamvada Maurya | Computational Biology | Best Researcher Award

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Mrs. Satyamvada Maurya | Computational Biology | Best Researcher Award

ICAR-National Bureau of Fish Genetic Resources | India

Dr. Satyamvada Maurya is a bioinformatics researcher with extensive experience in genomics, computational biology, and drug discovery. She holds a Ph.D. in Bioinformatics, focusing on the design and development of novel anti-tuberculosis agents through computational approaches. Her academic foundation includes a Master’s in Bioinformatics and a Bachelor’s in Biotechnology, which laid the groundwork for her multidisciplinary research. She has worked as a Project Assistant and Young Professional in premier Indian research institutes, contributing to projects in genome analysis, database development, SNP characterization, and functional genomics of aquatic organisms, particularly Clarias magur. Her research interests span next-generation sequencing, genome analysis, protein structure-function prediction, drug design, homology modeling, phylogenetic analysis, and database creation for biological resources. She has authored multiple research articles, book chapters, training manuals, and popular science articles, accumulating 27 citations with an h-index of 3 and i10-index of 1, reflecting the impact of her work. She has received awards including the TEQIP fellowship and best presentation accolades at national and international conferences. Dr. Maurya is committed to advancing bioinformatics applications in both healthcare and aquaculture, bridging computational tools with experimental biology to address complex biological challenges. Her work continues to contribute to the development of innovative solutions in genomics and drug discovery.

Profile: Google Scholar

Featured Publications

Verma, S., Maurya, R., & Maurya, S. (2016). Prediction of gene action and combining ability for yield and quality traits in F1 and F2 generations of wheat (Triticum aestivum L.). Tropical Plant Research, 3(2), 449–459.

Maurya, S., Jain, A., Singh, V., Haque, S., & Mishra, B. N. (2023). Evaluation of Saraca asoca for its anti-tubercular potential via molecular docking and molecular dynamics simulation studies. ChemistrySelect, 8(12), e202204899.

Maurya, S., Alhazmi, A., Vidyarthi, A. S., Jain, A., Singh, V., Khan, F., Haque, S., & Mishra, B. N. (2022). In-silico study reveals potential antitubercular drug targets unique to Mycobacterium tuberculosis H37Rv. Minerva Biotechnology & Biomolecular Research, 34(2), 71–79.

Maurya, S., Kumar, M. S., Kumar, R., & Kushwaha, B. (2024). Role of machine learning and artificial intelligence in transforming aquaculture and fisheries sector. Indian Farming, 74(8), 24–27.

Maurya, S., Jain, A., Rehman, M. T., Hakamy, A., Bantun, F., AlAjmi, M. F., Singh, V., … Mishra, B. N. (2023). In silico identification of novel derivatives of rifampicin targeting Ribonuclease VapC2 of M. tuberculosis H37Rv: Rifampicin derivatives target VapC2 of Mtb H37Rv. Molecules, 28(4), 1652.

Riya Mukherjee | Meta Research | Best Researcher Award

Published-on by Indian Scientist

Ms. Riya Mukherjee | Meta Research | Best Researcher Award

Chang Gung University | India

Dr. Riya Mukherjee is a passionate and emerging researcher in biomedical sciences whose scholarly work integrates biotechnology, nanomedicine, and regenerative therapies. Her research primarily focuses on exosome-based therapeutic strategies for osteoarthritis, antimicrobial resistance, and tissue regeneration. She has authored multiple impactful publications, with a total of over 1,500 citations, h-index of 8, and approximately 45 documents indexed in global databases. Her notable works include studies on antioxidant assays, nanoparticle-based drug evaluation, and antimicrobial resistance, reflecting strong interdisciplinary expertise. She is currently pursuing her Ph.D. in Biomedical Sciences at Chang Gung University, Taiwan, where she also served as a Project Assistant and research contributor. Her academic background in microbiology from SRM University and Kalyani University strengthens her foundation in molecular and cellular biology. Dr. Mukherjee has presented at numerous international conferences and participated in innovation and entrepreneurship competitions, demonstrating leadership and creativity beyond laboratory research. Her research interests encompass exosome biology, nanotechnology, regenerative medicine, and computational biology. With several high-impact publications and international recognition, she continues to advance translational biomedical research aimed at global health improvement.

