Resume

General Information

Full Name Xuyang Wu
Contact elviswu0306 [at] gmail [dot] com
Languages Chinese (native), English (fluent)

Research Areas

  • My research aims to improve the accuracy, efficiency, and fairness of search and ranking systems while addressing bias in large language models (LLMs).
  • I am also deeply committed to AI fairness and responsible AI, ensuring that large language models—the backbone of modern chatbots and virtual assistants—operate equitably across diverse user groups.

Education

  • 2019 – 2025
    Santa Clara University – Ph.D. in Computer Science
    • Advisor: Prof. Yi Fang.
    • Doctoral research focused on deep learning approaches for search ranking and fairness in AI.
    • Dissertation: Neural Ranking in Sparse Data Environments
  • 2013 – 2015
    University College London – M.Sc. in Web Science and Big Data Analytics
    • Thesis advised by Prof. Jun Wang.
    • Thesis: Active Learning in Real-time Bidding for Online Advertising.
  • 2011 – 2013
    Coventry University – B.Sc. in Computer Science
    • Graduated with First Class Honours.
    • Awarded Coventry University Scholarship.

Work Experience

  • 2020 - 2025
    Visiting Researcher at NTT DOCOMO Innovations, Inc.
    • Prototyping deep learning models for real-world applications.
    • Collaborated with cross-functional teams to quickly deploy research prototypes into demonstration products.
    • Developed and tested AI models for 3D image reconstruction from 2D photos, improving model accuracy for real-world scenes.
  • Summer 2022
    Data Scientist at Walmart Global Tech (Summer Intern)
    • Applied machine learning to e-commerce search and ranking.
    • Proposed a meta-learning approach for the product search ranking algorithm to handle sparse training data, enabling the model to generalize better with limited user feedback.
    • Demonstrated improved ranking performance over existing Learning-to-Rank methods, leading to a publication in ACM TOIS on sparsely supervised ranking.
  • Summer 2021
    Data Scientist at Walmart Global Tech (Summer Intern)
    • Designed an end-to-end multi-task learning framework using BERT (a language model) to jointly learn query understanding and product ranking.
    • Achieved a 5.8% improvement in click-through AUC over the baseline model (XGBoost) on Walmart’s dataset, contributing to a research paper accepted at WWW 2022.
  • 2021 – 2022
    Teaching Assistant at Santa Clara University
    • Courses assisted: Natural Language Processing, Machine Learning, Operating Systems, Database Systems, Object-Oriented Programming.
    • Led lab sessions and helped students grasp complex concepts through hands-on exercises and one-on-one mentoring.
    • Received positive feedback for clarifying theoretical concepts with practical examples.
  • 2020 – 2021
    Research Assistant at Markkula Center for Applied Ethics, Santa Clara University
    • NLP Research on media and ethics.
    • Developed an NLP pipeline (with Stanford CoreNLP) to analyze journalistic text, identifying quoted sources and their attributes (gender, title, organization) to study media bias and sourcing diversity.
    • Co-authored a paper on detecting journalistic boundary behaviors, published in the ISOJ 2023 conference proceedings.
  • 2016 – 2019
    Technical Director at Beijing QingLan Tech Co.
    • Led development of large-scale news recommendation and advertising systems.
    • News Recommendation System: Architected and deployed a content recommendation platform (RESTful API service) serving 30+ news websites and mobile apps.
    • Oversaw modules for data synchronization, cleaning, content classification, and real-time recommendation algorithms. Optimized recommendation strategies, boosting user engagement metrics across various media clients.
  • 2015 – 2016
    Senior Algorithm Engineer, Beijing Ruangao Technology Co., Ltd
    • Worked on machine learning models for online advertising.
    • Implemented click-through rate prediction models using large-scale user behavior data.
    • Improved the targeting accuracy of online ads by leveraging categorical feature encoding and ensemble learning techniques.

