I am a Master’s student in Computer Science at Stanford University, where I focus on developing human-centered AI systems that empower individuals in both everyday tasks and complex knowledge work. With a passion for bridging artificial intelligence and human interaction, my research aims to enhance learning, decision-making, and productivity by creating systems that collaborate seamlessly with users.

Publications

Unless otherwise specified, the paper is accepted/submitted as a research track long/regular paper. “ ∗ ” indicates equal contribution.

• Collaborative Gym: A Framework for Enabling and Evaluating Human-Agent Collaboration
  • Yijia Shao, Vinay Samuel$^∗$, Yucheng Jiang$^∗$, John Yang, Diyi Yang
  • [Pre-print]
• Into the Unknown Unknowns: Engaged Human Learning through Participation in Language Model Agent Conversations
  • Yucheng Jiang$^∗$, Yijia Shao$^∗$, Dekun Ma, Sina Semnani, Monica S. Lam
  • Accepted by 2024 Annual Conference of the Empirical Methods in Natural Language Processing (EMNLP 2024 main)
  • [Paper] [Code] [Website]
• Assisting in Writing Wikipedia-like Articles from Scratch with Large Language Models
  • Yijia Shao, Yucheng Jiang, Theodore A. Kanell, Peter Xu, Omar Khattab, Monica S. Lam
  • Accepted by 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2024 main)
  • [Paper] [Code] [Website]
• Effective Seed-Guided Topic Discovery by Integrating Multiple Types of Contexts
  • Yu Zhang$^∗$, Yunyi Zhang$^∗$, Martin Michalski$^∗$, Yucheng Jiang$^∗$, Yu Meng$^∗$, Jiawei Han
  • (Accpted by) The 16th ACM International Conference on Web Search and Data Mining (WSDM 2023)
  • [Paper] [Code]
• Entity Set Co-Expansion in StackOverflow
  • Yu Zhang$^∗$, Yunyi Zhang$^∗$, Yucheng Jiang, Martin Michalski, Yu Deng, Lucian Popa, ChengXiang Zhai, Jiawei Han
  • (Accepted by) IEEE BigData 2022 Workshop on Knowledge Discovery and Data Mining in IT Operations (BigData-IT)(short)
  • [Paper]
• An Analytic Comparison of Student-Scheduled and Instructor-Scheduled Collaborative Learning in Online Contexts
  • Geoffrey Herman$^∗$ , Yucheng Jiang$^∗$ , Yueqi Jiang, Seth Poulsen, Matthew West, Mariana Silva
  • (Accpted by) The 2022 Conference of the American Soceity for Engineering Education (ASEE 2022)
  • [Paper]

Research project

Engaged human learning through collaborative discourse with LLM agents

• Stanford Open Virtual Assistant Lab (2024 - Present)
• Directed the development of a human-AI collartion project aimed at facilitating human-centered natural language processing (NLP) and leveraging LLMs for enhanced human learning
• Contributed to the project’s global reach, serving over 200,000 users across 175 countries, with engagement from five school districts in the U.S. and U.K., highlighting its educational and societal impact
• Designed and implemented a full-stack web application to enable and evaluate complex information-seeking workflows, driving insights into human-AI interaction

Writing wikipedia by automatic knowledge curation with LLMs

• Stanford Open Virtual Assistant Lab (2023 - Present)
• Conceptualized and designed a cutting-edge pipeline for generating extensive Wikipedia articles autonomously, without relying on pre-existing outlines or resources
• Achieved over 13k stars on GitHub for innovative project contributions and generated over 300,000 articles in the wild
• Led the development of an LLM-driven automatic evaluation framework to systematically assess and enhance the quality of generated articles

Multi-modal depression and anxiety detection during pre-visit rooming

• Stanford Partnership in AI-Assisted Care (2023 - 2024)
• Led a team of four students in conducting critical experiments, utilizing cross-attention contrastive learning methods to analyze patient data for mental health indicators
• Engaged in emergency room shadowing at the Stanford Hospital Marc and Laura Andreessen Adult Emergency Department to identify practical applications for AI in enhancing the emergency room workflow and patient care
• Implemented a multi-modal approach, integrating data from various sources such as audio, visual, and textual patient information to improve detection accuracy

Long-range Context Hierarchical Seed-Guided Topic Discovery

• UIUC Data Mining Group (2022 - 2023)
• Lead a team of three students extend topic mining framework into hierarchy structure to facilitate hierarchical taxonomy construction and document classification
• Designed framework to leverage benefit of pre-trained language model and retrieve topic implicative document segments to perform topic discovery in a broader context
• Achieved 8% accuracy improvement compared to all state-of-art baseline models

Entity Set Co-Expansion in StackOverflow

• UIUC Data Mining Group (2022 - 2023)
• Design an entity set expansion model to simultaneously expand multiple types of seed by using mutual exclusivity among entity sets to determine expansion boundary
• Leverage generic natural language knowledge from pre-train language model to facilitate learning seed representation based on themselves and their context simultaneously

Seed-Guided Topic Mining

• UIUC Data Mining Group (2021 - 2022)
• Designed an iterative topic mining framework with text embedding and pre-trained language model based representations
• Improved weakly hierarchical multi-label text classification model to test on 100 million conference papers
• Achieved 13% accuracy improvement compared to baseline models

Professional experience

Software Development Engineer, Apple
San Diego, CA (2023)

• Ensured Apple’s compliance with regulatory standards for accuracy and availability, contributing to the expansion of location services new markets as they open
• Led the design and maintenance of key infrastructure for advanced location technologies, incorporating novel systems for localization using diverse information sources
• Implemented and refined testing and support infrastructure for WiFi and cellular positioning systems, boosting system reliability
• Deployed large-scale dashboards and monitoring of performance metrics

Software Engineer Intern, Apple
San Diego, CA (2022)

• Constructed software to support data analysis for the wifi positioning system and cellular positioning system.
• Proposed and implemented new algorithms for localization with wifi and cellular signals, improve accuracy by over 50%
• Coded testing and infrastructure to support wifi and cellular positioning systems

Teaching

• CS 222 Software Design Lab course assistant (Aug. 2022 - Dec. 2022)
• CS 225 Data Structure course assistant and project mentor (Aug. 2022 - Dec. 2022)
• CS 374 Intro to Algorithm \& Model of Computation course assistant (Aug. 2022 - Dec. 2022)
• CS 126 Software Design Studio course assistant (Jan. 2022 - May 2022)
• CS 128 Introduction to Computer Science II course developer ( Jan. 2021 - May 2021)
• CS 125 Introduction to Computer Science course assistant (Jan. 2020 - Dec. 2020)

Award

• University of Illinois Urbana-Champaign CRA Undergraduate Research Award (Oct. 2022)
• University of Illinois Urbana-Champaign Statistics Competition Second Place (Sep. 2021)
• Software Design Studio course algorithm competition First Place (Mar. 2020)