May 2024 – Aug 2024 · 3 mos · On-site

• Developed extensive simulation suite for laser under optical injection conditions achieving over 50x speedup over RK4 method
• Developed fiber-optics simulation to model dispersion and modulation effects in optical fibers
• Setup experiment to generate ultrafast pulses (<50ps) using electrical pulse generators and optical amplitude modulation
• Setup cascaded non-linear optical experiments – injection locking, SHG, PSA etc. both in-fiber and free space achieving conversion efficiencies of up to 90%

May 2023 – May 2024 · 1 yr · Toronto, Ontario, Canada · Hybrid

• Developed Firmware for PCIe and Ethernet IPs focusing on implementations of Transceiver Calibrations and Adaptations
• Automated code generation in calibration and verification pipelines providing up to 25x speedup over manual update and maintenance methods
• Implemented DSP algorithms providing 10 times improvement in Bit Error Rates on Ethernet IPs by improving on existing calibration methods
• Collaborated with large teams for hardware development by efficiently utilising project management software like JIRA, Confluence and Perforce

Sep 2022 – Mar 2023 · 6 mos · Toronto, Ontario, Canada · Remote

• Project Title: Tracking Covert Spatial Attention using Linear and Non-linear Perceptrons
• Developed data processing pipelines for raw EEG data analysis and filtering in MATLAB and Python
• Designed parallel training pipeline for approx. 200 temporally resolved models to provide a 5 times computational speed up
• Predicted onset of visual attention from complex EEG data using small Perceptrons (<300 parameters) within 95% timing accuracy

Jun 2022 – Aug 2022 · 2 mos · Toronto, Ontario, Canada

• Led a small team of volunteers to organize and manage a two-day electronics workshop - ElecTRiC - for high school students
• Designed analog, digital and mechanical circuits and projects to teach at the workshop
• Taught introductory level analog and digital electronics at workshop
• Improved communication and leadership skills

Jun 2021 – Dec 2021 · 6 mos · University of Toronto

• Built simulations to run and collect benchmarking data for 18 optimization algorithms over 10 experiment planning datasets
• Performed regret calculations on benchmarking data and sensitivity analysis of datasets.
• Benchmarked algorithms using Bayesian Neural Networks as experiment emulators
• Presented research findings at National Conference on Undergraduate Research, 2022
• Gained machine learning, TensorFlow and SciPy experience