SINDHUJA MADABUSHI

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

PRIVEE: Privacy-Preserving Vertical Federated Learning Against Feature Inference Attacks
Sindhuja Madabushi, Haider Ali, Ahmad Faraz Khan, Ananthram Swami, Rui Ning, Jin-Hee Cho, Submitted to IEEE International Conference on Big Data 2025
CODE

OPUS-VFL: Incentivizing Optimal Privacy-Utility Tradeoffs in Vertical Federated Learning
Sindhuja Madabushi, Ahmad Faraz Khan, Haider Ali, Jin-Hee Cho, Submitted. Available on arXiv preprint, 2025
PDF| CODE

Empirical Analysis of Privacy-Fairness-Accuracy Trade-offs in Federated Learning: A Step Towards Responsible AI
Dawood Wasif, Dian Chen, Sindhuja Madabushi, Nithin Alluru, Terrance Moore, Jin-Hee Cho, AIES 2025
PDF| CODE

Two-Cloud Private Read Alignment to a Public Reference Genome
Sindhuja Madabushi, Parameswaran Ramanathan, PETS 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| SLIDES

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
Award 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 AND HONORS

  • Elected Secretary: Computer Science Graduate Council, Virginia Tech, 2025–2026
  • 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

SERVICE

  • Peer Reviews: IEEE Transactions on Network and Service Management (1 review), Transactions on Services Computing (3 reviews).
  • Volunteer: C-Tech² Program: Virginia Tech, Summer 2025
  • Volunteer: STEM Santa Fe: Nonprofit organization that delivers STEM programs, mentoring, and resources
  • Master’s Mentor: Otto-von-Guericke University, 2017–2018
  • Organizer: Magdeburg Indians, 2017–2018