Guanren Zhou

I am a Ph.D. candidate at UC Berkeley, advised by Prof. Khalid M. Mosalam in the STAIR Lab. My research focuses on grounded multimodal reasoning and generation across vision-language and NLP/LLM systems.

I am seeking a Summer 2027 internship in AI/ML research, machine learning engineering, or software engineering for AI systems.

Email  /  Scholar  /  GitHub  /  LinkedIn

Research

My work asks how models can reason over complex visual and textual inputs while grounding their outputs in identifiable image regions and source passages.

Hierarchical SAM 3 retrieval and DINOv3 specialist classifiers ground a frozen VLM’s fine-grained diagnoses in segmentation masks, enabling traceability without new task-specific annotations or VLM fine-tuning.

GeoScout conditions a PPO next-best-view policy on refined VLM geometry captions, using language as a prior over unobserved shape to reconstruct unseen object instances with fewer views than a matched no-caption policy.

This review contrasts case-specific optimization with reusable RL policies, highlighting cross-instance generalization, constraint satisfaction, and verifiable evaluation.

Fine-tuned BERTweet estimates state-level stress prevalence from social-media posts to calibrate an interpretable network model, revealing that social influence outweighed direct exposure in over 80% of U.S. states.

An event-triggered pipeline combines fine-tuned RoBERTa, VLM extraction from event graphics, and citation-constrained LLM synthesis to turn heterogeneous web sources into source-attributed briefings and temporal analyses.

A hierarchical LLM pipeline combines CNN-extracted visual attributes with structured metadata to generate per-instance reports and cross-instance summaries from multimodal observations.

Ongoing Research

This project formulates proposition-to-event grounding as a four-way target-conditioned classification task that exposes false attribution hidden by document-level relevance; benchmark construction is underway.

Website design borrows from Jon Barron