I'm Rakshit Naidu and I am a Masters in Information Technology (MSIT-PE) student at Carnegie Mellon University (CMU). (Just graduated in Dec 2022!)
I was a Research Engineer at OpenMined where I worked on Privacy-Preserving Machine Learning (PPML). My research interests hover around Ethical Machine Learning, Resposible AI and Trustworthy AI.
I’m always open to discussions and I'm incredibly passionate about mentoring students or receiving mentorship from senior experts in my field of interests.
If you have any queries related to my work or a potential collaboration, or if there's any possible way I could guide you, please feel free to connect with me or drop me a mail.
Email / Google Scholar / LinkedIn / Github
News
- Feb 2023 : I have received a student travel grant to attend Secure and Trustworthy ML (SaTML) 2023, see you in Raleigh!
- Nov 2022 : I will be back as a reviewer at PPAI-AAAI'23!
- Sept 2022 : Our paper Pruning has a disparate impact on model accuracy has been accepted to NeurIPS 2022! Spotlight Lightning Talk
- Jul 2022 : I will be presenting two short position papers (1 and 2) at the Privacy Threat Modelling (PTM) workshop @ SOUPS'22. See you soon, Boston!
- May 2022 : I will be joining Prof. Ferdinando Fioretto's lab as a Visiting Research Scholar at Syracuse University over the summer (June-Aug 2022) to research on topics related to Differential Privacy + Fairness in AI! Super excited!
- April 2022 : Two posters accepted at IEEE S&P'22 and I received a student registration grant to attend it.
- Jan 2022 : I am the Teaching Assistant for 11860 - Quantum Computing Theory and Lab! Excited to partner up with Dan!
- Oct 2021 : I will be a first time reviewer at PPAI-AAAI'22. Please submit your papers here!
- Sept 2021 : Three papers accepted at PPML-CCS'21!
- Sept 2021 : One paper accepted at ECONLP-EMNLP'21!
- Aug 2021 : I have started my Masters at CMU!
- Jul 2021 : Three papers accepted at ICML'21 workshops!
- Jun 2021 : Two extended abstracts accepted at RCV-CVPR'21!
- May 2021 : FedPerf is now published at PMLR!
Research Interests
- Privacy-Preserving Machine Learning (PPML)
- Differential Privacy
- Federated Learning
- Secure Computations
- Adversarial Machine Learning
- Explainable AI
- Interpretable Machine Learning
- Fairness
- Robustness
- Quantum Machine Learning (QML)