Xuechen Liang | Computer Science | Research Excellence Award

Mr. Xuechen Liang | Computer Science | Research Excellence Award

Master | East China Jiaotong University | China

Mr. Xuechen Liang is a computer science researcher focused on large language models, multi-agent systems, and intelligent analysis in imperfect information settings. His research addresses commentary generation, strategic reasoning, and agent collaboration, with notable contributions to top-tier venues such as IJCAI, EACL, AAAI, and IEEE Access. His work spans personalized role-playing frameworks, self-evolving and memory-augmented agents, psycholinguistically inspired token reduction, and collaborative tuning methods to enhance model efficiency and performance. His scholarly output includes 7 research documents, receiving 8 citations, and reflects an h-index of 2, demonstrating growing academic impact in advanced AI and language model research.

Citation Metrics (Scopus)

10

8

6

4

2

0

Citations
8

Documents
7

h-index
2

Citations

Documents

h-index

Featured Publications

Self-Evolving Agents with Reflective Memory for Complex Decision Tasks

– arXiv Preprint, 2024

Amreen Shafique | Software Engineering | Best Researcher Award

Dr. Amreen Shafique | Software Engineering | Best Researcher Award

Phd Scholar at Dalian University of Technology, China

Amreen Shafique is a dedicated Ph.D. scholar in Software Engineering at Dalian University of Technology, China. She has a strong academic background in computer science, complemented by practical teaching experience and a growing publication record in artificial intelligence and cybersecurity. Passionate about research and innovation, she aims to contribute to cutting-edge technologies such as Explainable AI, deep learning, and software-defined networking. Her analytical mindset, programming skills, and commitment to academic excellence define her professional identity.

Publication Profile 

Scopus

Educational Background 🎓

  • Doctor of Philosophy (Ph.D.) in Software Engineering
    Dalian University of Technology, China
    2022 – Ongoing

  • Master of Science (MS) in Computer Science
    Mohi-ud-din Islamic University, Azad Kashmir, Pakistan
    2016 – 2018
    CGPA: 3.16 / 4.00

  • Bachelor of Science (BS) in Computer Science
    The University of Azad Jammu and Kashmir, Pakistan
    2007 – 2011
    CGPA: 2.72 / 4.00

Professional Experience 💼

  • Lecturer, Computer Science
    University of Kotli, Azad Kashmir, Pakistan
    2018 – 2022
    Delivered undergraduate courses, guided student projects, and participated in curriculum development.

  • Lecturer, Computer Science
    Leads Group of Colleges, Azad Kashmir, Pakistan
    2014 – 2018
    Engaged in teaching foundational and advanced computer science subjects.

Research Interests 🔬

  • Explainable Artificial Intelligence (XAI)

  • Cyber Security

  • Wireless Networking and Security

  • Deep Learning Enabled Robotics and Automation

  • Software Defined Networking (SDN)

  • Advanced Neural Networks

  • Generative Models

Strengths and Technical Skills

  • Technical and Research Writing (English)

  • Critical Analysis of Literature

  • Data Analytics

  • Programming Languages: MATLAB, Python, Java

Conclusion🌟

Amreen Shafique is an emerging researcher with a strong vision for integrating ethical AI, cybersecurity, and intelligent automation into real-world solutions. Her commitment to academic growth, combined with hands-on teaching and research experience, positions her as a valuable contributor to any forward-thinking research team or academic institution. She seeks opportunities that will foster collaboration, innovation, and impactful scientific contributions.

Publications 📚

1️⃣ AI Models and Ethical Considerations in Research

🧠📜 This publication explores the integration of ethical frameworks in the development and deployment of artificial intelligence models, emphasizing transparency, bias mitigation, and responsible innovation.


2️⃣ PypiGuard: A Novel Meta-Learning Approach for Enhanced Malicious Package Detection in PyPI Through Static-Dynamic Feature Fusion

This research presents PypiGuard, a cutting-edge hybrid model that combines static and dynamic analysis techniques using meta-learning to detect malicious packages in Python’s official package repository (PyPI), enhancing cybersecurity and trust in open-source software ecosystems.