Ruoxi Zhao

• ·Developed AI agents integrating QuantLib and OpenBB for automated financial data analysis and quantitative modeling.
• ·Implemented iterative control loops enabling GPT API interaction with user input, including tool-calling functions for file read/write, Python execution, and code editing.
• ·Extending the agent framework toward reinforcement learning–based decision-making and adaptive strategy optimization.

• ·Analyzed and preprocessed heterogeneous X-Ray Diffraction (XRD) datasets to enable quantitative materials optimization.
• ·Developed objective functions and evaluated synthesis outcomes using statistical metrics.
• ·Automated data processing workflows using Python and Pandas.

Poster

Optimization Formulations for Self-Driving Inorganic Materials DesignOpen PDF ↗

• ·Surgical tool localization and detection in robotic surgery based on endoscopic video frames.
• ·Utilized Segment Anything Model (SAM) with text and box prompts; trained YOLOv8.
• ·Team ANL-Surg finished 3rd place in 2023 MICCAI SurgToolLoc challenge.
• ·Presented research poster at Argonne Lab's Learning on the Lawn event.

Poster

Surgical Instrument Localization using Language and Vision Foundation ModelsOpen PDF ↗

• ·Predicted dental cavities using color photos and Convolutional Neural Networks.
• ·Built data frames by converting photos to matrices with Pandas and NumPy.
• ·Applied Gaussian blur to experiment with its effect on prediction accuracy.

• ·Quantified how transcription factor binding kinetics depend on sequence.
• ·Applied statistical methods and K-mer analysis across multiple datasets.

Poster

Understanding Transcription Factor Binding Kinetics Using Statistical Learning MethodsOpen PDF ↗

• ·Integrated single-cell and spatial datasets using Tangram and PyTorch.
• ·Predicted cell type locations in spatial voxels; cell segmentation via Cellpose.
• ·Presented at Berkeley Lab's final symposium.

Poster

Integrating Single Cell Data with Spatial Transcriptomics Using Machine LearningOpen PDF ↗

• ·Built binary classifiers using molecular descriptors and 3D CNNs to find COVID-19 antivirals.
• ·Processed 2D/3D datasets (HDF5) with Pandas, NumPy, and PyTorch.

• ·Worked on planetary defense: classified stars vs. galaxies and captured asteroids from Palomar Observatory data.
• ·Applied CNNs with PyTorch; presented results to LLNL scientists and engineers.

Teaching Assistant

Mathematics Department, UC Riverside

• ·Assisted instruction for undergraduate courses: precalculus, calculus, discrete mathematics, differential equations, and linear algebra.
• ·Led discussion sections and office hours; graded assignments and exams.

Data Science Consultant

Graduate Quantitative Methods Center (GradQuant), UC Riverside

• ·Led workshops on data science fundamentals for UCR graduate students and postdoctoral scholars.
• ·Provided one-on-one coding and quantitative analysis support via remote consultations.

Data Analysis Intern

Businessolver & Open Avenues

• ·Built an interactive visualization tool in Python (Pandas, Matplotlib, NumPy) to analyze user-chatbot interactions.
• ·Compared inbound/outbound user trends and performed word frequency analysis on tweet data.

Shriram Summer Fellow

Reinvent Stockton Foundation & Stockton Scholars

• ·Created landscape analysis of Summer Bridge programs for incoming 9th graders across California.
• ·Presented findings to the Executive Board via Google Slides.

Project with Purpose

Merced County Arts Council

• ·Conducted case study research on the development of Arts & Culture Districts in demographics similar to Merced and their civic benefits.
• ·Provided recommendations to the MCAC on strategies for designating Downtown Merced as an Arts & Culture District.
• ·Created a PowerPoint and video presentation to introduce the concept and process to interested stakeholders.