Technical Electives at MIT: 

  • Probability and Random Variables - 18.440
  • Foundations of Computational and Systems Biology - 20.390
  • Introduction to Computational Neuroscience - 9.29
  • Neurotechnology Ventures - 9.455
  • Quantitative Physiology: Organ Transport Systems - 20.371
  • Design Medical Devices and Implants - 20.451
  • Mechanisms of Drug Actions - 20.201
  • Cellular & Tissue Biomechanics - 20.310
  • Introduction to MATLAB - 6.094
  • Neuropharmacology - 9.98

Afrah Shafquat

Bachelor of Science in Biological Engineering, MIT, 2013

Professional Experience

Data Science Consultant
  • Slalom Consulting
  • Designed and developed statistical approaches and machine learning models for clients.
Harvard School of Public Health
  • Bioinformatics Analyst
  • Predicted functional annotations of unknown proteins by designing and developing Python pipeline.
Research Intern
  • Parkland Center for Clinical Innovation
  • Developed computational tool to predict corrections to errors in EMR data resulting in improved disease predictions.
Research Intern
  • University of California San Diego
  • Automated cardiac capacity prediction from CT images using Active Shape Model in MATLAB.

Educational Experience


  • Instructor: Instructed high school students in calculus, arithmetic, geometry and statistics for SAT Preparation.
  • MIT Information and Systems Technology – Technical Consultant
  • MIT TechFair – Executive Member

Participation in Programs: 

  • MIT Educational Studies Program

Undergraduate Research Experiences: 

  • Brigham and Women’s Hospital: Developed computational tools to integrate and validate epidemiological data for genetic disorders from various sources
  • Sasisekharan Lab: Developed a series of quality-control tests in Python to ensure workflow validity for antigen-antibody binding prediction
  • Fraenkel Lab: Quantified and compared zinc finger binding motif predictions using EM algorithm as compared to motifs in TRANSFAC using divergence metrics in Python
  • Bathe Lab: Developed automated method to extract chromosome tracks from 3D movies using MATLAB


  • Zifan A., Shafquat A., Chapman B.E., ‘Automatic Ventricle Chamber Segmentation Using a Regression Neural Network Initialization Based Active Shape Model,’ 2013 AMIA Clinical Research.
  • Shafquat A., Joice R., Simmons S. L. Huttenhower C., ‘Functional and phylogenetic assembly of microbial communities in the human microbiome’, (2014) Trends in Microbiology Vol. 22, Issue 5, Pages 261-66
  • Joice R., Yasuda K., Shafquat A., Morgan X., Huttenhower C., ‘Determining microbial products and identifying molecular targets in the human microbiome’, (2014) Cell Metabolism Vol. 20, Issue 5, Pages 731-741
  • Frazonsa E., Hsu T., Sirota-Madi A., Shafquat A., Abu-Ali G., Morgan X., Huttenhower C., ‘Sequencing and beyond: integrating molecular 'omics' for microbial community profiling’, (2015) Nature Methods Vol 13, Issue 6, Pages 360-372
  • Boernigen D., Moon Y.S., Waldron L., Shafquat A., Franzosa E., Sweeney C., Morgan X., Garrett W., Huttenhower C., ‘A reproducible approach to high-throughput biological data acquisition and integration’, (2015) PeerJ e79
  • Hsu T., Joice R., Morgan X., Vallarino J., Baranowski C., Shafquat A., Gevers D., Spengler J., Huttenhower C. ‘Microbial communities in an urban mass transit system’ (2016) MSystems
  • Shafquat A., Mezey J., ‘Identification of novel disease loci by Bayesian latent variable recoding of phenotypes in GWAS,’ 2017 Biology of Genomes, Cold Spring Harbor Laboratory.
  • Meyers-Wallen VN, Boyko AR, Danko CG, Grenier JK, Mezey JG, Hayward JJ, et al. (2017) XX Disorder of Sex Development is associated with an insertion on chromosome 9 and downregulation of RSPO1 in dogs (Canis lupus familiaris). PLoS ONE 12(10): e0186331.


Activities, interests and hobbies: 

  • MIT Addir Fellows Interfaith Program - Fellow
  • MIT Alumni Association – Tech Callers
  • Pakistani Students @ MIT – Vice President
  • MIT Multicultural Conference
  • Interfaith Youth Core Leadership Conference

Additional Degrees: 

Cornell University, Ph.D. in Computational Biology (Expected: 2020)