NSF-supported analysis postdoc for the MIGDAL collaboration–a rare event search experiment aiming to observe the Migdal Effect in nuclear scattering. Some accomplishments in my first 4 months in this role include:-Pitching the idea of, and subsequently developing a YOLOv8-based real-time object detection pipeline for quickly and efficiently processing and analyzing up to 200 high resolution resolution images per second on a single consumer-grade PC. This pipeline automates the analysis of 1PB of image data per month, digesting to ~30GB of summary data that are useful for both for searches for the MIGDAL effect and for other physics applications.-Integrating this pipeline into the MIGDAL experiment's existing data acquisition software to ensure that the data is processed and analyzed as it's being recorded.-Developing user-facing real time data quality monitoring tools centered around this pipeline's analysis that provide instant feedback to detector operators, such as observed rates of various particle species, and real time energy calibrations.-Analyzing all unblinded image data recorded to date to compile Migdal Effect candidates for our collaboration that are currently being analyzed in detail.

Researches and applies deep learning-based computer vision techniques to improve particle identification and directional sensitivity in gaseous time projection chambers.

Primarily researched directional-neutral particle detection with detectors called gaseous time projectionchambers (TPCs). This work is applicable both for directionally pinpointing neutral particle production atparticle accelerators, and for directional dark matter detector R&D.● Administered the design, development, construction, and implementation of a system of TPCs atthe SuperKEKB collider experiment in Tsukuba, Japan.● Oversaw all aspects of this system including remote operation, data collection, automated dataprocessing pipeline construction, and analyses that were featured in four journal publications.● Utilized deep learning (convolutional neural networks) in the analysis of 3D images recorded byTPCs to achieve world-leading particle identification and directional sensitivity performance.● Standardized QA and QC procedures for constructing and testing components of the TPC systemand developed training manuals for system operation and maintenance.● Created and maintained front-end GUI displays for real-time monitoring of key quantities fromover 15 detector systems present at the SuperKEKB particle accelerator.● Presented research at over 10 meetings and conferences and invited to give pedagogical talks toundergraduates, graduate students, and postdocs at two Belle II Summer School workshops.

Responsible for teaching a total of nine introductory physics lab sessions, three introductory physicsrecitation sessions, and four senior-level quantum mechanics (QM) recitation sessions.● Elected as Head TA responsible for mentoring all physics TAs teaching introductory courses.● Developed all teaching materials used in the quantum mechanics recitation sessions.● Introduced computer-based tutorials to facilitate conceptual understanding of QM processes.● Awarded an Outstanding Physics TA prize.● Twice-nominated for the University-wide outstanding undergraduate teaching award.

Founding Physics Teacher focused on delivering the principles of inquiry, equity, inclusion, and effectiveassessment through interactive and engaging lessons with data-driven assessment.● Developed physics curriculum adhering to New York State Physics Core curriculum guidelines.● Established both the school’s AP Physics program and the school’s physics lab.