Dr. Himanshu Tolani

Dr. Himanshu Tolani

Assistant Professor (S.S.)

Profile Summary

Dr. Himanshu Tolani started his journey as an aspiring researcher in applied statistics, he brought fervent dedication for advancing knowledge at the intersection of theory and practice. With a solid foundation statistical principle, honed through rigorous academic training and practical experience, he is poised to embark on doctoral research that bridges statistical theory with real-world applications. His interdisciplinary background equips me to navigate complex problems in diverse domains such as Public Health and Social sciences. From his master’s to doctoral degree in statistics he tried to build proficiency in various statistical methodologies, including Applied Bayesian inference, and always eager to contribute innovative solutions to contemporary challenges. Moreover, his passion for collaboration and effective communication ensures that his research not only pushes disciplinary boundaries but also resonates with broader audiences. Through my doctoral journey, his aim to make meaningful contributions to both the academic community and society at large, leveraging statistics as a powerful tool for informed decision-making and societal progress.

Work Experience

Dr. Himanshu brings experiences from both government and non-government organisations. He started as a visiting lecturer at Sri Venkateswara College then he worked at ICMR-National Institute of Medical Statistics, as a Research Associate, there, he applied statistical methods to analyse public health data and conducted spatio-temporal modelling, contributing to evidence-based decision-making in public health initiatives. Post to ICMR-NIMS he worked at NITI Aayog as a young professional and utilized advanced statistical techniques to evaluate policy effectiveness and inform strategic recommendations. He also worked at India Health Action Trust and there he spearheaded biostatistical research projects, driving impactful interventions in maternal and child health. More recently he worked at IIHMR Delhi as an Assistant Professor he collaborated on interdisciplinary research, applying biostatistical methodologies to address complex health systems challenges. He utilized is experiences in providing hands-on training on statistical software to like R to public health and medical graduates and working professionals. Through these diverse roles, he honed his skills in data analysis, interpretation, and communication, making tangible contributions to improving healthcare outcomes and informing policy at both local and national levels.

Research Interests

Dr. Himanshu has research interests that lie at the intersection of advanced statistical analysis and public health, focusing on the rigorous examination of medical and clinical data using sophisticated statistical tools. He is particularly deals with statistical modelling techniques, including applied Bayesian modelling, which offer nuanced insights into complex health phenomena. Additionally, he has worked on spatial analysis methods to uncover geographical patterns in health outcomes, while meta-analysis allows him to synthesize evidence across studies for comprehensive understanding. By leveraging these methodologies, his aim is to contribute to evidence-based decision-making, improve healthcare policies, and ultimately enhance population health outcomes.

Teaching Philosophy

Emphasizing intuitive understanding over rote memorization, he prioritizes active learning methods like case studies and hands-on exercises. Encouraging critical thinking, he empowers students to question assumptions and apply statistical principles creatively in analysing health data. Flexibility in approach accommodates diverse learning styles, fostering an inclusive classroom environment. Bridging theory with practice, he underscores the ethical imperative of statistical literacy in healthcare research and decision-making. Ultimately, his teaching philosophy aims to cultivate not just competent statisticians, but thoughtful analysts poised to address pressing public health challenges.

Courses Taught

In his teaching portfolio, he has offered a range of courses in statistics and biostatistics tailored to diverse academic levels. These include foundational courses covering basic statistical concepts, probability theory, and inferential statistics. Intermediate and advanced classes delve into specialized topics such as regression analysis, experimental design, survival analysis, and longitudinal data analysis. Additionally, he developed courses focusing on advanced statistical methodologies like Bayesian modelling, spatial analysis, meta-analysis and advanced statistical analysis using R. Through these courses, students gain comprehensive knowledge and practical skills essential for conducting robust statistical analyses in various fields, particularly in the realm of public health and medical research.

Scholarly Activities

His scholarly activities encompass a diverse range of pursuits. These include conducting original research and publishing findings in peer-reviewed journals, presenting at academic conferences, and securing research grants to support innovative projects. He actively engages himself in collaborative research endeavours, both within academia and with industry partners, fostering interdisciplinary dialogue and knowledge exchange. Additionally, he contributed to the scholarly community through serving as a peer reviewer for academic journals and participating in professional associations. Through these endeavours, he strives to advance the field of statistics, mentor aspiring researchers, and address pressing societal challenges through data-driven insights.