Profile: Google Scholar

Featured Publications

Baliyan, S., Mukherjee, R., Priyadarshini, A., Vibhuti, A., Gupta, A., Pandey, R. P., et al. (n.d.). Determination of antioxidants by DPPH radical scavenging activity and quantitative phytochemical analysis of Ficus religiosa. Molecules, 27(4), 1326. https://doi.org/10.3390/molecules27041326

Pandey, R. P., Vidic, J., Mukherjee, R., & Chang, C. M. (n.d.). Experimental methods for the biological evaluation of nanoparticle-based drug delivery risks. Pharmaceutics, 15(2), 612. https://doi.org/10.3390/pharmaceutics15020612

Mukherjee, R., Priyadarshini, A., Pandey, R. P., & Raj, V. S. (n.d.). Antimicrobial resistance in Staphylococcus aureus. In Insights into drug resistance in Staphylococcus aureus. IntechOpen.

Pati, P. R., Riya, M., Anjali, P., Gupta, A., Vibhuti, A., Leal, E., Sengupta, U., et al. (n.d.). Potential of nanoparticles encapsulated drugs for possible inhibition of the antimicrobial resistance development. Biomedicine & Pharmacotherapy, 141, 111943. https://doi.org/10.1016/j.biopha.2021.111943

Léguillier, V., Pinamonti, D., Chang, C. M., Mukherjee, R., Cossetini, A., et al. (n.d.). A review and meta-analysis of Staphylococcus aureus prevalence in foods. The Microbe, 4, 100131.

Mansi Verma | Bioinformatics | Excellence in Research Award

Published-on by Indian Scientist

Dr. Mansi Verma | Bioinformatics | Excellence in Research Award

Hansraj College, University of Delhi, India

Author Profile

ORCID

GOOGLE SCHOLAR

🎓 EARLY ACADEMIC PURSUITS

Dr. Mansi Verma’s academic journey is marked by a solid foundation in biological sciences and computational methods, which paved the way for her specialization in Bioinformatics. She earned her undergraduate degree in Biotechnology, followed by a master’s degree in Bioinformatics, showcasing a strong interdisciplinary grasp of molecular biology, computer science, and statistics. Her academic rigor and analytical aptitude earned her early recognition through research fellowships and top-tier university placements.

🏢 PROFESSIONAL ENDEAVORS

Dr. Verma’s professional trajectory encompasses academic research, teaching, and collaborative scientific projects. She has held key positions in reputed research institutions and universities, contributing as a lecturer, senior research fellow, and post-doctoral researcher in bioinformatics and computational biology. Her expertise spans genomics, proteomics, and systems biology, and she has mentored numerous graduate and doctoral candidates in these areas.

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN BIOINFORMATICS

Dr. Mansi Verma’s core research focus lies in:

  • Genomic data analysis, with emphasis on disease gene prediction and variant calling.

  • Machine learning applications in omics data interpretation.

  • Network biology and molecular interaction mapping.

  • Designing algorithms for drug-target interaction prediction.

Her contributions include the development of novel bioinformatics pipelines, publication of peer-reviewed journal articles, and collaborations on multi-institutional projects for computational disease modeling.

🏅 ACADEMIC CITATIONS, ACCOLADES AND RECOGNITION

  • Citations: Over 1,500 citations on Google Scholar with an H-index of 18+.

  • Awards: Recipient of the Young Scientist Award in Bioinformatics (2021) and the Best Paper Presentation award at the International Conference on Computational Life Sciences.

  • Memberships: Active member of the ISCB (International Society for Computational Biology) and INSA

🌍 IMPACT AND INFLUENCE

Dr. Verma’s work has significantly impacted precision medicine and personalized therapeutics, especially in oncogenomics and rare genetic disorders. She has contributed to open-source databases, aiding scientists globally in accessing curated genetic datasets. As an invited speaker and panelist, she actively participates in international bioinformatics forums, shaping discussions on ethical AI in biological research.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Dr. Mansi Verma is not only an innovator in algorithmic biology but also a mentor and advocate for women in STEM. Her legacy includes:

  • A growing repository of open-access computational tools.

  • Curriculum contributions in Bioinformatics education.

  • A forthcoming book on “Deep Learning in Bioinformatics: A Systems Perspective.”

Her future research is poised to delve into multi-omics integration using generative AI models, further accelerating discovery in disease mechanism prediction.

 ✅CONCLUSION

Dr. Mansi Verma represents the convergence of biological intelligence and computational innovation. With a visionary approach to biomedical informatics, her work continues to inspire and elevate the global bioinformatics landscape. Her ability to translate complex biological phenomena into actionable computational frameworks makes her a thought leader in the 21st-century biosciences revolution.

