Education
- Master of Science in Computer Science, Georgia Institute of Technology, Aug. 2024 – May 2026
- Master of Science in Computational Science and Engineering (Applied Mathematics), Georgia Institute of Technology, Aug. 2023 – May 2026
- Bachelor of Engineering in Artificial Intelligence, Shandong University, Sep. 2019 – June 2023
Research Experience
Research Assistant
Georgia Institute of Technology | Atlanta, GA | Sep. 2025 – Present
Advised by Prof. Mingfeng Lin.
- Designing scalable multi-agent LLM experimentation frameworks to study causal effects in identity disclosure and stance change, using controlled R1–R2 role structures and cross-model interactions across 12 frontier models and 1.9K sessions.
- Building a Chromium/Electron orchestration layer that unifies browser chatbot sessions and direct API inference, using Playwright automation for parallel prompting, DOM-based response capture, and coordinator-LLM consistency scoring at scale.
- Current work targets an ACL 2026 submission on causal inference in multi-agent LLM interactions and identity-conditioned persuasion dynamics.
Machine Learning Researcher
Sustainable Urban Systems Lab, Georgia Tech | Atlanta, GA | Jan. 2025 – Present
- Developed FusionLSTM, a novel deep learning architecture integrating Gated Residual Networks, Variable Selection Networks, parallel multi-scale LSTM branches, and multi-head attention for urban microclimate forecasting, processing 947K warm-season 10-min observations from 16 weather stations (2015-2019).
- Built a physics-aware feature pipeline with solar-angle and cyclic-time encodings, enabling station-agnostic 24-hour temporal modeling and robust generalization to unseen locations (MAE: 0.95°C for temperature, 4.23% for humidity; R²: 0.857/0.823).
- Integrated Regression Kriging with PyKrige and Random Forest using nine geospatial covariates (LULC, elevation, shadow ratio) to generate 100K+ high-resolution grid-level predictions across the Georgia Tech campus (~3.5 km²), leveraging 16-station coverage for stable variogram estimation.
- Established comprehensive baseline comparisons and preparing a research manuscript for Building and Environment (SCI Q1, Impact Factor ≈ 7.1).
Research Assistant
Georgia Institute of Technology | Atlanta, GA | May 2025 – July 2025
Advised by Prof. Patrick Kastner.
- Optimization of microclimate surrogate models with cross-station generalization and Regression Kriging refinement.
Undergraduate Researcher
Shandong University | Shandong, China | Feb. 2023 – June 2023
- Developed an enhanced Bidirectional Rapidly-Exploring Random Tree (Bi-RRT) algorithm for autonomous vehicle path planning in complex parking lot environments.
- Implemented adaptive probabilistic sampling and local trajectory smoothing modules, improving exploration efficiency and reducing curvature in dense obstacle fields.
- Integrated real-time collision detection, dynamic obstacle avoidance, and kinematic feasibility validation for continuous, safe navigation under motion constraints.
- Achieved 2× faster planning speed, ~35% smoother paths, and 15% shorter average trajectory length compared to baseline RRT and RRT*, validated across 100+ randomized test scenarios.
Research Intern
Shandong University | Shandong, China | Sep. 2021 – April 2022
- Co-first & corresponding author of a peer-reviewed international conference paper (SPIE 2022) on automatic image colorization.
- Designed a novel lightweight GAN pipeline (U-Net generator + ResNet18 discriminator) and introduced a YUV-channel separation technique, reducing training cost while boosting structural fidelity and perceptual sharpness.
- Stabilized adversarial training with optimized objectives (re-weighted “realness” reliability term and tuned loss balance), improving color fidelity and transfer robustness under diverse textures and scenes.
- Scaled experiments on 4.3K+ natural & animated images in PyTorch with extensive visual comparisons, consistently outperforming baselines in visual quality and detail preservation.
Work Experience
Machine Learning Engineer
GMI Cloud | Mountain View, California | May 2025 – August 2025
- Optimized Flux-Schnell (12B DiT) multimodal inference on H100 clusters with GPU memory persistence & offload, reaching ~30 images/min/GPU and 1–2s latency (10–15× faster than baseline).
- Scaled a distributed multi-GPU inference pipeline (NCCL all-reduce, ONNX → TensorRT) achieving linear throughput across nodes.
- Built production-ready infrastructure (queuing, heartbeat monitoring, structured logging, GCS integration, content moderation) to ensure long-running stability & compliance.
- Implemented a video super-resolution pipeline (Real-ESRGAN + FastAPI) with PSNR/SSIM evaluation, reducing 5s@24fps clip runtime by ~65% (284s → 100s) when integrated with Wan2.2 text-to-video.
- Developed an AI-powered e-commerce try-on service (ComfyUI, Flux-Kontext + Segformer), delivering <5s per image outfit changing, background removal, and style transfer via secure RESTful APIs.
