Professional Experiences:
September 2024–Present: Principal Biostatistician at Pfizer India, Chennai, India.
August 2022–August 2024: Postdoctoral Research Fellow, Saw Swee Hock School of Public Health, National University of Singapore, Singapore.
Academic Qualifications :
2018–2022: Doctor of Philosophy (Ph.D.) from Banaras Hindu University, Varanasi, India. (BHU)
Thesis Title: STATISTICAL MODELING AND ANALYSIS OF COMPETING RISK LIFETIME DATA (Thesis)
Supervisor: Dr. M. S. Panwar (Profile)
2015–2017: Master of Science (M.S.) from the University of Allahabad, Prayagraj, India. (UoA)
Master's Project: CUSTOMER CHURN ANALYSIS using ML Techniques
Advisor: Prof. Subramanian LALITHA
2012–2015: Bachelor of Science (B.Sc.) from the University of Allahabad, Prayagraj, India. (UoA)
Subjects: Statistics, Mathematics, and Physics.
2010–2012: Higher Secondary Examination (H.S.) from R A MISHRA I C, Lalganj, Pratapgarh, UP, India.
Board: Uttar Pradesh State Board of High School and Intermediate Education
Subjects: Mathematics, Physics, Chemistry, English, and Hindi.
2008–2010: Secondary Examination from Yamuna Prasad Yadav Uchhatar Madhymic Vidyalay, Verma Nagar (Affiliated: R R Yadav Higher Secondary, Rampur Khas, Pratapgarh, UP, India)
Board: Uttar Pradesh State Board of High School and Intermediate Education
Subjects: Mathematics, Science, English, Social Science, Hindi, and Drawing
Awards Received:
APSR Assembly Education Award (Link) for abstract presentation "Application of Bayesian network in investigating risk factors and treatment interactions in severe asthma patients" at the Asian Pacific Society of Respirology conference, November 16-19, 2023, Singapore. [APSR(2023)]
Recipient of UGC Research Fellowship (Mar, 2018 - Mar, 2022) during Ph.D. at Banaras Hindu University.
Studies with Media Coverage:
Study 1:
A novel Bayesian Network analysis on the International Severe Asthma Registry (ISAR) has identified key clinical and biological pathways that contribute to the risk of future severe exacerbations in patients with severe asthma. Leveraging real-world data from over 6,800 biologic-naïve adults across 17 countries, the study—recently published in CHEST under the title “Prediction Pathway for Severe Asthma Exacerbations: A Bayesian Network Analysis”—provides significant insights into how complex clinical factors interact to influence exacerbation risk.
To learn more about the study, please read the full publication in CHEST, as well as the accompanying slide deck.
Study 2:
Pathways that predict severe asthma attacks (exacerbations) were found to be similar, with matching strength of prediction, in both clinical trials (Randomised Controlled Trials, RCTs) and real-world data (RWD) settings in the new International Severe Asthma Registry (ISAR) study “Interactive Pathways of Key Prognostic Factors in Severe Asthma: A Bayesian Network Comparison of Clinical Trials & Real-World Data”.
To learn more about the study, please read the full publication in CHEST, as well as the accompanying slide deck.
Served as Refereed for Prestigious Journals:
Computational Statistics, Healthcare, Symmetry;
Mathematics, International Journal of Population Data Science;
BMC Public Health, Clinical Epidemiology;
Statistical Methods in Medical Research