 🔬NOTABLE PUBLICATION:

Global Impact of Tuberculosis and HIV Coinfection

  • Authors: Aeshna Nigam, Udita Mukherjee, Mansi Verma

  • Journal: Microsphere

  • Year: 2022

Exploring Microbial Potential for Sustainable Agriculture

  • Authors: Varunendra Singh Rawat, Mansi Verma, Helianthous Verma, Charu Dogra Rawat

  • Journal: Microsphere

  • Year: 2022

Highly Conserved Epitopes of DENV Structural and Non-Structural Proteins: Candidates for Universal Vaccine Targets

  • Authors: Mansi Verma (and co-authors, names not fully listed here)

  • Journal: Gene

  • Year: 2019

From Dengue to Zika: The Wide Spread of Mosquito-Borne Arboviruses

  • Authors: Shivani Sukhralia, Mansi Verma, Shruthi Gopirajan, P. S. Dhanaraj, Rup Lal, Neeti Mehla, Chhaya Ravi Kant

  • Journal: European Journal of Clinical Microbiology & Infectious Diseases

  • Year: 2019

Mr. Subhrangshu Das – Bioinformatics – Best Researcher Award 

Published-on by Indian Scientist

Mr. Subhrangshu Das - Bioinformatics - Best Researcher Award 

CSIR-Indian Institute of Chemical Biology - India

PROFESSIONAL PROFILES

SCOPUS

GOOGLE SCHOLAR

Early Academic Pursuits

Subhrangshu Das's academic journey began with a strong foundation in science during his Higher Secondary Examination at Agarpara Mahajati Vidyapith, West Bengal, where he excelled in subjects like Physics, Chemistry, Mathematics, and Statistics. He then pursued a Bachelor of Technology (B.Tech.) in Computer Science & Engineering from Narula Institute of Technology, graduating with first-class honors in 2012. His quest for knowledge led him to Jadavpur University, where he earned a Master of Engineering (M.E.) in Computer Science & Engineering in 2014, also with first-class honors. His academic pursuits culminated in submitting his Ph.D. thesis in Structural Biology and Bioinformatics at the University of Calcutta in 2022, showcasing his interdisciplinary approach to combining computer science with biological research.

Professional Endeavors

Subhrangshu Das's professional career is marked by significant roles at the CSIR-Indian Institute of Chemical Biology. He began as a Junior Research Fellow in August 2022, progressing to a Senior Research Fellow by November 2015. His dedication and expertise earned him the position of Research Associate in August 2022. Throughout these roles, he has been involved in critical research projects that bridge computer science and bioinformatics, demonstrating his ability to apply computational techniques to biological problems.

Contributions and Research Focus On Bioinformatics

Subhrangshu Das has made substantial contributions to the fields of structural biology and bioinformatics. His research primarily focuses on image processing, machine learning, and data science, applied to medical and biological problems. Notable projects include developing an algorithm for detecting Alzheimer's disease from brain MRI using image processing and machine learning techniques, and quantifying and categorizing strokes from brain CT scan images. His work on the classification and prediction of protein-protein interaction interfaces using machine learning algorithms has been published in reputable journals, Bioinformatics highlighting his innovative approach to computational biology.

Accolades and Recognition

Throughout his career, Subhrangshu Das has received numerous accolades and recognition for his academic and research excellence. He qualified for the GATE examination twice, in 2011 and 2012, and achieved a commendable All India Rank. He also qualified for the CSIR NET in December 2014, securing an impressive rank of 92. His achievements have been further recognized through scholarships from UGC and CSIR, Bioinformatics supporting his studies and research endeavors. These accolades underscore his commitment to academic excellence and research innovation.

Impact and Influence

Subhrangshu Das's work has had a significant impact on both the academic and research communities. His contributions to Alzheimer's disease detection and stroke quantification have the potential to influence medical diagnostics and patient care. His mentorship and collaboration with peers and students have helped foster a new generation of researchers in the fields of computer science and bioinformatics. His published works and conference presentations have disseminated his research findings to a broader audience, Bioinformatics influencing ongoing studies and sparking new research ideas.

Legacy and Future Contributions

Looking ahead, Subhrangshu Das's legacy in interdisciplinary research is poised to inspire future innovations in bioinformatics and structural biology. His ongoing projects, such as the development of web servers for Alzheimer's disease detection and protein complex prediction, demonstrate his commitment to advancing scientific knowledge and practical applications. As he continues to explore new frontiers in research, Bioinformatics his contributions are expected to have a lasting impact on the scientific community, paving the way for future discoveries and technological advancements.

NOTABLE PUBLICATIONS