Welcome!

I am Mohammadreza Rostam, a PhD candidate in Control Engineering at the University of British Columbia, where I research at the Control Engineering Laboratory. My research focuses on creating smart control algorithms that enhance the efficiency of mechatronic systems, particularly those dealing with unknown disturbances with quasi-periodic patterns. I am presently conducting doctoral research on a novel control system that merges the model predictive control approach with Gaussian process machine learning technology.  

I work as an Applied Scientist at Amazon, where I develop and optimize Large Language Models (LLMs) and Machine Learning (ML) models to improve Alexa’s capabilities and user experience. Previously, I served as a Senior Deep Learning Researcher and Developer at Picovoice, specializing in cutting-edge speech and language technologies.

My technical expertise spans a wide range of domains, including:

• Deep Learning Architectures: RNNs, CNNs, Transformers, GANs
• LLMs: Development, fine-tuning, and application of LLMs (including RAG) for tasks such as text generation and question-answering.
• GPU Optimization: CUDA programming
• NLP on Resource-Limited Devices
• Time-Series Forecasting
• Control Theory: Adaptive, robust, nonlinear, optimal
• Optimization & Model Predictive Control
• Signal Processing
• Embedded Systems & Firmware Development

Previous Experience

Before starting my PhD, I gained experience as an embedded software/mechatronic engineer in multiple small startups. During this time, I honed my programming skills for Bare-Metal, RTOS, and Linux systems, focusing on firmware development and working extensively with various sensor types.