PHD RESEARCHER | AI ENGINEER
Tavis Shore
Visual Navigation Engineer
GREAT
EXPERIENCE
My extensive experience in the field is a testament to how my knowledge and priorities have developed. From working as a data scientist in defence, to co-founding an AIoT startup - I always target complex, high-impact challenges.
AUTONOMY
I excel in my work with a strong sense of autonomy, making me a self-reliant and efficient engineer. My ability to take initiative and drive projects forward independently has consistently proven to be a valuable asset in delivering successful outcomes.
INVOLVEMENT
I actively engage in every aspect of the development process, fostering collaboration and synergy within teams. My dedication to active involvement ensures I contribute effectively to projects, creating efficient solutions.
Developed proficiency across 5 years of experience including a Master’s and PhD, with a strong focus on machine learning and autonomous systems. Published multiple peer-reviewed papers in top-tier venues, combining theoretical insight with practical application across academic and industrial contexts.
Since starting my PhD, I have gained practical experience in computer vision - developing and testing novel algorithms feature extraction and aggregation, as well as scene reconstructions, supported by publications demonstrating applied research and technical rigor.
I have extensive Python experience accumulated across my Bachelor’s, Master’s, and PhD studies, as well as professional work. This includes writing scalable code for data analysis, machine learning pipelines, and automation, with a strong focus on clean, efficient, and reproducible programming.
From undergraduate studies to co-founding a startup, where I developed embedded software for sensor data acquisition and transmission, focusing on performance and low-level hardware interaction.
Developed proficiency across 5 years of experience including a Master’s and PhD, with a strong focus on machine learning and autonomous systems. Published multiple peer-reviewed papers in top-tier venues, combining theoretical insight with practical application across academic and industrial contexts.
Since starting my PhD, I have gained practical experience in computer vision - developing and testing novel algorithms feature extraction and aggregation, as well as scene reconstructions, supported by publications demonstrating applied research and technical rigor.
I have extensive Python experience accumulated across my Bachelor’s, Master’s, and PhD studies, as well as professional work. This includes writing scalable code for data analysis, machine learning pipelines, and automation, with a strong focus on clean, efficient, and reproducible programming.
From undergraduate studies to co-founding a startup, where I developed embedded software for sensor data acquisition and transmission, focusing on performance and low-level hardware interaction.