Xijing Wang (Thomas)
Apple SDE Intern · MLE · Research Engineer
Carnegie Mellon University, School of Computer Science
I'm a graduate student at Carnegie Mellon University (School of Computer Science), pursuing an M.S. in Automated Science.
I received my B.S. in Computer Science (emphasis in Algorithms) from Santa Clara University, where I worked with Dr. Lang Chen and was advised by Dr. Nicholas Q. Tran.
My interests lie in AI Agents, ML Systems, and full-stack intelligent applications.
Looking for opportunities in AI Agent, AI Infrastructure, and MLSys. Please reach out at thomasw3@andrew.cmu.edu
Updates
Last updated: Jun 2026Core ML Tools — LightGBM to Core ML converter supporting Booster, LGBMClassifier, and LGBMRegressor models.
Jun 2026
Software Engineering Intern at Apple, Analytics & Data Science team in Wireless Technology Ecosystem. Focused on agent development and applied ML work.
May — Aug 2026
Article published in Communications Biology — E/I imbalance and internal noise cause weak neural representations and face recognition challenges in ASD.
Apr 2026
Open source contributor to apache/tvm — end-to-end deep learning compiler stack for CPUs, GPUs, and specialized accelerators.
Since Apr 2026
Building localmelo/localmelo — a local-first AI agent framework with progressive long-term memory and Sleep Model embedding fine-tuning. Modular Melo / Support / Test architecture, supporting Ollama, MLC, and OpenAI-compatible backends.
Since Apr 2026
Open source contributor to mlc-ai/mlc-llm — on-device LLM deployment framework. Used in Headache Note iOS app with quantized LLaMA 3.
Since Jan 2026
Open source contributor to xthomaswang/OpenOT2 — lab automation framework for the OT-2 liquid handling robot.
Since Jan 2026
Poster at GenAI4Health @NeurIPS 2025 — The Second Workshop on GenAI for Health: Potential, Trust, and Policy Compliance. San Diego, CA.
Dec 2025
Research Engineer at CMU — built AI-powered biomedical literature analysis platform with RAG pipeline and embedding-based semantic search. Fine-tuned Qwen3 0.6B embedding model on multi-GPU, achieving strong benchmark on PMC-Patients PPR task.
July — Dec 2025
Started graduate studies at Carnegie Mellon University in the MSAS program, School of Computer Science. Director's Scholarship recipient.
Aug 2025
Poster at CogSci 2025 — 47th Annual Meeting of the Cognitive Science Society. San Francisco, CA.
July 2025
ML Research Intern at LCCN Lab, SCU. Fine-tuned CNNs and Vision Transformers to test neuroscience hypotheses. Built fMRI data processing and representation analysis pipelines.
2024
Experience
Software Engineering Intern @ Apple
May 2026 — Aug 2026Cupertino, CA
Summer 2026 internship on the Analytics & Data Science team in Wireless Technology Ecosystem, focused on agent development and applied ML work.
Research Engineer (AI Agent) @ Carnegie Mellon University
July 2025 — Dec 2025Pittsburgh, PA
Built an AI-powered biomedical literature analysis platform with Quick (<30s) and Deep (<=3min) modes using a RAG pipeline with parallel retrieval from PubMed and MedRxiv. Fine-tuned Qwen3 0.6B embedding model on multi-GPU, achieving strong benchmark results on PMC-Patients PPR task. Poster at NeurIPS 2025 Workshop on GenAI for Health.
ML Engineer Intern @ LCCN Lab, Santa Clara University
June 2024 — Sep 2024Santa Clara, CA
Developed CNN models for neuroscience research and preprocessed fMRI data for HPC workflows. Article published in Communications Biology; poster accepted at CogSci 2025.
Education
Carnegie Mellon University
Aug 2025 — May 2027M.S. in Automated Science
School of Computer Science · Pittsburgh, PA
Director's ScholarshipSanta Clara University
Sep 2021 — Mar 2025B.S. in Computer Science, Minor in Economics
College of Arts and Sciences · Santa Clara, CA
REAL Program ScholarSkills
Projects
Clinical Copilot — Medical Literature Analyzer
ResearchAI-powered literature analysis system using a RAG pipeline with PubMed & MedRxiv. Fine-tuned Qwen3 0.6B embedding model on multi-GPU, achieving strong benchmark on PMC-Patients PPR task. Poster at NeurIPS 2025 Workshop on GenAI for Health.
apache/tvm — Deep Learning Compiler Stack
Open SourceOpen-source contributor to Apache TVM, an end-to-end deep learning compiler stack for CPUs, GPUs, and specialized accelerators. Focused on operator scheduling and on-device inference paths.
LocalMelo — Local-First AI Agent Framework
Open SourceA local-first AI agent framework exploring always-on agents that automate routine work and learn user habits. Modular architecture (Melo core / Support / Test), with progressive long-term memory and a Sleep Model that fine-tunes the embedding model offline. Hybrid local + API execution, supporting Ollama, MLC, and OpenAI-compatible backends.
mlc-ai/mlc-llm — On-Device LLM Deployment
Open SourceContributor to MLC-LLM, an open-source framework for deploying LLMs on-device across platforms (iOS, Android, Web). Used the framework to enable on-device inference with quantized LLaMA 3 models in the Headache Note iOS app.
OpenOT2 — Open-Source Lab Automation
Open SourceOpen-source contribution to OpenOT2, a lab automation framework for the OT-2 liquid handling robot. Enabling reproducible scientific workflows through programmable protocols.
Headache Note — Offline iOS AI Agent
SoftwareFully offline iOS AI agent built by quantizing LLaMA 3 1.6B with MLC-LLM, optimized for iPhone. Swift-based health assistant with prompt engineering and SwiftData for private, on-device inference and personalized lifestyle recommendations.
Neurocomputational Basis of Face Recognition in ASD
ResearchResearch on face recognition challenges in ASD using CNNs, ResNet50, and Vision Transformers as computational frameworks. Built fMRI data processing pipelines and Pearson correlation analysis. Article published in Communications Biology (Nature Portfolio, 2026); poster at CogSci 2025.
MasumiRanker — AI Agent Platform (Hackathon)
SoftwareAI agent discovery platform with natural language semantic search using Sentence Transformers and Faiss for efficient similarity matching. FastAPI + SQLAlchemy backend with user ratings, recommendation logging, and SHA-256 data integrity.
Food Recognition iOS App
SoftwareSwiftUI iOS app with MVVM architecture, integrating a TensorFlow-trained CoreML model for food classification with 85% accuracy across 100+ categories. Optimized inference speed by 4x and reduced memory usage by 40%.
EmojiAndEmotion — Health Tracking App
SoftwareFull-stack iOS app with React Native and SQLite. Optimized data queries by 75% (200ms to 50ms). Integrated Apple HealthKit for real-time HRV metrics with 98% accuracy. 90% test coverage.
Social Networking Website
SoftwareFull-stack web server using the Go Gin framework with RESTful API, JSON-based database for efficient data management, and a scalable commenting system.
Resume & CV
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