Waterloo, Ontario, Canada
Postdoctoral Fellow in Systems Design Engineering, University of Waterloo 49 peer-reviewed publications, 9 first-authored, 28 SJR Q1. Research interests: Environmental Monitoring, GeoAI, Geospatial Data Analysis, remote sensing, GIS, 3D computer vision, foundational models, large language models, vision language models. Teaching Experience: Sessional lecturer, University of Waterloo.
AI research, focusing on 3D computer vision and large language models applied to remote sensing and geographic information systems.
*Secured major research funding through successful MITACS and assisted NSERC-DG grant applications. *Led collaborations resulting in 30+ peer-reviewed publications, advancing interdisciplinary research.
Course taught: GEOG316/PLAN351 Fall 2024 • Modified and adapted lectures, coursework, and assignments, and developed a new set of exams. • Offered expertise in active research areas of remote sensing and the application of multivariate sta- tistical methods. • Guided students in developing a thorough understanding of statistical methods in geography, remote sensing, and GIS through discussions and office hours.
• Studied beam-beam resonances of the Large Hadron Collider using Lie algebra methods. • Derived and implemented new algorithms to predict resonances based on particle bunch dynamics. • Derived a new resonance reduction condition based on relative bunch phasing
• Demonstrated quantum hall effects in low temperature experiments on Canada’s domestically pro- duced electron dot quantum computing chips. • Maintained sensitive low temperature equipment and quantum computing chips
• Developed algorithm modeling electron beams in TRIUMF’s Electron Linear Accelerator. • Implemented algorithm which minimizes beam orbit deviation.
• Performed Monte Carlo simulations modelling irradiation of human bodies • Researched and applied statistical methods to reduce variance in Monte Carlo N-Particle (MCNP) simulations increasing performance by an order of magnitude. • Implemented parallelization of MCNP software on computing cluster.