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rockmagma02/README.md

Hi there πŸ‘‹

I'm Ruiyang Sun (/ruΜ―eΙͺΜ― jΙ‘Ε‹ swΙ™n/, or Ryan Sun; ε­™ηΏι˜³). I'm a πŸŽ“ senior undergraduate student pursuing a double major in 🧲 Physics and πŸ€– Artificial Intelligence (AI) at πŸ›οΈ Peking University.

I have previously worked in the areas of πŸ”’ Safe Reinforcement Learning (Safe RL) and πŸ€–πŸ§­ LLM Alignment, under the guidance of Prof. Yaodong Yang at the PKU Pair Lab. Currently, my research is focused on 🌱 Emergent Socio-Dynamic Behavior and 🧩 Alignment Issues in πŸ€–πŸ‘₯ AI-Human Societies, particularly focusing on advanced AI systems such as πŸ—£οΈ Large Language Models (LLMs), πŸ–ΌοΈ Large Multimodal Models (LMMs), and πŸ€–πŸ’Ό LLM-powered Autonomous Agents. I aim for my research to contribute to the safer, more harmonious, and dignified integration of πŸ€– AI systems into πŸ‘¨β€πŸ‘©β€πŸ‘§β€πŸ‘¦ human society. Here are some of the key research questions I'm exploring:

  1. When πŸ€– AI systems are treated as human-like entities in AI-human mixed ecosystems, can we observe the 🌟 emergence of human-like socio-dynamic behaviors from these AI systems?

  2. In what ways do the behaviors of πŸ€– AI systems diverge from those of πŸ‘₯ humans, and how can these distinctions inform our understanding of human-AI 🀝 interactions?

  3. How can emergent behaviors (e.g., 🀝 social learning, πŸ€— cooperation) enhance the intelligence of πŸ€– AI systems and the collective 🧠 intelligence of AI-human societies?

  4. What forms of ⚠️ misalignment might arise between πŸ‘₯ human and πŸ€– AI systems in AI-human mixed ecosystems, and what strategies can be used to πŸ› οΈ mitigate these misalignments effectively?

I believe that to develop more πŸ€– intelligent and ethical AI systems, we need to draw insights not only from πŸ’» Computer Science but also from fields like 🧠 Psychology, πŸ‘₯ Sociology, and 🧠 Cognitive Science. I welcome discussions from people with diverse perspectives! 🌍

Besides research, I'm also a passionate 🍎 Apple developer, and I am currently working on creating a new πŸ€– AI-powered teamwork research toolkit. I'd love to discuss or collaborate on this with anyone interested! 🀝

Where you can find me:

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  1. PKU-Alignment/safe-rlhf PKU-Alignment/safe-rlhf Public

    Safe RLHF: Constrained Value Alignment via Safe Reinforcement Learning from Human Feedback

    Python 1.3k 119

  2. huggingface/transformers huggingface/transformers Public

    πŸ€— Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

    Python 135k 26.9k

  3. PKU-Alignment/omnisafe PKU-Alignment/omnisafe Public

    JMLR: OmniSafe is an infrastructural framework for accelerating SafeRL research.

    Python 938 132

  4. StreamUtilities StreamUtilities Public

    StreamUtilities is a toolbox providing two utilities for working with stream in swift. SyncStream, a class that generates a sequence of values and operates synchronously. BidirectionalStream, a cla…

    Swift 1