Elijah Sagaran  

Project Title: Fighting Fire with Fire: Deepfake Detection

Elijah is passionate about optimizing machine learning algorithms, building statistical models, and exploring human-machine interactions. He is currently working with Dr. Rashida Hasan under the CSUN-LSAMP Spring Research Grant. His current research focuses on unseen anomaly detection in network intrusion data.

Aaron Hoffman

 Project Title: Anomaly Detection in Medical Image Data

Aaron is a graduate student in the Department of Computer Science at CSUN. He has a strong interest in applying machine learning algorithms to advance innovative medical software. His current research focuses on detecting anomalies in medical imaging data. The goal is to help predict diseases that are not easily visible, even to experienced practitioners. This work aims to support earlier and more accurate diagnoses.

Rithvik Krosuri 

Project Title: AI-Generated Text Detection

Rithvik Krosuri holds a Bachelor of Technology in Electronics and Computer Engineering from the Amrita School of Computing, India. With a focus on machine learning and data analysis, he has co-authored a peer-reviewed publication on financial market forecasting models using advanced algorithms. Currently, he is contributing to a research initiative titled "Spotting Deepfakes," which explores methods to detect AI-generated textual content

Vaishnavi Sen 

Project Title: AI-Generated Text Detection

Vaishnavi is an international undergraduate student majoring in Computer Science at CSUN. She is passionate about leveraging artificial intelligence and emerging technologies to drive meaningful advancements in society. Her current research focuses on detecting AI-generated text, with the goal of combating misinformation, promoting academic integrity, and supporting the responsible use of technology.

Luis Olmos 

Project Title: Graph Anomaly Detection

Luis Olmos is a dedicated researcher in the lab, contributing to innovative work in anomaly detection for graph-structured data. He was the recipient of the CSUN-LSAMP Research Grant for Fall 2024 and Spring 2025, and was competitively selected for the prestigious SMART Scholarship by the U.S. Department of Defense. He has published three peer-reviewed conference papers showcasing his research contributions. Currently, Luis is developing a novel anomaly detection algorithm for graph-structured data.

Dhruvi Godhani 

Project Title: Intrusion Detection System for IoT-based smart environments

Dhruvi Godhani completed her Bachelor of Science in Computer Science from India. She is passionate about developing algorithms for intrusion detection systems in IoT devices. Her current research project is to develop novel machine-learning algorithms to identify security vulnerabilities in IoT-based smart systems.

Amir Rashidi 

Project Title: Fraud Detection in Financial Transactions

Amir Rashidi holds a Bachelor of Science degree in Computer Science from the University of California San Diego with a minor in Cognitive Science. He worked as a contingent worker for META Enterprise as a Business Intelligence Analyst. He is passionate about developing novel algorithms for knowledge discovery using machine learning and deep learning. His current research project focuses on developing a novel machine-learning algorithm for fraud detection in the static and streaming environment