Projects
AI-Powered Product Recommendation System
Independent Venture | April 2024 – August 2024
- Architected an AI-powered recommendation system that analyzes millions of Amazon product reviews to help users quickly discover the most relevant and high-quality items through semantic search and LLM-based understanding.
- Developed a PySpark ETL pipeline to clean, tokenize, and embed reviews (768-dim via text-embedding-005), storing vectors and metadata efficiently in BigQuery for hybrid semantic retrieval.
- Designed a hybrid retrieval engine (ScaNN + metadata filters) that improved nDCG@3 by +21% (0.85 vs 0.70) and achieved MRR = 0.88, using approximate nearest neighbors (TreeAH + AVQ) with reranking via FastAPI microservice.
- Integrated Google Gemini with LangChain for RAG-based sentiment analysis and feature summarization, achieving 88% accuracy and 4.3 / 5 relevance for explainable recommendations.
- Provisioned scalable infrastructure on GCP (Cloud Run, BigQuery, Cloud Storage) using Terraform, sustaining ~6 s query latency and 92% product-category coverage across 500 test queries.
Competition Experience
American Express Default Prediction
Kaggle Competition | May 2022 – August 2022 | Top 0.4% (20th/4,874 teams), Silver Medal
- Developed a weighted ensemble of LightGBM (DART) and GPU-accelerated XGBoost models on 16 GB tabular time-series data covering transactions, balances, delinquencies, and repayments.
- Led model tuning and ensemble strategy, optimizing hyperparameters via grid search and stratified 5-fold cross-validation.
- Designed diverse feature sets—including lag features, rolling statistics, and trend indicators—and trained multiple seeds to boost stability, delivering a compact, high-performing solution that outperformed all baselines.
Teaching Experience
Teaching Assistant
Georgia Institute of Technology | Atlanta, GA | Sep. 2025 – Present
- ME 4710 – Foundations in Machine Learning for Engineers (Sep. 2025 – Dec. 2025, with Dr. Jarred Fountain): Designed grading rubrics and assessed weekly assignments on Python implementations, statistical modeling, and ML algorithm selection
- MGT 6655 – Business Data Preparation and Visualization (Jan. 2026 – May 2026, with Prof. Mingfeng Lin): Responsibilities include grading visualization exercises and dashboard projects; supporting students on Ed Discussions with Tableau, PowerBI, and data preparation techniques
- Academic Integrity TA Team (Jan. 2026 – May 2026): Institute-wide initiative; responsibilities include supporting academic integrity policies and student education across all colleges and departments
Undergraduate Teaching Assistant
Shandong University | Shandong, China | Sep. 2020 – July 2021
- Supported a 400+ student Linear Algebra course, driving grading, records management, and personalized learning support; recognized as Outstanding Teaching Assistant for exceptional dedication to student success.
- Assessed 600+ handwritten assignments with clear, actionable feedback, directly boosting student understanding and measurable performance outcomes.
- Tracked weekly attendance and maintained meticulous, audit-ready academic records, enabling accurate progress reviews and timely academic interventions.
- Answered 30+ student questions weekly via online forums, delivering detailed explanations and real-world examples to clarify key concepts like eigenvalues, matrix operations, and vector spaces.
Leadership & Service
Publicity Manager – Starlight Art Troupe
Shandong University | Shandong, China | Sep. 2019 – August 2021
- Directed the design and production of 30+ posters, flyers, and digital media assets to promote events, boosting audience turnout by 25% and strengthening brand recognition.
- Managed social media operations and curated engaging content, streamlining workflows and driving a 40% increase in follower engagement over two semesters.
- Coordinated 170+ photo/video shoots and post-production using Photoshop, Canva, Adobe Illustrator, Lightworks, and CapCut, delivering polished outputs on tight timelines.
- Led event planning and promotion with cross-functional teams, fostering community participation and earning the Outstanding Individual Award for Student Organizations at Shandong University.
Skills
- Programming Languages: Python, C/C++, Java, JavaScript, HTML/CSS, SQL, Bash/Shell, MATLAB, R, Julia
- Machine Learning & AI: PyTorch, TensorFlow, scikit-learn, HuggingFace, LangChain
- Cloud & Infrastructure: AWS, Azure, GCP, Docker, Kubernetes, Terraform
- Big Data & ETL: Apache Spark, Apache Airflow, PySpark, Databricks
- Database Systems: MySQL, PostgreSQL, MongoDB, Redis, BigQuery, Amazon Redshift
- Tools & Frameworks: Git, Linux, FastAPI, Flask, React, Node.js, Express, REST APIs
- Data Analysis & Visualization: Pandas, NumPy, Matplotlib, Tableau, Power BI, D3.js