Tianhui (Hilda) Zou
Fine-tuning Thesis Work - Generative AI for Automating Software Uplifts
Experience
Fine-tuning Thesis Work - Generative AI for Automating Software Uplifts
Ericsson
- Explored state-of-the-art Generative AI techniques, mining selected GitHub repositories with all versions from the last 3 years.
- Built and maintained a cleaned dataset of 1M+ for LLM fine-tuning to detect breaking changes from third-party library updates.
- Fine-tuned CodeT5+ and Code Llama with the QLoRA method, achieving an F1-score above 95%, highlighting GenAI’s potential in software upgrades.
Reinforcement Learning – Lunar Lander
KTH Royal Institute of Technology
- Implemented Deep Q-Learning with a replay buffer and target networks.
- Optimized hyperparameters (discount factor, buffer size, learning rate), improving average reward to 200+ after ~350 episodes.
- Evaluated training curves, showing DQN outperforming the random agent.
Parallel Sobel Filtering for Fast Image Processing
KTH Royal Institute of Technology
- Implemented image preprocessing and matrix transformation in Python.
- Designed and parallelized the Sobel filter in C with MPI on Dardel (the top supercomputer), employing red-black communication to avoid deadlocks.
- Achieved strong parallel efficiency and near-linear speed-up up to 128 processors on 150k+ pixel images.
Industries Experience
See where this freelancer has spent most of their professional time. Longer bars indicate deeper hands-on experience, while shorter ones reflect targeted or project-based work.
Experienced in Telecommunication (0.5 years) and Education (0.5 years).
Business Areas Experience
The graph below provides a cumulative view of the freelancer's experience across multiple business areas, calculated from completed and active engagements. It highlights the areas where the freelancer has most frequently contributed to planning, execution, and delivery of business outcomes.
Experienced in Information Technology (1 year) and Research and Development (1 year).
Summary
Applied & Computational Mathematics graduate with expertise in Python, Machine Learning, and Generative AI. Experienced in fine-tuning LLMs and building large-scale datasets. Skilled in data preprocessing, feature engineering, and evaluation, with hands-on experience in ML pipelines and real-world projects.
Skills
Programming: Python (Pandas, Numpy), Sql (Bigquery, Mysql), R, Matlab
Ml Techniques: Fine-tuning, Hyperparameter Optimization, Model Evaluation
Tools & Platforms: Git, Jupyter, Google Colab, Fastapi, Databricks, Kubernetes
Visualization: Tableau, Matplotlib
Adaptability
Communication
Persistence
Teamwork
Languages
Education
KTH Royal Institute of Technology
Master of Applied and Computational Mathematics · Applied and Computational Mathematics · Stockholm, Sweden
University of Science and Technology Beijing
Bachelor of Mathematics and Applied Mathematics · Mathematics and Applied Mathematics · Beijing, China
Profile
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