resume.json

{
  "basics": {
    "name": "Keyu He",
    "label": "Master in NLP@CMU SCS || NLP Researcher",
    "image": "keyu.png",
    "email": "keyuhe@cmu.edu",
    "phone": "(213) 713-2973",
    "url": "https://keyu-he.github.io/",
    "summary": "Master of Intelligent Information Systems (MIIS) student at Carnegie Mellon University. Previously earned B.S. from USC with double major in Computer Science and Applied & Computational Mathematics. Passionate about socially intelligent AI systems and human-centered AI evaluation.",
    "location": {
      "city": "Pittsburgh",
      "region": "Pennsylvania",
      "countryCode": "US"
    },
    "profiles": []
  },
  "education": [
    {
      "institution": "Carnegie Mellon University",
      "location": "Pittsburgh, PA",
      "url": "https://www.cmu.edu/",
      "area": "Master of Intelligent Information Systems (MIIS)",
      "studyType": "Master's",
      "startDate": "2025-08-01",
      "endDate": "2027-05-01",
      "score": "4.14/4.33",
      "summary": "Graduate program focusing on intelligent information systems, NLP research, and AI systems. Conducting research on explainable AI and socially intelligible AI.",
      "courses": [
        "Advanced Natural Language Processing (A+)",
        "Multimodal Machine Learning (A+)",
        "Prompt Engineering (A+)",
        "Introduction to Question Answering (A)",
        "Independent Study in Language Technologies (A)",
        "Directed Study in Language Technologies (A)"
      ]
    },
    {
      "institution": "University of Southern California",
      "location": "Los Angeles, CA",
      "url": "https://www.usc.edu/",
      "area": "Computer Science and Applied & Computational Mathematics",
      "studyType": "Bachelor's",
      "startDate": "2021-08-01",
      "endDate": "2025-05-01",
      "score": "3.98/4.00",
      "summary": "Minor in Artificial Intelligence Applications. USC Dornsife Dean's List & USC Viterbi Dean's List (2021-2025). USC Center for Undergraduate Research in Viterbi Engineering (CURVE) fellow with $6,750 in research funding (Spring 2024 - Spring 2025). USC Academic Achievement Award covering $24,000 in tuition.",
      "courses": [
        "Language Models in Natural Language Processing (A)",
        "Applied Machine Learning for Natural Language Processing (A)",
        "Applied Neural Networks (A)",
        "Capstone: Design and Construction of Large Software Systems (A)",
        "Mathematical Statistics (A)",
        "Probability Theory (A)",
        "Numerical Methods (A)"
      ]
    }
  ],
  "publications": [
    {
      "name": "RECAP: An End-to-End Platform for Capturing, Replaying, and Analyzing AI-Assisted Programming Interactions",
      "author": "Keyu He*, Qianou Ma*, Valerie Chen, Wayne Chi, Tongshuang Wu",
      "publisher": "ACL 2026 Demo",
      "releaseDate": "2026-07",
      "summary": "RECAP captures AI chat and code edits in VS Code, merges them into replayable timelines, and provides analysis modules for studying developer-AI interaction patterns.",
      "url": "https://arxiv.org/pdf/2605.01104"
    },
    {
      "name": "Believing without Seeing: Quality Scores for Contextualizing Vision-Language Model Explanations",
      "author": "Keyu He, Tejas Srinivasan, Brihi Joshi, Xiang Ren, Jesse Thomason, Swabha Swayamdipta",
      "publisher": "ACL 2026",
      "releaseDate": "2026-07",
      "summary": "We introduce Visual Fidelity and Contrastiveness -- two explanation quality scores that help users more appropriately rely on vision-language model predictions without seeing the image.",
      "url": "https://arxiv.org/pdf/2509.25844"
    },
    {
      "name": "ELI-Why: Evaluating the Pedagogical Utility of LLM Explanations",
      "author": "Brihi Joshi*, <b>Keyu He*</b>, Sahana Ramnath, Sadra Sabouri, Kaitlyn Zhou, Souti Chattopadhyay, Swabha Swayamdipta, Xiang Ren",
      "publisher": "Findings of ACL 2025",
      "releaseDate": "2025-07",
      "summary": "Evaluate the pedagogical utility of LLMs in tailoring explanations to users with different educational backgrounds.",
      "url": "https://arxiv.org/pdf/2506.14200"
    },
    {
      "name": "Attributing Culture-Conditioned Generations to Pretraining Corpora",
      "author": "Huihan Li*, Arnav Goel*, Keyu He, Xiang Ren",
      "publisher": "ICLR 2025",
      "releaseDate": "2025-04",
      "summary": "This paper introduces MEMOed, a framework to analyze whether AI generations are driven by memorization or generalization, with a focus on cultural symbols.",
      "url": "https://arxiv.org/pdf/2412.20760"
    },
    {
      "name": "Enhancing Debugging Skills of LLMs with Prompt Engineering",
      "author": "Keyu He*, Max Li*, and Joseph Liu*",
      "publisher": "Technical Report",
      "releaseDate": "2023-12",
      "url": "../assets/pdf/Enhancing-Debugging.pdf",
      "summary": "Study on improving LLM debugging through prompt engineering techniques. Evaluated few-shot learning and chain-of-thought approaches on GPT-3.5, revealing limitations in current debugging capabilities."
