Solmaz Seyed Monir

Solmaz Seyed Monir

I'm a Ph.D. student at the University of Washington, advised by Professor Dongfang Zhao. My research focuses on database systems and information retrieval, with an emphasis on efficient indexing and retrieval for vector databases.

Research Areas: Database Systems, Data Management, Information Retrieval, Indexing

Current Research

I am currently researching advanced indexing and search techniques.

VectorSearch Illustration
VectorSearch: Enhancing Document Retrieval with Semantic Embeddings and Optimized Search

VectorSearch is a hybrid vector retrieval system that integrates semantic embeddings, multi-vector search, and hybrid indexing to improve retrieval accuracy and query efficiency through optimized index design and dynamic vector management.

Semantic Similarity Distribution
NexusIndex: A Self-Optimizing Multimodal Framework for Fake News Detection with Dynamic Indexing and Retrieval

NexusIndex integrates multi-model embeddings, attention mechanisms, and a FAISSNexusIndex layer to support efficient fake news detection via dynamic vector indexing and real-time retrieval across textual and visual data.

VecLSTM Research Diagram

VecLSTM: Trajectory Data Processing and Management for Activity Recognition through LSTM Vectorization and Database Integration

VecLSTM integrates dynamic vectorization with a CNN–LSTM architecture to process trajectory data efficiently within a relational database environment, improving accuracy and training time compared to traditional LSTM models.

Efficient Feature Extraction Illustration
Efficient Feature Extraction for Image Analysis through Adaptive Caching in Vector Databases

This research introduces a caching subsystem leveraging in-memory vector databases to improve image feature extraction efficiency. The framework integrates batch insertion and parallel processing to optimize performance.

ICICT 2024

Time Series Research
Enhanced Chaotic Transition Prediction Using Hierarchical Clustering for the Lorenz System

This research focused on using deep neural networks and hierarchical clustering to predict chaotic transitions in natural convection systems, specifically in the Lorenz system.

IMECE 2023

Academic Service

Program Committee: The Web Conference (WWW) 2026 — Security & Privacy Track

Reviewer: WWW 2025 — Search & Retrieval-Augmented AI Track, IEEE eScience 2025, IPDPS 2025, ICDCS 2025, ACM CIKM 2024, Journal of Big Data (2024–2025)

Education & Experience

University of Washington

2021 – Present

PhD Student, Computer Science & Systems

Sep 2023 – Present

Graduate Research Assistant (AI & Database Systems)

Handshake AI

Nov 2025 – Present • Remote, USA

AI Research Fellow

University of Washington

2022 – 2023

Graduate Research Assistant (Data Science & Mechanical Engineering)

North Seattle College

Sep 2023 – Present • Seattle, WA, USA

Lecturer

CSC 110 — Python Programming
CSC 142 — Java Programming I

Central Washington University

Sep 2022 – 2023 • Ellensburg & Des Moines, WA, USA

Lecturer

CS 380 — Software Engineering
CS 470 — Operating Systems

InstaHub

Oct 2021 – Apr 2022 • Philadelphia, PA, USA

Software Engineering Intern

Developed analytics web interfaces, built REST APIs, and supported AWS-based deployment.

Illinois Institute of Technology

2017 - 2019 • Chicago, IL, USA

M.S. in Information Technology Infrastructure (GPA: 4.0)

Azad University

M.S. in Data Science

Thesis: Modeling for Customer Value Optimization in Contact Centers

University of Science & Culture

B.E. in Computer Software Engineering