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I am a dedicated computer scientist specializing in theoretical computer science and machine learning, currently pursuing my Master's degree at ETH Zurich. I have gained diverse experience through internships and research roles, focusing on enhancing the efficiency and performance of AI models, especially in computer vision and protein property prediction. I enjoy applying my skills to solve challenging problems and contribute to sustainable AI solutions. Throughout my academic and professional journey, I've developed strong expertise in software engineering, machine learning model optimization, and AI research. I am passionate about leveraging state-of-the-art technologies like PyTorch, numpy, Hugging Face, and Large Language Models to build innovative applications like AI chatbots and improve deep learning training efficiency. I look forward to advancing my career by combining theoretical knowledge with practical implementation in cutting-edge AI projects.…I am a dedicated computer scientist specializing in theoretical computer science and machine learning, currently pursuing my Master's degree at ETH Zurich. I have gained diverse experience through internships and research roles, focusing on enhancing the efficiency and performance of AI models, especially in computer vision and protein property prediction. I enjoy applying my skills to solve challenging problems and contribute to sustainable AI solutions. Throughout my academic and professional journey, I've developed strong expertise in software engineering, machine learning model optimization, and AI research. I am passionate about leveraging state-of-the-art technologies like PyTorch, numpy, Hugging Face, and Large Language Models to build innovative applications like AI chatbots and improve deep learning training efficiency. I look forward to advancing my career by combining theoretical knowledge with practical implementation in cutting-edge AI projects.

Lixuan Lang

Developer, AI Engineer, Data Scientist, +1

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I am a dedicated computer scientist specializing in theoretical computer science and machine learning, currently pursuing my Master's degree at ETH Zurich. I have gained diverse experience through internships and research roles, focusing on enhancing the efficiency and performance of AI models, especially in computer vision and protein property prediction. I enjoy applying my skills to solve challenging problems and contribute to sustainable AI solutions. Throughout my academic and professional journey, I've developed strong expertise in software engineering, machine learning model optimization, and AI research. I am passionate about leveraging state-of-the-art technologies like PyTorch, numpy, Hugging Face, and Large Language Models to build innovative applications like AI chatbots and improve deep learning training efficiency. I look forward to advancing my career by combining theoretical knowledge with practical implementation in cutting-edge AI projects.…I am a dedicated computer scientist specializing in theoretical computer science and machine learning, currently pursuing my Master's degree at ETH Zurich. I have gained diverse experience through internships and research roles, focusing on enhancing the efficiency and performance of AI models, especially in computer vision and protein property prediction. I enjoy applying my skills to solve challenging problems and contribute to sustainable AI solutions. Throughout my academic and professional journey, I've developed strong expertise in software engineering, machine learning model optimization, and AI research. I am passionate about leveraging state-of-the-art technologies like PyTorch, numpy, Hugging Face, and Large Language Models to build innovative applications like AI chatbots and improve deep learning training efficiency. I look forward to advancing my career by combining theoretical knowledge with practical implementation in cutting-edge AI projects.

Available to hire

I am a dedicated computer scientist specializing in theoretical computer science and machine learning, currently pursuing my Master’s degree at ETH Zurich. I have gained diverse experience through internships and research roles, focusing on enhancing the efficiency and performance of AI models, especially in computer vision and protein property prediction. I enjoy applying my skills to solve challenging problems and contribute to sustainable AI solutions.

Throughout my academic and professional journey, I’ve developed strong expertise in software engineering, machine learning model optimization, and AI research. I am passionate about leveraging state-of-the-art technologies like PyTorch, numpy, Hugging Face, and Large Language Models to build innovative applications like AI chatbots and improve deep learning training efficiency. I look forward to advancing my career by combining theoretical knowledge with practical implementation in cutting-edge AI projects.

Skills

Experience Level

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Advanced

Chinese

Advanced

Work Experience

Master thesis student at Disney Research Studio

November 30, 2024 - July 22, 2025

Enhanced training efficiency of large vision models by adaptively modifying batch and patch sizes; improved model convergence speed, and decreased energy consumption by 8%, contributing to sustainable AI practices. Reduced Autoencoder training time in Stable Diffusion by 50% and reduced training time of the SwinIR model for super-resolution tasks by 1.4x.

Research intern at Tencent AI Lab

April 30, 2021 - July 22, 2025

Implemented PointNet model to achieve a 15% improvement in protein quality assessment scores, aiding identification of misfolded proteins and improving structural refinement processes within the team. Conducted 30 experiments to optimize hyperparameters for protein pretraining models, leading to a consistent 5% improvement in protein property prediction across seven different datasets.

Software Engineer Intern at Flap.js

December 31, 2019 - July 22, 2025

Developed a React-based web app for constructing and analyzing formal languages and automata (DFA, NFA, PDA) in a team of 6 students. Incorporated automated optimization routines, such as state minimization, achieving a 20% reduction in computational complexity for automata analysis while maintaining functional equivalence. Deployed state linearization algorithm, minimizing memory usage by 20% during automata processing, optimizing resource allocation for complex language models and improving overall application performance.

Master thesis student at Disney Research Studio

November 30, 2024 - August 27, 2025

Enhanced training efficiency of large vision models by adaptively modifying batch and patch sizes, improving model convergence speed and reducing energy consumption by 8%, contributing to sustainable AI practices. Reduced Autoencoder training time in Stable Diffusion by 50% and decreased training time of the SwinIR model for super-resolution tasks by 1.4x.

Research intern at Tencent AI Lab

April 30, 2021 - August 27, 2025

Implemented PointNet model achieving 15% improvement in protein quality assessment scores, aiding identification and refinement of misfolded proteins. Conducted 30 experiments optimizing hyperparameters of protein pretraining models, resulting in a steady 5% prediction improvement across seven datasets.

Software Engineer Intern at Flap.js

December 31, 2019 - August 27, 2025

Developed a React-based web application for constructing and analyzing formal languages and automata (DFA, NFA, PDA) as part of a six-student team. Incorporated automated optimization routines such as state minimization, reducing computational complexity by 20% without losing functional equivalence. Deployed state linearization algorithm minimizing memory usage by 20% during automata processing, optimizing resources for complex language models and improving overall application performance.