Fengling (Feng) Hu, PhD
MD-PhD student
Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Perelman School of Medicine
Welcome
Hi, it’s nice to meet you! I’m Feng, a sixth-year MD-PhD student in Biostatistics. I completed my PhD in the PennSIVE group at the Perelman School of Medicine with Dr. Russell (Taki) Shinohara. My research interests include developing novel statistical and machine-learning-based methodology for neuroimaging and other big data settings. So far, I’ve developed tools for multi-modal image analysis, unsupervised MRI segmentation problems, and image harmonization. I’m particularly interested in leveraging powerful and flexible methods, such as deep learning, in statistically-informed ways and building new methods alongside the scientists who will use them.
Outside of my methodological work, I’m interested in teaching biomedical researchers and clinicians how to get the most out of their data in a statistically-sound way, as well as how to interpret studies and clinical trials from a statistical lens. I’ve also served as a statistical consultant for a number of biomedical, clinical, and health informatics projects. To formalize the process, organize real-life consulting experience for fellow Biostatistics students, and provide a free and effective statistical service to fellow biomedical trainees, I founded and run the Biostatistical Student Analysis Core (BSAC) within the Biostatistics graduate program! If you’re a Penn biomedical trainee of any kind and are interested in working together, please reach out to us through our BSAC Intake Application! We’d love to hear from you!
Clinically, I’m interested in anesthesiology, radiology, and neurology. I love the mix of diagnosis, medical thinking, and opportunity for procedure within these specialties. Over the last few years of my MD, I’m excited to learn more!
View my CV here or at the “My CV” tab above!
- Neuroimaging
- Deep learning
- Clinical trials
- Observational studies
- scRNA-seq
- Spatial statistics
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MD-PhD student in Biostatistics, 2019—present
University of Pennsylvania
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BA in Statistics and Biology, 2015—2019
Amherst College
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High school, 2012—2015
Illinois Mathematics and Science Academy (IMSA)
Skills
Research Experience
- Learn, apply, and extend theoretical statistics concepts in the biomedical setting.
- Develop and validate statistically-motivated methodology for computational neuroscience.
- Collaborate with neuroimaging scientists on applied segmentation and analysis problems.
- Work with Graduate Group leadership to build, organize, and run BSAC within PhD program time and funding constraints.
- Lead outreach for new collaborations and connect collaborators to consultants with appropriate skillset.
- Advocate for fellow BSAC consultants to get appropriate credit and conduct consultations that are limited in scope.
- Provide statistical guidance and conduct analyses for basic science, clinical, and health informatics collaborators.
- Draft methodological descriptions and create figures for publication.
- Investigate essential metal characteristics in weedy rice species to determine the metal uptake mechanisms.
- Establish Arabidopsis thaliana lines with mutations in essential iron-deficiency response proteins.
- Provide statistical guidance for experimental design and analysis of complex data.
- Create publication-quality figures and draft manuscript.
- Perform mixed-methods, thematic analysis on a program designed to improve postpartum return to care.
- Investigate themes in text-message-based communication correlated with return for postpartum care.
- Tutor students in Introduction to Statistics, Intermediate Statistics, and Probability in lecture materials, homework, and R code.
- Review class handouts and create solution sets R worksheets.
- Serve as a statistical analyst for various on-campus academic and administrative departments and projects.
- Write and edit manuscript draft describing impact of NPLD on labor and delivery outcomes in China
- Collect and analyze longitudinal data on changes in labor and delivery outcomes across multiple Chinese hospitals.
- Mediate conversation between American obstetricians, obstetrical anesthesiologists, neonatologists, and nurses and their Chinese counterparts in the delivery rooms of target hospitals for one week each summer. The goals were to facilitate use of labor analgesia, decrease Cesarean rates, and provide better neonatal care.
- Provide instruction and guidance to a team of mostly American high school, college, and medical school students who are semi-fluent to fluent in Chinese.
- Maintain and distribute an updating list of commonly encountered medical terminology and their translations.
- Analyzed single cell RNA sequencing data to determine appropriate methodology for analyzing cell populations and characterizing data collection errors.
- Learned theory behind statistics methodology, applications of big data statistics, and implementation of learned concepts in R.
All Publications
Contact
- fengling.hu@pennmedicine.upenn.edu
- 423 Guardian Drive, Philadelphia, PA 19104
- GitHub