Scholar
Haripriya Harikumar
Google Scholar ID: 50ErN80AAAAJ
Research Fellow, University of Manchester, UK
Adversarial Learning
AI Security
AI Safety
Differential Privacy
Trustworthy AI
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Citations & Impact
All-time
Citations
190
H-index
8
i10-index
6
Publications
20
Co-authors
20
list available
Contact
Email
haripriyaaharikumar@gmail.com
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Publications
1 items
TRUST: Test-time Resource Utilization for Superior Trustworthiness
2025
Cited
0
Resume (English only)
Academic Achievements
Paper “Privacy-Preserving Neural Processes for Probabilistic User Modeling” accepted to UAI 2025 (Rank A*).
Paper “Defense Against Multi-target Multi-trigger Backdoor Attacks” accepted to PAKDD 2025.
Paper “Targeted Manifold Manipulation Against Adversarial Attacks” accepted to IEEE SaTML 2025.
Paper “Composite Concept Extraction through Backdooring” accepted to ICPR 2024 and CVPR 2024 Workshop on Fine-Grained Visual Categorization.
Paper “Revisiting the Dataset Bias Problem from a Statistical Perspective” accepted to ECAI 2024.
Paper “Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation” accepted to NeurIPS 2022.
Paper “Towards Effective and Robust Neural Trojan Defenses via Input Filtering” accepted to ECCV 2022.
Paper “Prescriptive analytics with differential privacy” published in International Journal of Data Science and Analytics.
Paper “Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient” published in BioData Mining.
First paper on Trojan defense, “Scalable Backdoor Detection in Neural Networks,” accepted to ECML 2020.
Workshop “Backdoors in Deep Learning: The Good, the Bad, and the Ugly” accepted to NeurIPS 2023.
Awarded ELSA travel grant to attend CISPA-ELLIS Summer School 2025 on Trustworthy AI.
Awarded travel grant for IEEE SaTML 2025.
Delivered talks at IEEE Student Branch, MAIL Research Lab, and FOSS-CIL T24 conference.
Served as panelist in Black in AI Emerging Leaders Grad prep program.
Invited mentor at Women in Machine Learning (WiML) Workshop 2023.
Co-authors
20 total
Santu Rana
Associate Professor of Computer Science, Deakin University
Svetha Venkatesh
Deakin Distinguished Professor, Deakin University
Sunil Gupta
Professor, Head of AI Optimization and Materials Discovery, Deakin University
Kien Do
Applied Artificial Intelligence Institute (A2I2), Deakin University
Truyen Tran
Professor | Head of AI, Health and Science @ Deakin University
Thin Nguyen
Senior Research Lecturer, Deakin University, Australia
Hung Le
Research Lecturer (Assistant Professor), Deakin University
Dang Nguyen, PhD
Applied Artificial Intelligence Institute (A2I2), Deakin University, Australia
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