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Liu C. AI, Deep Learning and Generative AI Platforms

My name is Liu C. and I have over 1 year of experience in the tech industry. I specialize in the following technologies: Deep Learning, Artificial Intelligence, Computer Vision, Generative AI, Large Language Model, etc.. I hold a degree in Doctor of Philosophy (PhD), Master's degree. Some of the notable projects I've worked on include: Exceeding 95% Accuracy in Text Classification via DeBERTa Fine-Tuning, Boosting LLM Math Accuracy by 42% via Advanced Prompt Engineering, AI-Powered Video Generation & Editing from Sketches, Advanced AI for Photorealistic Image Editing. I am based in Hefei, China. I've successfully completed 4 projects while developing at Softaims.

I possess comprehensive technical expertise across the entire solution lifecycle, from user interfaces and information management to system architecture and deployment pipelines. This end-to-end perspective allows me to build solutions that are harmonious and efficient across all functional layers.

I excel at managing technical health and ensuring that every component of the system adheres to the highest standards of performance and security. Working at Softaims, I ensure that integration is seamless and the overall architecture is sound and well-defined.

My commitment is to taking full ownership of project delivery, moving quickly and decisively to resolve issues and deliver high-quality features that meet or exceed the client's commercial objectives.

Main technologies

  • AI, Deep Learning and Generative AI Platforms

    1 year

  • Deep Learning

    1 Year

  • Artificial Intelligence

    1 Year

  • Computer Vision

    1 Year

Additional skills

Direct hire

Potentially possible

Previous Company

USTC

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Experience Highlights

Exceeding 95% Accuracy in Text Classification via DeBERTa Fine-Tuning

With the explosion of LLM-generated content, ensuring text authenticity has become critical for anti-plagiarism applications. However, standard BERT models often fail, as simple fine-tuning leads to o

Boosting LLM Math Accuracy by 42% via Advanced Prompt Engineering

To overcome the notoriously poor mathematical reasoning of base LLMs, I engineered a two-stage solution to achieve near-perfect accuracy. First, by implementing an advanced Chain-of-Thought prompt arc

AI-Powered Video Generation & Editing from Sketches

Text-to-video models often lack precise control over object shapes and scene layouts. I developed a novel deep learning framework that empowers users to direct video generation and editing with simple

Advanced AI for Photorealistic Image Editing

Standard text-to-image AI often fails to capture fine-grained visual details. To solve this, I developed a novel deep learning system for precise, example-based image editing. Instead of text, users c

Education

  • University of Science and Technology of China

    Doctor of Philosophy (PhD) in Computer science

    2021-01-01-2026-01-01

  • University of Science and Technology of China

    Master's degree in Computer science

    2021-01-01-2023-01-01

Languages

  • English (Fluent)
  • Chinese (Native or Bilingual)