Overview:

This NISS–CANSSI Collaborative Data Science Webinar will focus on the role of modern data science and statistical methodology in advancing neonatal and perinatal research. The session will explore how rigorous study design, innovative analytic approaches, and careful treatment of uncertainty support high-impact clinical trials and observational studies in maternal and child health. Emphasis will be placed on the challenges of working with complex, multicenter clinical data, the integration of clinical expertise with statistical reasoning, and the translation of data-driven evidence into practice. The webinar will be of interest to researchers and practitioners engaged in biostatistics, data science, and interdisciplinary health research who seek to strengthen the methodological foundations of clinical and population-based studies.

Speakers

Dr. Anup Katheria, Associate Professor of Pediatrics at Drexel University College of Medicine, and Director of the Neonatal Research institute at Sharp Mary Birch Hospital for Women & Newborns

Dr. Abhik Das, Distinguished Fellow, Biostatistics at RTI International

Moderator

Sahar Zangeneh, Cascade Insights LLP

About the Speakers

Dr. Anup Katheria is an Associate Professor of Pediatrics at Drexel University College of Medicine, and the Director of the Neonatal Research institute at Sharp Mary Birch Hospital for Women & Newborns. Interests are in functional echocardiography, point of care ultrasound, and conducting clinical trials. I am currently conducting several large multi center trials: 1. comparing cord milking to early cord clamping in term non-vigorous infants, and 2. comparing delayed cord clamping to umbilical cord milking in preterm infants, 3. Comparing empiric antibiotic therapy to placebo in extremely low birthweight infants. 4. comparing early CPAP to early caffeine plus less invasive surfactant administration (LISA), 5. Evaluating the use of Cromolyn Sodium therapy to reduce BPD 6. Comparing the effectiveness of nasal high flow cannula to CPAP . Dr. Katheria earned his BS in Biology from the University of California, Los Angeles, his MD from Drexel University College of Medicine, completed his pediatric residency at Children’s Hospital of Orange County, and his Neonatal-Perinatal Fellowship at the University of California, San Diego. See Profile

Dr. Abhik Das is a Distinguished Fellow in Biostatistics. Having led the Data Coordination Center for the NICHD Neonatal Research Network (NRN) for 16 years, Dr. Das is an expert in modeling, analyzing, and interpreting public health data. He has a wealth of experience in the design of intervention studies, including randomized clinical trials, and he also provides statistical expertise in neonatology, substance abuse, health insurance coverage, diabetes, and maternal and child health. Since 1999, Dr. Das has been providing biostatistical leaderships for multicenter clinical studies in neonates. As the Principal Investigator for the Data Coordinating Center for the NRN, he helped design, implement, monitor, analyze and publish 30 plus multicenter randomized controlled trials, 20 plus observational studies, and 200 plus publications in perinatology that have informed clinical practice. Dr. Das has designed and analyzed studies in perinatal settings spanning a variety of designs, including Bayesian, pragmatic comparative effectiveness, comprehensive cohort, factorial, cluster randomized, phase II and pharmacokinetic studies. He has a wide range of experiences in a variety of areas, including studying near-term and neurodevelopmental morbidities, fetal alcohol effects, effects of prenatal substance use on development, pharmacologic interventions under investigational new drug application, and international trials in maternal-infant nutrition. Dr. Das is a member of the Society for Pediatric Research. He serves as the Associate Editor for the American Journal of Perinatology. Additionally, he is a reviewer on several journals, including JAMA Pediatrics and the Journal of Pediatrics. Dr. Das is also a reviewer on several study sections and data and safety monitoring committees associated with the National Institutes of Health (NIH), the National Science Foundation, and more. See Profile

About the Moderator

Sahar Zangeneh is a statistician at Cascade Insights LLP with broad expertise in the design and analysis of clinical and epidemiological studies. Her work draws on extensive experience with secondary data sources, including electronic health records, claims data, and disease registries, and she has strong methodological expertise in missing data, causal inference, and multilevel modeling. Sahar is deeply committed to interdisciplinary research and values team building and collaboration to address complex scientific questions. Previously, Dr. Zangeneh served as a Senior Research Statistician at RTI, where she specialized in the design and analysis of complex sample surveys and developed novel statistical methods for non-ignorable missing data. Her methodological research integrates classical and modern approaches, including parametric and nonparametric likelihood-based methods, Bayesian modeling, and machine learning tools. Her contributions have been recognized with multiple awards from professional societies, including the American Statistical Association, the International Society for Bayesian Analysis, and the Institute of Mathematical Statistics. Before joining RTI in 2021, Dr. Zangeneh was a faculty biostatistician in the Vaccine and Infectious Disease Division at the Fred Hutchinson Cancer Research Center, where she also completed her postdoctoral training. There, she conducted research focused on HIV and COVID-19 prevention and led the analysis of both observational and interventional studies, developing and implementing research protocols for diverse domestic and international health projects. She is also a Clinical Instructor at the University of Washington in Seattle, where she teaches and contributes to graduate-level curriculum development. Dr. Zangeneh is a member of several professional organizations, including the American Statistical Association, Institute for Mathematical Statistics, International Statistical Institute, International Society for Bayesian Analysis, and the Iranian Statistical Society, and she is deeply committed to advancing inclusion, diversity, and STEM engagement for underrepresented and underserved students. See Profile

About the NISS-CANSSI Collaborative Data Science Web Series:

The NISS-CANSSI Collaborative Data Science initiative that the National Institute of Statistical Sciences (NISS) in collaboration with the Canadian Statistical Sciences Institute (CANSSI) brings together experts from various fields to tackle complex data challenges through interdisciplinary teamwork and innovative methodologies.

Goals of the Initiative

The goal is to foster progress in:

• Developing new ideas for experimental and observational data-driven learning and discovery that address key questions at the cutting edge of science and scientific deduction;
• Quantifying and summarizing uncertainty in data-driven theories, as well as complex Data Science models, algorithms, and workflows; and
• Establishing new practices for scientific reproducibility and replicability through Data Science.

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