Xinyu Wang

Research & Engineering Portfolio

Xinyu (Ricky) WangStatistics, machine learning & AI systems

I build and evaluate machine learning models, then connect them to practical systems—from robotics perception to multi-agent LLM applications.

PhD candidate, Statistics & Data Science
University of Delaware · Expected May 2029

Advisor: Wei Qian · MS in Biostatistics, NYU

Portrait of Xinyu (Ricky) Wang

Selected projects

What I built, how I evaluated it, and where to explore it.

01 / Robotics & Computer Vision

Camera–LiDAR Perception with ROS 2

Contribution. Built a ROS 2 pipeline connecting YOLOv8n detections, camera–LiDAR fusion, vehicle-relative localization, and RViz visualization.

Evidence. Demo, technical report, and result bags with 1,305 timestamped output arrays at 0.25× replay.

Python · ROS 2 · OpenCV · YOLO
Demo & reproduction guide ↗
02 / Kaggle Competition · Team Project

Shopee Product Matching

Contribution. Contributed to a team retrieval solution combining Swin Transformer, NFNet, ArcFace, TF-IDF, and perceptual hashes.

Team result. Silver medal, top 4%. Includes the archived inference notebook and dependency notes.

PyTorch · Computer vision · Metric learning · Retrieval
Notebook & pipeline ↗
03 / Time-Series Forecasting

Stock & Energy Forecasting with PatchTST

Contribution. Applied the existing PatchTST model to Microsoft stock prices and AEP electricity demand using supervised training and self-supervised pretraining with fine-tuning.

Evaluation. Two univariate datasets, a seven-model baseline comparison, and accuracy/runtime summaries.

PyTorch · Univariate forecasting · Self-supervised learning
Code & recorded results ↗
04 / Reinforcement Learning · Course Project

Reinforcement Learning Strategy Evaluation

Contribution. Compared PPO, A2C, and DDPG in an NYU team course project using rolling training and validation windows.

Evaluation. Selected models by validation Sharpe ratio before evaluating the next trading period.

Python · Reinforcement learning · Time-series evaluation
Experiment & report ↗
05 / Healthcare & Statistical Modeling

Cervical Cancer Risk Modeling

Contribution. Collaborated on missing-data handling, exploratory analysis, and LASSO feature selection in R.

Evaluation. Compared models across sampling ratios using 858 patient records.

R · Statistical modeling · Healthcare data
Analysis & report ↗
06 / Natural Language Processing

Hate Speech Classification

Methods. Text preprocessing and BERT representations for hate speech classification.

Evaluation. Baseline model comparisons and ROC analysis.

NLP · BERT · Classification · Model evaluation
Explore the project ↗

More work: Graph Learning Prototypes · SQL Portfolio

Research & technical writing

Doctoral Research

Supervised dimension reduction

My doctoral research focuses on supervised dimension reduction, sparse modeling, and variational autoencoders, using simulation, ablation studies, and Python/PyTorch pipelines on HPC infrastructure.

STAT 802 · Technical Review

Sparse + Low-Rank Gaussian Graphical Models

A technical review connecting latent-variable precision matrix decomposition, convex optimization, geometric identifiability, and statistical consistency. Includes an attributed discussion of the reference paper’s experiments.

Read the report & source ↗

Engineering experience

Talengine

AI Engineer Intern

Built a LangGraph multi-agent interview system connecting resume-based questions, LLM answers, and adaptive follow-ups in structured JSON dialogue trees. Deployed MinerU parsing and candidate-matching workflows on AWS.

AMA AI

AI Engineer Intern

Integrated OpenAI APIs for conversational English practice, deployed a serverless text-to-speech workflow with Azure Functions, and supported Supabase databases and APIs.

Toolkit

Modeling

PyTorch, transformers, VAEs, regression, classification, feature selection

AI systems

LangGraph, multi-agent orchestration, OpenAI APIs, structured JSON outputs

Data & statistics

Python, R, SQL, SAS, pandas, NumPy

Deployment

AWS EC2/S3/Lambda, Azure Functions, PostgreSQL/Supabase, Linux, Shell

Evaluation

Controlled simulations, ablation studies, chronological validation, model benchmarking

Let’s connect.

For internship opportunities and research conversations.