Pedram Bakhtiarifard
PhD Fellow @ University of Copenhagen, ML Section
“The only difference is they tried. So can you.” — my mom
About Me
I’m a PhD Fellow in Machine Learning at the University of Copenhagen, working on continual learning, algorithmic complexity, and efficient ML as part of SAINTS Lab. My focus is building scalable AI systems that reduce compute and energy use while staying reliable and practical. Since 2022, I have led development of Carbontracker recognized by the European Commission’s Innovation Radar, which makes the energy and carbon footprint of training visible.
Earlier in industry, I worked as a software engineer at Danske Bank, co-leading the end-to-end design and deployment of their large-scale mortgage refinancing system. That experience taught me to approach ML systems with the same rigor as financial infrastructure: latency, cost, and reliability must be measured, not assumed.
Outside the lab, I speak and write about AI’s rising compute demands and sustainable approaches. I’ve shared these perspectives at Thoughts for Future, D3A Conference, TV2 News, and DR Radio, aiming to make complex technical issues clear to a broader audience.
What I’m Working On
Research
Investigating continual learning, generalisability, and algorithmic complexity, with a focus on developing methods that remain performant under compute and energy constraints.
Teaching
Developing and teaching with tools like CarbonTracker and EC-NAS, focusing on advanced ML courses and workshops that emphasize reproducibility and efficient systems.
Community
Sharing my work at Thoughts for Future, D3A, and PhD Summer Schools and in media including TV2 and DR, making the trade-offs of large-scale AI clear to broader audiences.
Key Publications
Moments in time
A collection of photos from conferences, media appearances, research milestones, and everyday moments that shape my journey.
