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Rajinder Singh-Moon, Ph.D

Engineer | Scientist | Developer

About

Myself

Hello, I'm Raj, an engineer with a passion for data, machine learning, software development, and medical diagnostics. I currently work as the Director of Data Science at Modulim, a medical device start-up based in Irvine, California.

Interests

Machine Learning and Data Analytics

Software Development

Biomedical Optical Systems

Recent Publications

Quantification of irrigated lesion morphology using near‑infrared spectroscopy

Soo Young Park, Rajinder P Singh‑Moon, Haiqiu Yang, Deepak Saluja, Christine Hendon
Nature Scientific Reports, 2021
pdf

Steal syndrome from a superficial circumflex iliac perforator artery flap in a patient with a hypoplastic posterior tibial artery and severe diabetic peripheral artery disease

Grant A Murphy, Rajinder P Singh-Moon, Vincent Rowe, Ketan Patel, Amaan Mazhar, David Cuccia, David G Armstrong
Journal of Surgical Case Reports 2021
pdf

Quantifying dermal microcirculatory changes of neuropathic and neuroischemic diabetic foot ulcers using spatial frequency domain imaging: a shade of things to come?

Grant A Murphy, Rajinder P Singh-Moon, Amaan Mazhar, David J Cuccia, Vincent L Rowe, David G Armstrong
BMJ Open Diabetes Research and Care 2020
pdf

Education

Columbia University

Ph.D in Electrical Engineering, May 2019

Dissertation:

Design and development of optical reflectance spectroscopy and optical coherence tomography catheters for myocardial tissue characterization
New York University

B.Sc in Electrical Engineering, 2011

Experience

  • Modulim

    Director, Data Science

    • Led the establishment and growth of the data science team at a medical device startup, resulting in a 50% increase in operational efficiency and a 20% reduction in product development cycle time.
    • Developed and implemented a data-driven strategy to optimize manufacturing processes, resulting in a 15% reduction in defects and a 10% increase in product quality, leading to improved patient outcomes and increased customer satisfaction.
    • Spearheaded the development of machine learning algorithms and predictive models for patient monitoring, enabling early detection of critical events and reducing adverse events by 30%, while also improving the accuracy of diagnoses by 25%.

  • Modulim

    Senior Research & Development Scientist

    • Designed and developed deep learning models for solving light transport inverse problems, which lead to increases in accuracy (~30%) and computational speed (60-fold) when calculating imaging perfusion metrics
    • Designed and developed deep learning models for bypassing resource intensive step in data processing pipeline, enabling hardware simplifications and form-factor reductions, leading to a 25% reduction in device manufacturing cost
    • Designed and developed a web-based, cloud-supported, interactive dashboard with built-in data visualization and analytics to aid internal team and external customers in managing clinical programs and tracking progress
    • Experience writing design documents for newly proposed features to collaboratively define requirements and gain consensus across various business stakeholders
    • Mentored and supported junior engineers by leading daily standups and weekly R&D discussion groups to track progress

  • Modulim

    Research & Development Scientist

    • Designed and implemented image quality assessments in medical device software to reduce compromised data collection and improve data fidelity
    • Contributed to- and maintained Python image data handling library for internal and external (customer) consumption
    • Developed a Python tracking service for monitoring customer device utilization and pain points to inform marketing engagement strategies and billing. This tool dramatically decreased the customer management burden
    • Co-authored 2 peer-reviewed technical papers

  • SFIL, Columbia University

    Postdoctoral Research Scientist

    • Led cross-disciplinary pilot studies to validate optical imaging catheters in live animal subjects
    • Developed a graphical user interface with backend GPU processing for real-time acquisition and display of medical imaging data

  • SFIL, Columbia University

    Graduate Research Assistant

    • Co-authored 8 technical papers; traveled nationally and internationally to present research results.
    • Designed and fabricated optical imaging catheters and predictive models for enhancing ablation treatment of cardiac rhythm disorders
    • Co-developed a GPU-empowered, Monte-Carlo code for simulating light transport of optical catheter probes

  • Columbia University Medical Center

    Research Technician

    • Managed optical imaging systems for optimizing drug delivery to brain cancers in NIH funded research
    • Co-authored 5 technical papers; traveled nationally to present research results