Students

Ph.D. Student, CS

Graduate Teaching Assistant

Research Topic: Intersection of Natural Language Processing and usable privacy, security, and social media

dgoswam@gmu.edu 

LinkedIn, X (Formerly Twitter)

Google Scholar

Advisors: 

• Dr. Sanchari Das 

• Dr. Evgenios Kornaropoulos

ABOUT 

Dedicated and innovative fifth-year Ph.D. student with a strong foundation in Natural Language Processing (NLP), focusing on the intersection of usable privacy, security, and social media. My research leverages state-of-the-art Large Language Models (LLMs) to analyze and address challenges related to privacy concerns, sentiment dynamics, and security vulnerabilities in socio-technical systems. By combining expertise in linguistics, deep learning, and social media analysis, I aim to develop innovative solutions that enhance user privacy and security while contributing to cutting-edge advancements in NLP and its applications to real-world problems.

Ph.D. Student, IST

Research Topic: Large Language Models, Natural Language Processing, Graph Mining, and Explainable AI

shosse2@gmu.edu

LinkedIn, X (Formerly Twitter)

Google Scholar

Advisor: 

Dr. Sanchari Das

ABOUT 

I am an incoming Ph.D. student in the Information Sciences and Technology Department at George Mason University. My research interests include Large Language Models, Natural Language Processing, Graph Mining, and Explainable AI. I also have experience in spam detection and text analysis, as well as image and video processing. Broadly, my goal is to contribute to making social media platforms more trustworthy and enjoyable, while promoting greater transparency in AI-driven decision-making.

Masters Student, CS

Research Topic: Natural language processing

jnaveenk@gmu.edu

LinkedIn, X (Formerly Twitter)

Google Scholar

Advisor: 

Dr. Sanchari Das

ABOUT 

Fueled by a passion for innovation, I specialize in artificial intelligence and machine learning, leveraging expertise in NLP, predictive analytics, and deep learning to solve complex challenges. Proficient in Python, TensorFlow, and AWS, I design scalable, data-driven solutions that deliver transformative results and drive technological advancements.

Masters Student, DAEN

Research Topic: Machine learning modeling, Statistical analysis, Data engineering

hsingh45@gmu.edu 

LinkedIn, X (Formerly Twitter)

Google Scholar

Advisor: 

Dr. Sanchari Das

ABOUT 

Hello, my name is Harkirat Singh, and I am a Master’s student in Data Analytics Engineering at George Mason University. My academic background has equipped me with expertise in tools and technologies such as Python, SQL, R, Tableau, and Databricks. I have worked on projects such as analyzing structural and environmental data to optimize bridge longevity, developing a movie recommendation system using collaborative filtering, and utilizing machine learning models to enhance liver disease diagnostics. With a strong foundation in predictive modeling, statistical analysis, and data engineering, I am eager to collaborate on innovative research initiatives that generate meaningful insights and drive progress in the field.

Masters Student, DAEN

Research Topic: Identity and Access Management

vpodapat@gmu.edu 

LinkedIn, X (Formerly Twitter)

Google Scholar

Advisor: 

Dr. Sanchari Das

ABOUT 

I am a second-year graduate student at George Mason University, pursuing a Master’s degree in Data Analytics Engineering. I hold a Bachelor’s degree in Computer Science and have professional experience in Identity and Access Management from my tenure at Deloitte USI, where I worked with tools such as ServiceNow, SailPoint, and Mainframe. My journey has provided me with a good foundation in python, SQL, tableau, machine learning, and database management, and I am committed to learning and improve everyday. 

Masters Student, DAEN

Research Topic: AI/ML to Cyber Security

mgrover3@gmu.edu 

LinkedIn, X (Formerly Twitter)

Google Scholar

Advisor: 

Dr. Sanchari Das

ABOUT 

Hello, my name is Mayank Grover, and I am a graduate student in Data Analytics Engineering at George Mason University. With a foundation in full-stack development and a strong interest in data science, I’ve worked on projects involving data management, deep learning classification, and analytics. My recent focus lies in applying AI/ML to cybersecurity and data privacy challenges. As part of my undergraduate research, I contributed to projects utilizing image data and generative adversarial networks (GANs), which enhanced my expertise in predictive modeling and deep learning. I’m passionate about building secure, data-driven solutions to address evolving cyber threats and privacy concerns.

Masters Student, CS with ML specialization

Research Topic: Natural Language Processing (NLP), Vision-Language Models (VLMs)

dbanerj@gmu.edu 

LinkedIn, X (Formerly Twitter)

Google Scholar

Advisor: 

Dr. Sanchari Das, Dr. Ziwei Zhu

ABOUT 

I am a Computer Science graduate student specializing in Machine Learning, with research interests spanning Natural Language Processing (NLP), Vision-Language Models (VLMs), and the development of reliable, interpretable AI systems. My current work focuses on Medical Visual Question Answering (VQA), applying vision-language modeling to interpret structured health data such as heart rate and sleep trends. I am also investigating prompt injection vulnerabilities in LLM-based agentic systems, exploring how differential privacy impacts model performance and robustness. With prior experience as a Salesforce Developer and Data Analyst, I combine practical industry skills with experimental research to contribute to advancing trustworthy, scalable AI technologies.

Ph.D. Candidate, CS

Research Topic: Natural Language Processing for Privacy Policies

Andrick.Adhikari@du.edu 

LinkedIn, X (Formerly Twitter)

Google Scholar

Advisors: 

Dr. Sanchari Das and Dr. Rinku Dewri 

ABOUT 

I have joined Google as a Software Engineer from 2023. My research interests encompass Privacy and NLP. My dissertation is focused on the application of NLP to effectively extract privacy specific features from organizational privacy policies and present a scalable, easily adaptable solution for users.