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SINDHUJA MADABUSHI 
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I am a PhD student in the Computer Science department at Virginia Tech, advised by Dr. Jin-Hee Cho. My research focuses on building privacy-preserving, robust, and incentive-aligned federated learning systems that enable collaborative model training without compromising individual data security or fairness.
I design algorithms that address key challenges in federated learning—such as client dropout, adversarial behavior, data heterogeneity, and incentive misalignment—by integrating techniques from privacy-preserving machine learning, game theory, and applied cryptography. My goal is to ensure that federated systems are not only efficient and scalable, but also trustworthy and equitable in real-world deployments.
I hold a Master’s degree in Data and Knowledge Engineering from Otto von Guericke University Magdeburg, and a Bachelor's degree in Computer Science from GITAM University.
My broader interests include secure and explainable AI, algorithmic fairness, and incentive mechanisms for distributed systems. I am especially drawn to problems that sit at the intersection of theory and practice, and contribute to the responsible deployment of machine learning technologies.
Feel free to reach out at msindhuja@vt.edu if you'd like to connect or explore potential collaborations.
PAPERS
OPUS-VFL: Incentivizing Optimal Privacy-Utility Tradeoffs in Vertical Federated Learning
, Ahmad Faraz Khan, Haider Ali, Jin-Hee Cho
arXiv preprint, 2025
PDF
Empirical Analysis of Privacy-Fairness-Accuracy Trade-offs in Federated Learning: A Step Towards Responsible AI
Dawood Wasif, Dian Chen, , Nithin Alluru, Terrance Moore, Jin-Hee Cho
arXiv preprint, 2025
PDF
Two-Cloud Private Read Alignment to a Public Reference Genome
, Parameswaran Ramanathan
Proceedings on Privacy Enhancing Technologies Symposium 2023
PDF
CODE
TALK
M.Sc Thesis: Graph Sketches and Embeddings: A Study of their Applications in Graph Databases
Otto-von-Guericke-University Magdeburg
PDF
Bachelor's Thesis: Novel Network System with Miscellaneous Features
GITAM University
TALKS
P2VFL: Privacy-Preserving Incentive Mechanism in Vertical Federated Learning
2025 Commonwealth Cyber Initiative Southwest Virginia Student Researcher Showcase
Best Poster Award
EVENT
P2VFL: Privacy-Preserving Incentive Mechanism in Vertical Federated Learning
ACM The Capital Region Celebration of Women in Computing Conference (CAPWIC) 2025
CONFERENCE
SLIDES
Privacy Preserving and Feature Importance Based Incentive Mechanism in Vertical Federated Learning
ACM The Capital Region Celebration of Women in Computing Conference (CAPWIC) 2024
CONFERENCE
SLIDES
Exploring NoSQL Databases: Challenges and Opportunities
Guest Lecture for CS5614: Database Management Systems, Spring'24, Virginia Tech
Guest Lecture for CS4604: Introduction to Database Management Systems, Fall'23, Virginia Tech
SLIDES
AWARDS
Best Poster Award: Commonwealth Cyber Initiative Southwest Virginia Student Researcher Showcase 2025
Travel Award: ACM The Capital Region Celebration of Women in Computing Conference (CAPWIC) 2025
Travel Award: ACM The Capital Region Celebration of Women in Computing Conference (CAPWIC) 2024
Travel Award: Annual Computer Security Applications Conference (ACSAC) 2023