Parikh Lab

Meet the Lab

Nehal A. Parikh, DO, MS

Principal Investigator, Early Prediction Study 

Professor of Pediatrics, Perinatal Institute 

Nehal Parikh, DO, MS has led or co-led several cohort studies of advanced brain MRI in very preterm infants, clinical trials of neuroprotective therapies in high-risk newborns, and the development of the NICHD Extremely Preterm Birth Outcomes prognostic calculator/website. Following training in neonatology, translational research and clinical trials, he has conducted several clinical studies of etiology, prediction and prevention of neurodevelopmental disabilities in high-risk newborns.

nehal.parikh@cchmc.org

Twitter: https://twitter.com/DrNehalParikh

Karen Harpster, PhD, OTR/L

Occupational Therapist III 

Karen received her Master's in Occupational therapy and Ph.D. both from The Ohio State University.  She is a clinician scientist and occupational therapist and has been at Cincinnati Children’s Hospital since 2011.  Karen is also an assistant professor at the University of Cincinnati and a faculty member for the Leadership Education in Neurodevelopmental and Related Disability (LEND) Program. Clinically, Karen evaluates and treats children with neurodevelopmental disorders with a large focus on infants and children with cerebral palsy and/or cortical visual impairment.  Karen’s research focus is to develop research and clinical programs for prevention and early treatment for infants at high-risk for cerebral palsy and those with visual impairment.

Lili He, PhD

Assistant Professor 

Lili is a computer scientist by training with a BS degree in Electronical Engineering from Tsinghua University (Beijing, China), an MS degree in Computer Science from The University of Missouri (Columbia, Missouri), and a PhD in Computer Science and Engineering from The University of Connecticut (Connecticut, USA). She completed her post-doctoral fellow training at Massachusetts General Hospital, Harvard Medical School in 2010. Prior coming to Cincinnati, she worked as a senior computer scientist at the Center for Perinatal Research, The Research Institute at Nationwide Children's Hospital. Lili has a long-standing commitment to improve the prediction of neurodevelopmental outcomes for high risk newborns and infants. Her expertise focuses on the development of objective and quantitative advanced MRI methods to identify multimodal neuroimaging biomarkers in infants. Her current research emphasizes the development of novel machine learning and deep learning algorithms for early prediction of long-term neurodevelopmental disabilities in preterm infants.

Venkata Sita Priyanka Illapani, MS

Research Assistant III 

Priyanka was born and raised in South India and came to the U.S. to obtain a graduate degree in Biomedical Engineering at The Ohio State University. She joined the Cincinnati Children’s community 2 years ago from Minnesota. Prior to her work at Children’s, she was a Systems Analyst at the Department of Human Services in Minnesota. Now her work focuses on image quality and analysis.

Julia Kline

Research Associate

Julia Kline received a PhD in Biomedical Engineering from The University of Michigan in 2015. For her thesis work, she used high-density EEG and signal processing to study cortical dynamics during human full-body motion. Afterwards, she spent three years as a Research Scientist at Fitbit in Silicon Valley, working on biosensing algorithms related to sleep, fitness, and mental health. Julia is currently part of the Early Prediction Study. She applies advanced MRI techniques to identify neonatal biomarkers that predict long-term cognitive and language outcomes. 

Hailong Li, PhD

Research Associate 

Hailong is a Research Associate in the Parikh Lab. He received his Ph.D. in Computer Science in 2013 from The University of Cincinnati. He joined the Parikh Lab in 2016. His research focuses on applying machine learning algorithms to neonatal brain MRI data for risk prediction in very preterm neonates. His current studies include structural and functional MRI data analysis with deep neural networks (DNN), deep convolutional neural networks (CNN), and Capsule Networks using advanced machine learning tools, such as TensorFlow, Keras, and Python.

Donna Wuest

Senior Administrative Assistant

Donna received an Associate’s Degree from The University of Cincinnati.  She started at Children’s in 2007 in the Division of Biostatistics and Epidemiology. Donna then moved to Neonatology in 2009. Her background at Children’s is in research support. Although Donna was born and raised in Kentucky, she currently resides in Ohio near her 2 sons and 5 grandchildren.