cv

Education

  • 2018/08 - 2024/08

    Berkeley, CA, USA

    PhD
    University of California, Berkeley
    Electrical Engineering and Computer Science
  • 2014/09 - 2018/06

    Cambridge, MA, USA

    BS
    Massachusetts Institute of Technology
    Electrical Engineering and Computer Sciences

Work

  • 2024/08 - Present
    Postdoctoral Researcher
    University of California, Berkeley
    • Extended our non-contrast perfusion imaging method via multiplexing to accelerate acquisition. Demonstrated multi-slice imaging to map perfusion sources at multiple locations simultaneously.
    • Developed an approach to image slow cerebrospinal fluid (CSF) flow in the brain and presented findings at ISMRM 2025.
    • Devised a Python-based reconstruction algorithm to obtain high-fidelity images from shorter scan times.
  • 2023/06 - 2023/08
    Research Intern
    Merck
    • Performed gated lung micro-CT acquisitions on mice with various respiratory conditions.
    • Developed a reconstruction and analysis pipeline on the micro-CT data to extract biomarkers and assess the severity of disease.
  • 2018/08 - 2024/08
    Graduate Student Researcher
    University of California, Berkeley
    • Venous Perfusion Source Mapping:
      • Developed a non-contrast MRI method to map perfusion sources and slow-flow dynamics.
      • Implemented the research pulse sequence on the scanner.
      • Designed a CAD model for a flow phantom in Autodesk Fusion 360 and 3D-printed the design
      • Conducted flow-phantom and in-vivo volunteer studies to demonstrate the capabilities and versatility of the technique.
      • Validated sensitivity and specificity by designing controlled experiments and conducting in-vivo tests on volunteers.
      • Presented findings at ISMRM in 2020, 2022, 2023 and 2024.
    • Caterpillar Traps: Flexible Cable Traps for RF Coils in MRI Scanners:
      • Constructed a novel distributed cable-trap design for RF coils.
      • Performed finite element analysis for design validation and optimization using HFSS. Demonstrated robustness of design to bending with benchtop experiments. Achieved improved performance compared to commercial cable traps.
      • Presented findings at ISMRM in 2020 and 2021.
      • Mentored and trained three undergraduate students.
  • 2018/01 - 2018/02
    Research Intern
    Philips Healthcare
    • Designed a GUI in MATLAB for labeling lung ultrasound images to be used to train deep learning algorithms. Analyzed and labeled lung ultrasound images.
  • 2017/08 - 2018/07
    Undergraduate Researcher
    Research Laboratory of Electronics (RLE), MIT
    • Contributed to a research project aiming to diagnose patients with certain respiratory diseases using data obtained through capnography.
    • Restructured the model of the lung used previously in the project in order to capture certain characteristics of these pulmonary diseases. Implemented the revised model in MATLAB.
    • Assessed the success of the diagnosis using data from various patients. Presented findings at the 2018 IEEE EMBC conference.
  • 2017/06 - 2017/08
    Software Engineer Intern
    athenahealth
    • Coordinated with a team of software engineers and product managers working on automating the processing of fax documents in the electronic health record system.
    • Developed an efficient engine in Perl that categorized fax documents into templates in real time.
    • Designed and established an intuitive user interface using Javascript that allows a user to view and create rules for a template.
  • 2016/02 - 2016/12
    Undergraduate Researcher
    Graybiel Laboratory, McGovern Institute for Brain Research, MIT
    • Participated in a research project aimed to successfully record dopamine in the brain and improve the treatment for several brain disorders including Parkinson’s Disease.
    • Developed hardware that facilitates the recording of dopamine from 16 different channels.
    • Fabricated microelectrodes that are implantable in the brain for chronic dopamine recording.
    • Performed in-vivo surgeries on animals to test the capabilities of the fabricated microelectrodes for chronic dopamine recording.

Awards