• Managing the generation of an Investigational New Drug (IND) application for submission to the FDA by working closely with lead investigators, regulatory groups at the trial site, FDA, CROs and CMOs.• Successfully submitted a Type D meeting package to the FDA to receive further feedback on the clinical trial protocol for the Phase I clinical trial of the nerve contrast agent.• Developing a clinical trial protocol designed to ensure patient safety and determine a minimum dose for useful nerve visualization by surgeons all within the context of an effective commercialization strategy upon FDA approval.• Demonstrates project management skills for on-schedule progress towards IND approval and clinical trial initiation.• Leading a conference outreach program within the company to interface with key opinion leaders in the field to identify intraoperative imaging needs.

Developed novel computational approaches to process and analyze spatial transcriptomic datasets in support of R&D efforts for next generation hardware and software product development while providing computational support to the assay team.• Generated a colocalization analysis pipeline which was deployed as a method to increase the sensitivity and accuracy of the assay by improving analysis of z-stack image data.• Built a high-throughput analysis pipeline to provide quantitative feedback for assay development experiments to improve future experimental designs.• Leveraged experiences in wet-lab biomedical research and as a computational biologist to provide deep insight of the biological interpretation of analysis results.• Optimized image processing pipelines to maximize the accuracy of processed data.• Worked in a cross-functional role to increase collaboration between the assay and software teams resulting in increased rate of platform advancement.

Managed and advanced a cyclic immunofluorescence imaging platform to generate and analyze highly multiplexed, spatial proteomic datasets of a broad spectrum of cancer types.• Coordinated and ran cyclic immunofluorescence imaging studies for highly multiplexed, spatial proteomic characterization of human tumors and their microenvironments.• Analyzed highly multiplexed image datasets with custom Python and MATLAB scripts as well as with software-based image analysis tools.• Validated and established antibody panels to simultaneously characterize human tumor functionality, the immune landscape pre- and post-therapy, and assess the context of the tumor microenvironment.• Generated and presented reports to communicate cyclic immunofluorescence results to collaborators and at research tumor board meetings.• Managed a team, both in-person and remotely, to coordinate day-to-day wet- and dry-lab priority tasks as well as establish alterations to SOPs to optimize platform throughput.• Maintained accurate and organized documentation of all samples and experiments to track the data collected.

Developed a novel fluorescence imaging technology capable of in situ quantification of cancer drug target engagement and cellular proteomic response on a single tissue section with nanometer resolution.• Established and validated a methodology for highly multiplexed immunofluorescence imaging for quantification of protein expression at the single-cell level. • Applied DOE principles to develop and optimize a methodology for systemic administration of fluorescently labeled drugs to tumor bearing mice for quantification of drug target engagement through ex vivo tumor imaging. • Integrated drug target engagement and proteomic tissue section image datasets with custom spatial registration MATLAB scripts.• Performed cell segmentation of tissue section imaging data with a Python-based toolkit to generate high dimensional datasets with single-cell resolution.• Maintained accurate and organized documentation of all experiments to track the data collected.

Performed tissue imaging and software-based image analysis to quantify disease pathology.• Performed both brightfield and fluorescent imaging of tissue samples on a variety of equipment setups.• Independently designed and executed image analysis plans based on tissue, disease, and image type.• Worked on DOD, NIH, and ACS funded projects.• Managed and analyzed raw data sets in Microsoft Access to extract the primary endpoint data.• Collaboratively communicated with both academic professionals and companies to complete projects on time.• Exhibited project management skills by coordinating multiple projects and prioritizing tasks.

Led a project to develop high sensitivity imaging of cancer spread in lymph nodes using fluorescent imaging agents.• Prepared and tested novel fluorescent imaging agents to determine sensitivity prior to animal experiments.• Independently performed small animal imaging experiments to assess imaging agent uptake into lymph nodes.• Designed MATLAB scripts to quantitatively evaluate the imaging agent delivery to the lymph node.