As the Vice President of Research and Development (VP R&D) at Moberg Analytics, I lead all aspects of product development engineering. My role involves managing the software design and deployment for our innovative medical devices. With a diverse skill set, I excel in program and project management, ensuring efficient execution. I possess a deep understanding of relevant regulations and compliance, including 21 CFR and ISO, guiding our products to meet industry standards.My responsibilities extend beyond technical aspects, as I focus on developing effective research strategies and maintaining clear communication with stakeholders. I drive initiatives to restructure design control and risk management processes, upgrade product lines, and develop new technologies while optimizing costs and enhancing product quality.Collaboration is key in my role, as I oversee interactions with project teams, partners, and subcontractors. Working closely with R&D operations, facilities, and project management teams, I define clear project objectives, manage variances, and develop timelines to ensure timely delivery of all projects. Guiding the team to meet deliverables and objectives, I am dedicated to advancing Moberg Analytics' mission of helping brain injured patients with advanced technology and AI.

In this role, I was responsible for managing the top-level product and technology direction of our data management system for neurocritical care.

As a project manager, I was responsible for the oversight of a small team of software engineers working on our clinical trial data management system for brain-injured patients. My work involved implementing agile project management with Atlassian tools such as Jira and Confluence. I continued my previous software engineering role in parallel, mainly focusing on production-level web-based software deployments on IBM Cloud.

A clinical informatics engineer works with clinicians to develop relevant algorithms for managing and understanding patient outcomes and states. In this role, I worked with top neurointensivits to implement the necessary tools and architecture for executing well-known methods in the field. These specifically include measures of cerebral autoregulation such as the pressure-reactivity index and optimal cerebral perfusion pressure. Additionally, I explored physiological time-series crisis prediction using machine learning. See Projects section to read more: "A Multimodal Monitoring Approach to Predicting the Onset of Physiological Incidents Using Machine Learning" for more details.

Since November 2019, I have been working at Zhou Lab with Dr. Wanding Zhou and other lab members. Located at the Colket Translational Research Building, Zhou Lab focuses on epigenetic research and genomic data science. I worked directly with Dr. Zhou and a few other lab members to reconstruct the epigenetic differentiation of human cell lineages using machine learning algorithms. Specifically, I led the development of an R software package for tools related to this research that will hopefully be released publically through Bioconductor. My previous personal project in his lab was concerned with bisulfite-seq sequence mapping algorithms. See Project section for more information on these two research projects: "DNA methylation-based machine learning of developmental biology and epigenetic cell identity" and "A Base-3 Index for Bisulfate Sequence Mapping Algorithms."Since joining Zhou Lab during my first term at Drexel, I have collaborated with Dr. Zhou and other lab members in various areas of epigenetic research. As a result, I have gained both relevant and valuable experience in the C and R programming languages. Furthermore, I have worked with different debugging tools for C, such as Valgrind and GDB. Through researching remotely at Zhou Lab, I have learned how to manage and utilize the High-Performance Computing (HPC) Linux-based servers at CHOP. This opportunity has also provided me with both professional and collaborative team experience through working with others in the lab.

The Vertically Integrated Projects (VIP) program is focused on long term design projects involving interdisciplinary students from across the university. Undergraduate students who join VIP teams will earn academic credit for their participation in design/discovery efforts that assist faculty and graduate students with research and development issues in their areas of expertise. As a VIP team member, I worked with Dr. Anup Kumar Das in areas of neuromorphic computing. Through this experience, I became familiar with Python and many of its libraries related to machine learning such as support vector machines, random forest, convolution neural networks, recurrent neural networks, and long-short term memory networks. See Projects section to read more about the two research projects I took on during this program: "Neuromorphic Approaches to DNA Subsequence and Restriction Site Analysis" and "Motif Identification using Convolution-Neural Network-based Pairwise Subsequence Alignment Score Prediction."

The STAR Scholars Program is a competitive research program that allows first-year students to participate in faculty-mentored research, scholarship, or creative work during the summer after their freshman year. The program provides an opportunity for students to get to know faculty, explore a major area of research, and gain practical skills and valuable research experience. It is designed to bring the brightest and most forward-thinking minds at Drexel together to independently develop novel research and creative ideas.During this summer program, I explored protein structure prediction using machine learning algorithms. See Project section to learn more: "Measuring Protein Structure Deviation using Machine Learning."

While holding this position, I contributed to the 2017 Secondary Payload Project for NASA's Total Solar Eclipse Event through Montgomery County Community College (MCCC) and Temple University's College of Engineering. I met with several other students and a few teaching instructors (including a professor from the community college) weekly in order to research, design, and build different aspects of the payload device.