    }
  ],
  "work": [
    {
      "name": "Adobe",
      "position": "Machine Learning Engineer Intern",
      "location": "San Jose, CA",
      "startDate": "2026-05-01",
      "endDate": "2026-08-01",
      "summary": "Incoming",
      "highlights": []
    },
    {
      "name": "CMind",
      "position": "Data Engineer Intern",
      "location": "Remote",
      "startDate": "2025-05-01",
      "endDate": "2025-08-01",
      "highlights": [
        "Built a LangChain-based RAG prototype over an internal analytics DB (chunking, embeddings, FAISS indexing/retrieval, LLM answer synthesis) with metadata filters and notebook/API utilities.",
        "Designed CEO-speech trait metrics and an auto-evaluation pipeline with custom rubrics, achieving Fleiss' κ of 0.89–0.91 against human annotations."
      ]
    }
  ],
  "projects": [
    {
      "name": "LLM Prompt Recovery",
      "summary": "Developed a system to recover user prompts using fine-tuned Mixtral models, achieving top 3.4% in a Kaggle competition.",
      "startDate": "2024-03-01",
      "endDate": "2024-04-01",
      "highlights": [
        "Achieved a score of 0.65 using sentence-T5-base and sharpened cosine similarity.",
        "Ranked 75/2175 globally in the Kaggle competition.",
        "Published fine-tuned model on Kaggle for broader access."
      ],
      "url": "https://www.kaggle.com/models/keyuhe02/mixtral-8x7b-instruct-finetuned"
    },
    {
      "name": "AI-Based Career Advisor",
      "summary": "Built an AI tool to assist users in planning career paths based on skills and interests.",
      "startDate": "2024-11-01",
      "endDate": "2024-12-01",
      "highlights": [
        "Developed a Streamlit-based interactive UI integrating GPT-4o for job suggestions.",
        "Implemented cosine similarity search for skill-job matching.",
        "Integrated Bing AI for real-time job application link retrieval."
      ]
    },
    {
      "name": "Enhancing Debugging Skills of LLMs with Prompt Engineering",
      "summary": "Improved LLM debugging capabilities through advanced prompt engineering techniques.",
      "startDate": "2023-08-01",
      "endDate": "2023-11-01",
      "highlights": [
        "Experimented with various prompting strategies to enhance debugging efficiency.",
        "Achieved significant improvements in LLM performance on debugging tasks."
      ]
    },
    {
      "name": "Automated Hate Speech Detection in Social Media",
      "summary": "Developed an advanced ML model for detecting hate speech, achieving 94% accuracy.",
      "startDate": "2023-09-01",
      "endDate": "2023-12-01",
      "highlights": ["Fine-tuned BERT for classification tasks.", "Enhanced online safety and inclusivity through robust model optimization."]
    }
  ],
  "skills": [
    {
      "name": "Programming",
      "level": "",
      "keywords": ["C++", "Python", "Java", "MySQL", "HTML", "CSS", "JS", "TS", "x86-64 Assembly"]
    },
    {
      "name": "Software",
      "level": "",
      "keywords": ["PyTorch", "Pandas", "NumPy", "Git", "AWS", "LaTeX", "Mathematica", "Matlab"]
    },
    {
      "name": "Areas of Expertise",
      "level": "",
      "keywords": ["Machine Learning", "Natural Language Processing (NLP)", "Large Language Models (LLMs)", "Data Science / Data Engineering"]
    },
    {
      "name": "Languages",
      "level": "",
      "keywords": ["Mandarin (native)", "English (professional)"]
    }
  ],
  "awards": [
    {
      "title": "Silver Medal, Kaggle Competition",
      "date": "2024-04",
      "summary": "Ranked 75/2175 (Top 3.4%) on the global leaderboard, LLM Prompt Recovery Project.",
      "url": "https://www.kaggle.com/models/keyuhe02/mixtral-8x7b-instruct-finetuned"
    },
    {
      "title": "USC Academic Achievement Award",
      "date": "2022-12",
      "summary": "Awarded in Fall 2022, Spring 2023, Spring 2024, and Fall 2024. Covered 11 units of tuition costs in total, amounting to approximately $24,000."
    },
    {
      "title": "4th Place, USC Integral Bee Competition",
      "date": "2022-04",
      "summary": "Ranked 4th in the USC Integral Bee Competition."
    },
    {
      "title": "1st Prize, International Linguistics Olympiad",
      "date": "2021-07",
      "summary": "Senior Level, Individual Open Round, China."
    },
    {
      "title": "1st Prize, International Linguistics Olympiad",
      "date": "2021-07",
      "summary": "Senior Level, Team Open Round, China."
    }
  ]
}