Intern at Molecular Forecaster with MITACS Accelerate Fellowship working on AI/ML solutions

TEACHING PROGRAMMING, DEEP LEARNING, AND CHEMISTRY • Teaching assistant for Intro to Phys Chem 2 and Phys Chem for Biological Sciences, lead labs and tutorials. Created intro lesson for Python• Assisted in teaching for McMedHacks, an 8-week-long program that aims to teach students and researchers fundamentals of medical image analysisand deep learning in Python

Machine Learning for Computational Chemistry: Started as a Graduate researcher in October 2021, before formally starting my MSc Dec 2021. • Alongside Dr. Nicolas Moistessier, developing ML tool for computer-aided drug design distributed by Molecular Forecaster company• Implementing deep learning for ligand-protein pose estimation• ML for CYP activity prediction enhanced by docking software• Focus on combining ML/DL algorithms and chemical knowledge to achieve practical, accurate results which can be applied to the drug designprocess

Physics Research, Computational Simulation and Analysis:• Created and simulated proposed method to determine coprecipitation yield by Alpha counting. Computational analysis and simulation was suc-cessful giving constants and distributions essential for execution of method• Used mathematical and computational techniques to determine the alpha energy spectrum expected for our sample allowing for a novel alphacounting method

Physics/Chemistry Research, Accelerated Mass Spectrometry:• Alongside research associate Dr. Carlos Vivo-Vilches, developed novel method for assay of ultra trace amounts of radioactive nuclides using accel-erated mass spectrometry• Created chemical procedure for material digestion and AMS target fabrication• Installed, tested and used new expensive and complex microwave digestion system• Work was presented by Dr. Razvan Gornea at the McDonald Institute National Meeting

Physics Research, Experimental Particle Physics: • Alongside professor Dr. Gornea Razvan, researched, designed, and performed a novel experiment under EXO-200 to observe the range of a lowenergy electron• Developed a complete model and software to predict experimental results• Tested and assessed feasibility and accuracy of using various metals for thin layer vacuum evaporation depositions• Constructed modifications to vacuum chamber, as well as developed an apparatus to stabilize a delicate LED while ensuring it remained boththermodynamic and electrostatically stable allowing for much increased durability of the experiment