Daniel Han
San Francisco, California,United States
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Daniel Han is a highly accomplished technologist and entrepreneur, best known as the co-founder and former Chief Technology Officer (CTO) of FiscalNote (NYSE: NOTE), a leading AI-driven enterprise SaaS company that delivers legal and regulatory data and insights. He played a crucial role in architecting and scaling FiscalNote's technology platform from its inception, leveraging artificial intelligence and machine learning to process vast amounts of governmental data. His expertise spans software engineering, product development, AI/ML, and leading high-performing technical teams. Daniel is recognized for his innovative contributions to the GovTech space and his entrepreneurial acumen in building a successful technology company.
Professional Summary
Daniel Han's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Notable Achievements
Co-founder & Former CTO of FiscalNote
Co-founded FiscalNote in 2013 and served as its Chief Technology Officer, leading the development and scaling of its core technology platform for global policy and market intelligence. He was instrumental in growing the company from a startup to a publicly traded entity on the NYSE.
Forbes 30 Under 30 - Law & Policy (2016)
Recognized by Forbes alongside co-founder Tim Hwang for their groundbreaking work at FiscalNote, using technology to make governmental information more accessible and actionable for organizations worldwide.
Pioneering AI in Legislative Tracking
Spearheaded the application of artificial intelligence and natural language processing to analyze and predict outcomes of legislative and regulatory activities, transforming how businesses and governments engage with policy.
Successful Public Listing (IPO)
As a key member of the founding team and CTO, contributed significantly to FiscalNote's journey towards its successful initial public offering (IPO) and listing on the New York Stock Exchange.
Educational Background
Bachelor of Data Science, Algorithms & AI
UNSW Australia - Year 2017
Bachelor of Laws and Actuarial Studies
UNSW - Year 2016
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Company Overview
Unsloth AIUnsloth AI is a company focused on significantly accelerating the fine-tuning process for Large Language Models (LLMs) while drastically reducing memory requirements. They provide open-source solutions that enable developers to fine-tune popular models like Llama, Mistral, and CodeLlama up to 2-5 times faster and use up to 70% less memory, often making it feasible on consumer-grade GPUs. Their technology primarily leverages optimized implementations of techniques like LoRA (Low-Rank Adaptation) and QLoRA, making advanced AI model customization more accessible and efficient for a wider range of users and applications.
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