What I am all about.
I'm Daniel Fan, an Applied Scientist and Senior Machine Learning Engineer with 10+ years of experience building AI systems that serve tens of thousands of users worldwide.
My expertise spans transformers, LLM fine-tuning, reinforcement learning, and NLP. I've trained and deployed custom large language models, published peer-reviewed research at IJCNN, and led teams to deliver both scientific innovation and production impact.
I hold a Master's degree in Electrical and Computer Engineering from Binghamton University. Outside of tech, I'm also a martial artist and magician.
Technical overview.
I'm passionate about technology, so I'm always excited to learn something new.
These are the things that I'm the most confident in, and the ones that I use the most professionally.
Batman would be jealous.
Training, fine-tuning, and deploying LLMs with LoRA/PEFT and quantization to serve 30,000+ users worldwide.
Building predictive analytics and anomaly detection systems that saved $800K annually and reduced downtime by 20%.
Published peer-reviewed papers at IJCNN on neural networks and transformer architectures for NLP tasks.
Where I've worked.
Swayable | Seattle, WA | 2022 - Present
Built and scaled ML training systems running thousands of models weekly. Designed LLM-powered moderation that cut costs by 50%.
Advanced Learning Ltd. (Writer's Toolbox) | Auckland, NZ | 2020 - 2025
Led transformer research and deployed 10+ custom LLMs serving 30,000+ users. Secured $500K in R&D funding.
Fonterra | Auckland, NZ | 2018 - 2020
Built predictive analytics saving $800K annually. Implemented anomaly detection reducing downtime by 20%.
Debatebot | Remote | 2017 - 2019
Processed 60M+ academic papers into Neo4j knowledge graph. Built research infrastructure for transformer experiments.
Research & papers.
Fan, H.-T.; Wang, W.; Jin, Z. (2017). Performance Optimization of Echo State Networks through Principal Neuron Reinforcement. IJCNN 2017, pp. 1717-1723.
Wang, W.; Fan, H.-T.; Jin, Z. (2017). Structure Optimization of Dynamic Reservoir Ensemble using Genetic Algorithm. IJCNN 2017, pp. 2193-2200.
Fan, D., Hunter, I., & Liu, B. (2024). Model and Algorithm Development for Paragraph Quality and Logic Assessment in Student Writing. Stage 2 Research Report, Advanced Learning Ltd.
Fan, H.-T. (2017). Evolution of Echo State Networks with Anti-Oja Plasticity Rules. M.S. Thesis, Binghamton University.
Where I studied.
Binghamton University (SUNY) | Binghamton, NY | 2017
Thesis: Evolution of Echo State Networks with Anti-Oja Plasticity Rules. Research focus on neural network optimization and reservoir computing.
Things I've built.
Contact me.