Aaron Yang

Yongpu (Aaron) Yang

Data Scientist & AI Engineer

Washington, DCyongpuy@upenn.edu+1 (202) 498-9099GitHub

Experience

Founder

DoubleThinking LLCWashington, DC

Mar 2025 — Present
  • Founded an AI consulting firm designing, building, and deploying production-grade AI systems for businesses nationwide
  • Deliver AI customer support solutions with intelligent conversational agents that manage tickets and inquiries while maintaining brand voice consistency
  • Build AI system integrations embedding AI capabilities into existing business infrastructure, connecting CRMs and internal tools through automated pipelines
  • Design data and automation workflows including ETL pipelines and document processing systems that convert unstructured data into actionable insights
  • Lead end-to-end project delivery from discovery and workflow auditing through rapid prototyping, production implementation, and ongoing optimization

AI Software Designer

Accredited LabsDallas, TX (Remote)

Jun 2025 — Present
  • Design and develop AI-powered software systems for document processing, quality assurance, and recruitment automation
  • Developed AI-powered resume screening tool with prompt injection security, reducing recruiter review time by 60% across 100s of applicants per position
  • Built certificate validation system processing 170,000+ calibration records using Python, BigQuery, and Google Cloud Storage (ISO/IEC 17025)
  • Created automated QC workflows with validation rules for test points and technician certifications, decreasing data entry errors by 40%
  • Designed ETL pipelines consolidating multi-branch calibration data, enabling real-time reporting and one-click invoice generation

Graduate Research Assistant

George Washington UniversityWashington, DC

Jan — May 2025
  • Conducted research on multi-agent AI systems and LLMs for advanced text generation and comprehension
  • Developed multi-agent systems with AWS Bedrock and open-source LLMs (LLaMA) for NLP tasks
  • Built scalable NLP pipelines using LangGraph, LangChain, and RAG on large-scale datasets (WikiText, COCO)
  • Utilized Gensim for topic modeling and word embeddings, incorporating XAI (SHAP, LIME) for model transparency

Education

University of Pennsylvania

School of Engineering and Applied Science

Master of Science in Engineering in Data Science (MSE-DS)

Expected Aug 2027

George Washington University

Master of Science in Data Science

May 2025

Shanghai Normal University

Bachelor of Economics in Financial Engineering

Jun 2019

Skills

Programming & Frameworks: Python (Pandas, NumPy, Scikit-Learn, PyTorch, TensorFlow), SQL, R, C, NLTK, Gensim, FastAPI, Selenium, BeautifulSoup
AI & Machine Learning: LLMs, RAG, LangChain, LangGraph, Multi-Agent Systems, NLP, Computer Vision, Fine-Tuning, Prompt Engineering, XGBoost, Random Forest, SHAP, LIME, Transformers
Cloud & Data: AWS (EC2, S3, Bedrock), Google Cloud Platform (BigQuery, GCS, Firestore), ETL Pipelines, Data Warehousing, Hadoop, Spark, SQL Server
Tools & MLOps: Docker, Git/GitHub, Streamlit, Jupyter Notebook, Model Deployment, Linux CLI, CI/CD, REST APIs, Tableau, Power BI