Dacheng Shen

Dacheng Shen

Computer Science Ph.D. Student

Passionate about AI, Machine Learning, and NLP. Currently pursuing my Ph.D. at Washington State University, building intelligent systems that solve real-world problems.

🔬 View Research 💡 My Projects

🎓 Education

Washington State University, Tri-Cities Jan 2026 - Present
Ph.D. in Computer Science
University of Southern California June 2024 - Dec 2025
M.S. in Computer Science
University of Connecticut Sept 2020 - May 2024
B.S. in Computer Science
Dean's List Honors

💼 Experience

Software Development Engineer Jul 2023 - Aug 2023
HICOCA Intelligent Equipment Technology
  • Managed backend and server maintenance
  • Updated framework, improved UI and performance
  • Configured DB privileges and security
  • Led UI development with 32% improved user satisfaction

🔬 Research

Comparative Narrative Analysis with Claude 3.7 Mar. 2025 - Aug. 2025
Research Assistant
  • Designed and automated a full Claude 3.7 Sonnet-based LLM evaluation pipeline for 208 narrative pairs under four comparison dimensions (conflict, unique, holistic, overlapping)
  • Engineered scalable prompt-based inference using anthropic API and batched output parsing, reducing manual judgment workload by over 90%
  • Structured model responses into JSON and human-readable formats to enable systematic cross-model analysis and future human annotation
  • Collaborated with faculty and research team on dataset preparation, narrative extraction, and designing metrics for minimizing bias in LLM comparison
OEM Controls Automated Angle Test for AS5 Aug. 2023 - May. 2024
Capstone Project Lead
  • Led a year-long capstone project to automate Quality Assurance testing for the AS5 sensor system, significantly improving testing efficiency and reliability
  • Developed a Python-based control system on Ubuntu to operate a 6-axis robot arm, automating sensor calibration and test procedures with precise "Pass/Fail" feedback and real-time result logging
  • Designed and implemented a seamless UI-Backend integration using APIs, replacing the previous client version with a fully automated calibration solution
  • Successfully delivered the project, reducing manual testing time by 67% and improving calibration accuracy by 26%, which enhanced overall efficiency and reliability

📚 Projects

Transfer Learning for Waste Classification Jan. 2025 - May 2025
  • Developed a multi-class image classifier for nine waste categories using Python, TensorFlow/Keras, with an 80/20 train/test split and 20% in-training validation for robust model evaluation
  • Built a preprocessing pipeline to resize images and applied extensive data augmentation (random crops, zooms, rotations, flips, contrast adjustments, translations) to mitigate overfitting
  • Implemented transfer learning by freezing pretrained backbones (ResNet50, ResNet101, EfficientNetB0, VGG16) and adding custom FC layers with ReLU, softmax, L2 regularization, batch normalization, and 20% dropout
  • Evaluated all models on test set using precision, recall, AUC and F1-score; identified VGG16 as the top performer—achieving highest accuracy and generalization
AI-Driven Travel Assistant Design – FlySmart Mar. 2025 - May. 2025
  • Led a requirements engineering project to design an AI-powered flight booking assistant
  • Conducted stakeholder analysis, surveys, and interviews, derived user personas, empathy maps, and categorized requirements
  • Created and validated a Figma prototype with features including flight search, visa management, smart alerts, and personalized AI chat interface
  • Applied agile methodology with story-driven backlog, sprint-based development roadmap, and formal validation via usability testing and prototyping
Semantic Retrieval and QA System with Weaviate & RAG Sep. 2024 - Dec 2024
  • Built a semantic search pipeline using Weaviate with text2vec-transformers for vector-based brand similarity via GraphQL nearText queries
  • Developed a PDF QA chatbot with Streamlit, leveraging PyPDFLoader, ChromaDB, and Hugging Face embeddings in a RAG framework for document-grounded response generation
Large-Scale Sentiment Analysis on Amazon Office Reviews Aug. 2025 - Oct. 2025
  • Cleaned and normalized 200k+ review texts (regex HTML/URL removal, tokenization, stopword filtering, lemmatization)
  • Trained TF-IDF (uni + bi-gram) ML models including LinearSVC, Logistic Regression, and Perceptron
  • Reproduced and evaluated two GloVe-based representations: 100-d average pooling vs. 1000-d first-10-token concatenation
  • Demonstrated that 100-d average pooling generalizes more robustly across unseen reviews
Student Admin Design Sep. 2023 - Dec. 2024
  • Collaborated on a group project, using Figma to design the product model and present the plan to stakeholders
  • Developed and implemented the code to bring each Figma design feature to life
  • Completed the website development and thoroughly tested all functionalities
Food Ordering App Design Aug. 2021 - Nov. 2021
  • Used Java to build a food ordering app that could generate an invoice with the name and price of the dish and the total price after ordering
  • Group leader, used GitHub to share and merge information and parts of what each group member had finished
  • Completed a report and made a presentation

🔧 Skills

💻

Programming Languages

Python Java C C++ SQL HTML
🤖

AI / ML / NLP

Hugging Face Transformers RAG Transfer Learning LLM Prompting Semantic Search MapReduce Model Evaluation PyTorch NLTK Gensim scikit-learn
🗄️

Data & Databases

MySQL MongoDB ChromaDB Weaviate Web Crawling Data Preprocessing JSON Parsing
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Software Design

REST APIs Modular Architecture UML Agile (Scrum)
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Tools & Platforms

Git Docker Trello Figma Microsoft Office Suite AWS Streamlit Jupyter Lightroom Photoshop