Research Experience

  • Search & Ranking Optimization
    • Dr. Wu has led projects aimed at improving how search engines and recommendation systems rank results. In one project, he developed a product search ranking model using multi-task deep learning (combining language understanding and ranking in one framework). This approach improved the relevance of top results and was successfully tested on a major retailer’s search platform. Another project introduced a meta-learning to rank algorithm that helps search systems quickly adapt to sparse or new data (useful when user feedback is limited). These efforts not only enhanced performance metrics (like click-through rate and ranking fairness) but also resulted in published research validating the techniques.
  • Fairness & Bias in LLMs
    • As part of his commitment to responsible AI, Dr. Wu works on evaluating and mitigating bias in large language models. He has investigated whether Retrieval-Augmented Generation (RAG) – feeding external documents into an AI model to help it answer questions – might introduce unfair bias into the model’s responses. Additionally, he conducted an empirical study on how well large language models serve as rankers, i.e. if they can rank search results without favoring or disadvantaging content related to certain demographic groups. These projects provide insights into the biases of state-of-the-art AI and guide the development of fairer algorithms. Findings from this research were presented in recent NLP conferences, helping raise awareness of AI fairness in the research community.

Professional Activities

  • Journal Reviewer
    • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
    • Neurocomputing
    • IEEE Access
    • Journal of the Frontiers of Computer Science
    • Connection Science
    • Complex & Intelligent Systems (CAIS)
  • Conference Program Committee Member/Reviewer
    • International Conference on Learning Representations (ICLR)
    • ACM Special Interest Group on Information Retrieval (SIGIR)
    • ACM The Web Conference (TheWebConf)
    • ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
    • ACL Rolling Review (ARR)
    • International Conference on Web Search and Data Mining (WSDM)
    • Conference on Information and Knowledge Management (CIKM)
    • ACM SIGIR Conference on Information Retrieval in the Asia Pacific (SIGIR-AP)
    • ACM International Conference on the Theory of Information Retrieval (ICTIR)
    • Conference on Language Modeling (COLM)
    • KDD Workshop on Deep Learning Practice for High-Dimensional Sparse Data (DLP-KDD)
    • The Second Workshop on Generative Information Retrieval (Gen-IR)

Computer skills

  • ○ Research & Expertise: Deep Learning, Information Retrieval, Search Ranking Algorithms, Recommendation Systems, Large Language Models, Responsible AI (Fairness/Bias mitigation), Meta-Learning, Multi-Task Learning.
  • ○ Frameworks & Libraries: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers.
  • ○ Programming: Python, Java, C/C++, JavaScript, SQL; Big Data tools like Spark and Hadoop.
  • ○ Databases & Tools: MySQL, PostgreSQL, MongoDB, Redis, ElasticSearch; FAISS (vector search library) for similarity search.
  • ○ Workflow & Other: Linux/Unix, Git version control, cloud computing (AWS/Azure), and containerization (Docker). Strong abilities in large-scale data analysis, effective communication, and team collaboration.

Leadership Experience

  • Oct 2019 – Now
    President, Graduate Engineering Chinese Student Association (GECSA)
    • Leads a graduate student organization focused on academic and cultural exchange. Organizes workshops, tech talks, and networking events connecting students with alumni and industry professionals. Initiatives under his tenure have improved cross-cultural understanding and provided professional development opportunities for members.
  • 2022 – Now
    Volunteer, The River of Life Foundation Food Pantry
    • Regular volunteer helping distribute food and manage inventory to support local families in need. Through this role, Dr. Wu has further honed teamwork and community outreach skills, demonstrating his commitment to giving back to the community.

Honors and Awards

  • 2013
    First Class Honours (Coventry University)
  • 2011
    Coventry University Scholarship
  • 2011
    National Endeavor Fellowship

Other Interests

  • Sports: Badminton, Tennis, Hiking
  • Hobbies: Traveling, Music, Movies