Emma Bigelow Email & Phone Number

- Over 35 clients served across a variety of technical areas to research scientific validity, conduct market research, plan and write NIH, NSF, and DoD SBIR grants. Client technologies span biomaterials, diagnostics, devices, and health IT products. Proposals have procured over $30M in funds. - Assessing biomedical technologies and companies as an NSF SBIR reviewer twice annually since 2018.- Providing SBIR office hours at Johns Hopkins Tech Ventures FastForward incubator for faculty and students. Over 35 start-up companies advised since 2016.

Developed strategies for stakeholders In medical technology innovation and commercialization

Baltimore, Maryland, United States

Baltimore, Md

- PhD candidate in the Cellular and Molecular Medicine program- Advisors: Elizabeth Jaffee, MD (Oncology), Suchi Saria, PhD (Computer Science – Machine Learning), Mark Yarchoan, MD (Oncology), Elana Fertig, PhD (Applied Mathematics and Oncology), Alexander Baras, MD, PhD (Oncology, Pathology Informatics)- Thesis title: Using machine learning methods to predict therapeutic response to check point inhibitor therapeutics.- Work entails the use of standard ML methods, as well as development of novel method to allow the use of extended feature sets beyond what is typically usable for a limited number of samples. Method is most applicable and beneficial in multi-omics datasets. Work primarily in Python.

Baltimore, Md

-Advised 14 undergraduate BME Design Teams developing a wide range of medical devices in collaboration with Johns Hopkins physicians. Technologies include catheter-based sensors, biopsy systems, microfluidic chips, and ophthalmic surgical tools. -Led a 2-week January Intersession course on technical business communications and medical market sizing.

Columbia, Md

- Technical Work and Product Launch: Invented and developed technology for the continuous, real-time detection of drugs and biomarkers in vivo. Managed R&D budget across multiple projects.-Grant Writing and Fundraising: Conceived of and composed 6 successful NIH SBIR grants delivering >$4M in non-dilutive research funding (Phases I and II). Recruited academic collaborators.-Business Development: Fostered academic collaborations (including with inventors of licensed patents) and managed sponsored research relationships. Identified and connected with key opinion leaders.-Market Research: Evaluated a wide range of preclinical and clinical applications to identify the most significant scientific or clinical needs that correspond with core technology advantages. Sized markets for applications with most compelling scientific justifications. Validated customer needs through communication with physicians, researchers, and key opinion leaders. Developed understanding of likely product regulatory pathway

Columbia, Md

Conducted prototyping, testing, and in vivo studies for client companies. Technologies include miniature PCR devices and capsule endoscopy technology.

Cambridge, Ma

I helped develop the microfluidic diagnostic MEDIKit at the Little Devices Lab at MIT. The purpose of the lab is to develop medical devices that can be built in and used at resource poor clinical settings, which requires creativity in both material and manufacturing technique choices. I used a number of different methods to create modular microfluidic blocks and their fluidic connections, such as integrating devices on to LEGO blocks, using 3D printed parts to create channels, molding silicone, and laser cutting acrylic. I helped demonstrate the microfluidic MEDIKit at NYC's 2011 Maker Faire, where we won Editor's Choice for the lab's whole set up. I also prepared kits of these devices to be presented at the Copper-Hewitt National Design Museum exhibit "Design with the Other 90%: CITIES". These MEDIKits also appeared in Popular Science's "Best of What's New - 2011" issue.

Ithaca, New York Area

I worked as a Spanish translator between social workers and immigrant farm workers who were participating in the TP3 program.

Doctor Of Philosophy - Phd, Oncology And Machine Learning

Thesis title: Using machine learning methods to predict response to immune check point inhibitors. Mentors: Elizabeth Jaffee MD, Suchi.

Bachelor Of Science (Bs), Biomedical Engineering

Graduated cum laude