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๐Ÿ‡บ๐Ÿ‡ธ
University of Utah โ€” Salt Lake City, UT, USA Exchange Student(25.08.18~25.12.13)
๐Ÿ‡บ๐Ÿ‡ธ
University of Utah โ€” Salt Lake City, UT, USA Exchange Student(25.08.18~25.12.13)
  • Kahlert School of Computing, The University of Utah
  • Salt Lake City, Utah, United States

Highlights

  • Pro

Organizations

@UTAH-CS-ARCHIVE

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pxxguin/README.md

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Self-introduction

  • ๐ŸŽจ I'm a passionate Machine Learning Engineer with a strong background in data statistics.
  • ๐Ÿค– Deeply interested in LLM applications, currently studying about hallucination
  • ๐Ÿ›  Created various open-source libraries:
    • ThreatLens - An anomaly detection system built on the NSL-KDD dataset. Classifies network traffic into normal vs. abnormal (e.g., DDoS, scans), with model explainability (ELI5, Alibi) and Django-based web interface for real-time threat monitoring. ๐Ÿ“‘ Paper & ๐Ÿ“Š Poster
    • Autofic - A system that automatically detects security vulnerabilities in code, applies patches, and generates PR for seamless integration ๐Ÿ“‘ Paper & ๐Ÿ“Š Poster & ๐Ÿฅ‡ Award
  • ๐ŸŽ“ Undergraduate student majoring in Computer Science, specializing in Artificial Intelligence
    • University of Utah โ€” Salt Lake City, UT, USA Exchange Student, Computer Engineering (Aug 2025 โ€“ Dec 2025)
  • ๐Ÿ‘พ Programming is something I truly enjoy, and I'm always excited to create something new

Favorite techniques

  • ๐Ÿ“– Interested in Large Language Model optimization, with a focus on efficient fine-tuning (LoRA, PEFT) and hallucination reduction through retrieval-augmented generation.
  • ๐ŸŒ Passionate about multilingual NLP, especially in low-resource settings and cross-lingual transfer.
  • ๐Ÿ” Exploring explainability in NLP models, leveraging XAI techniques to make model decisions more transparent and trustworthy.

Algorithms

Solved.ac Profile

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  1. Development_of_an_Anomaly_Detection_System Development_of_an_Anomaly_Detection_System Public

    ThreatLens v2 is a cutting-edge project that combines data analysis and cybersecurity to detect and analyze abnormal access patterns in web logs

    Jupyter Notebook

  2. autofic-core autofic-core Public

    Forked from AutoFiC/autofic-core

    A solution for remediating vulnerable source code using LLMs

    Python

  3. UTAH-CS-ARCHIVE/cs3960-intro-ml UTAH-CS-ARCHIVE/cs3960-intro-ml Public

    This course is designed to provide a groundwork for both machine learning and deep learning early on in undergraduate studies.

    1

  4. UTAH-CS-ARCHIVE/cs6340-nlp UTAH-CS-ARCHIVE/cs6340-nlp Public

    This course surveys core algorithms and methods for building computational models of natural language understandingโ€”covering syntactic analysis, semantic representation, discourse, and statistical/โ€ฆ

    1

  5. UTAH-CS-ARCHIVE/cs6353-deep-learning UTAH-CS-ARCHIVE/cs6353-deep-learning Public

    This course focuses on modern, practical methods for deep learning with an emphasis on computer vision.

    1