RYAN LU

about me · experience · projects · blog · photos

Research Experience

Johns Hopkins University, Zhang Lab (February 2019 - August 2021)

  • Studied nonlinear theoretical mechanisms for graded persistent activity in neurons by developing computational models with Hodgkin-Huxley-like dynamics
  • Developed an anatomically accurate network model for the head direction circuit

Johns Hopkins University, Stevens Lab (August 2019 - August 2021)

  • Developed supervised machine learning algorithms for predicting delirium in ICU patients

Johns Hopkins University, NeuroData Lab (August 2019 - May 2020)

  • Developed brainlit, a Python software package for analyzing large 3D brain volumes
  • Merged a pull request into scikit-image, a popular open source image processing Python libraries with a million monthly downloads

Johns Hopkins University, Sgouros Lab (Summer 2019)

  • Developed a MATLAB tool to segment automatically images of cell spheroids and to detect spheroid fragmentation

Johns Hopkins University, Department of Pathology (January 2018 - May 2020)

  • Conduct research under Dr. Zahra Maleki to study efficacy of various reporting systems for diagnosing cancers in upper neck
  • Published paper on the Milan System for Submandibular Gland Cytopathology
  • Abstract "Risk Stratification of Thyroid Nodules Suspicious for Medullary Thyroid Carcinoma and the Bethesda System for Reporting Thyroid Cytopathology" accepted to the USCAP 109th Annual Meeting

Johns Hopkins University, Pasricha Lab (September 2017 - September 2018)

  • Computationally modeled the effects of extracellular electrical stimulation on dorsal root ganglion neurons using NEURON and Python
  • Explored different factors that influence neural responses to high frequency stimulation

UC Davis, Yamada Lab (Summer 2017)

  • Led a project to create an inducible CRISPR/Cas9 system

Work Experience

GridBright, Software Engineering Intern (Summer 2023)

  • Developed a data analysis pipeline with a GUI using Python and MySQL

Nevro, Preclinical Computational Research Intern (Summer 2018)

  • Created realistic morphological models of neurons from the dorsal horn and computationally modeled their passive and active responses to extracellular stimulation

Johns Hopkins University, Barclay Summer STEM Academy Teaching Assistant (Summer 2019)

  • Managed class of 25 middle schoolers enrolled in a free, three-week summer STEM enrichment program organized by the Johns Hopkins Whiting School Center for Educational Outreach

Johns Hopkins University, Head Course Assistant (Fall 2019 - Spring 2020)

  • Head Course Assistant for Intermediate Programming, a core required CS course covering intermediate to advanced programming, including object oriented programming, in C and C++
  • Managed team of 13 course assistants for over 100 students
  • Designed autograder tests and grading rubrics for coding assignments
  • Ran review sessions, graded assignments, held office hours, and provided guidance and mentorship to students

Johns Hopkins University, Teaching Assistant (Fall 2019)

  • Teaching Assistant for Computational Medicine: Cardiology, a core required BME course on quantitative models of the cardiovascular system, with a focus on cardiac electrophysiology, mechanics, and hemodynamics.
  • Graded assignments/exams and held weekly recitation sessions and office hours
  • Awarded the David T. Yue Memorial Award for outstanding teaching by an undergraduate teaching assistant

Education

Northwestern University Feinberg School of Medicine - G2

MD/PhD Candidate


Johns Hopkins University - Class of 2020

Bachelor of Science in Biomedical Engineering with Departmental Honors, Focus Area: Biomedical Data Science

GPA: 4.00

Honors: Richard J. Johns Award for outstanding achievement in Biomedical Engineering, Tau Beta Pi National Engineering Honor Society, Alpha Eta Beta Mu National Biomedical Engineering Honor Society, Omicron Delta Kappa National Leadership Honor Society


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