Resume
General Information
Full Name | Jack He |
jackhe313@ucla.edu | |
Mobile | 424-832-6703 |
Location | Los Angeles, CA 90024 |
Education
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2021.9 - 2025.6 Bacholar of Science, Computer Science | Applied Mathematics
University of California - Los Angeles - GPA: 3.92
- Honor: Dean's Honors List, 8th place in UCLA ACM-ICPC Algorithms Contest (Jan 2022)
- Core Courses: Machine Learning, Advanced Deep Learning & Neural Network, Computer Vision, Reinforcement Learning, Natural Language Processing, Data Structure, Algorithms, Linear Algebra, Optimization, Probability and Statistics
Research and Work Experience
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2024.3 - Pres Student Researcher
UCLA Prof. Bolei Zhou's Group - Applied large scale object extraction via GPT-4o, Grounded Dino, and Grounded SAM in real-world.
- Reproduced real-world object distribution in Embodied AI simulation platform, MetaUrban.
- Integrated MetaUrban into Nvidia's Isaac Lab, successfully transferring and optimizing digital-human assets.
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2023.3 - Pres Student Researcher
UCLA Computational Machine Learning Lab - Conducted analysis of data memorization in generative models (DDPM, GAN), focusing on the layer-wise distribution of memorization scores using Vision Transformers (ViTs) and Convolutional Neural Networks (CNNs) encoders.
- Developed a novel training-free fingerprinting method for identifying generative models' architecture, leveraging layer-wise memorization score distributions, achieving SOTA performance on model identification accuracy.
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2022.5 - 2022.8 Trip Budget Planning Web App
Software Product Sprint Participant, Google - Developed a trip budget planning web app using Java, JavaScript, and HTML/CSS, improving data storage efficiency by 30% with Google Cloud integration.
- Focused on backend development and coordinated with the front-end team to create functionalities for efficient storage of user, trip, event, and budget data, doubling the system's capacity and boosting performance by 90%.
Projects
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2024.1 - 2024.3 Text-Guided Image Editing Framework
- Developed an end-to-end image generation and editing framework using PyTorch.
- Introduced a training-free, text-guided semantic object segmentation method utilizing DiffEdit (Diffusion-based semantic image editing), BLIP, and other text-to-image models, achieving state-of-the-art capabilities.
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2024.2 - 2024.3 EEG Signal Classification Models Analysis
- Explored various architectures for EEG (Electroencephalography) signal analysis, including CNN, RNN, Transformers, and hybrid models to resolve the complex patterns of brain neural activities.
- Evaluated the impact of various hyperparameters and augmentation, improving classification accuracy by 15%.
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2024.1 - 2024.3 Fairness and Factuality of LLM
- Embarked on evaluating and enhancing the performance of Large Language Models in detecting fairness and factuality in textual claims, centered on Phi-2, Mistral-7B, and utilized GPT-3.5-Turbo for evidence generation.
Technical Skills
Programming Languages | Python, C/C++, Java, JavaScript, SQL, HTML/CSS, MATLAB, R. |
Frameworks & Libraries | PyTorch, TensorFlow, Keras, Scikit-learn, Pandas, NumPy, Node.js, React. |
Tools | Latex, Git, Shell, AWS, Docker, Google Cloud Platform, Azure. |