Older News

• 10/2023 [Paper]: Released a new pre-print based on work done during my summer internship at Bosch: "Model Selection of Anomaly Detectors in the Absence of Labeled Validation Data".
• 08/2023 [Paper]: "Attributions for ML-based ICS Anomaly Detection: From Theory to Practice" accepted at NDSS 2024!
• 05/2023 [Work]: This summer, I am interning at the Bosch Center for AI in Pittsburgh!
• 05/2023 [Misc]: Attending CACTUS-P at the University of Maryland in College Park! Find me if you want to chat about human interaction with anomaly detection!
• 04/2023 [Talk]: Presented my research on industrial anomaly detection at a CAE-R research seminar.
• 02/2023 [Service]: Serving as a PC member for FAccT '23!
• 10/2022 [Talk]: Presented my research on industrial anomaly detection at the 2022 CyLab Partners Conference.
• 09/2022 [Talk]: Speaking at ESORICS 2022.
• 03/2022 [Paper]: "Perspectives from a Comprehensive Evaluation of Reconstruction-based Anomaly Detection in Industrial Control Systems" accepted at ESORICS 2022.
• 03/2022 [Service]: Honoured and excited to serve as a PC member for FAccT '22!
• 09/2021 [Service]: Served as a conference volunteer at a couple of conferences: EuroS&P '21 and SOUPS '21. Sadly, they were both virtual. Hoping to volunteer and attend in person soon!
• 04/2021 [Talk]: Speaking at The Web Conference 2021.
• 01/2021 [Paper]: "Towards a Lightweight, Hybrid Approach for Detecting DOM XSS Vulnerabilities with Machine Learning" accepted at The Web Conference 2021.
• 12/2020 [Paper]: "Biscotti: A Ledger for Private and Secure Peer-to-Peer Machine Learning" accepted in IEEE Transactions on Parallel and Distributed Systems (TPDS)!
• 11/2020 [Misc]: I was interviewed on the Data Skeptic Podcast about my research in sybil attacks on federated learning. Very fun and cool experience!
• 10/2020 [Talk]: Speaking at RAID 2020.
• 05/2020 [Paper]: "The Limitations of Federated Learning in Sybil Settings" presented at RAID 2020.
• 08/2019 [Misc]: Starting my PhD at CMU. The journey continues!
• 08/2019 [Talk]: Speaking at APSys 2019. Had a great time in Hangzhou, China!
• 07/2019 [Work]: My last day at Oasis Labs. Thank you so much for a great 7 months in California, and I'm so excited to see more great work in privacy-preserving technology coming from the team!
• 06/2019 [Poster]: "GainForest: Scaling Climate Finance for Forest Conservation using Interpretable Machine Learning on Satellite Imagery" at the ICML 2019, Climate Change: How Can AI Help? workshop in Long Beach.
• 04/2019 [Paper]: "Brokered Agreements in Multi-Party Machine Learning" accepted at APSys 2019.
• 02/2019 [Poster]: "Biscotti: A Ledger for Private and Secure Peer to Peer Machine Learning" at NSDI'19.
• 01/2019 [Work]: My first day working at Oasis Labs, a Berkeley blockchain startup founded by Professor Dawn Song. Excited to build technology that enables privacy-preserving data computation on the blockchain!
• 11/2018 [Misc]: Defended my masters thesis: "Dancing in the Dark: Private Multi-Party Machine Learning in an Untrusted Setting". The thesis has also been reformatted and posted on arXiv.
• 08/2018 [Paper]: A summer side project, "Mitigating Sybils in Federated Learning" is now on arXiv.
• 05/2018 [Award]: I'm honoured to receive both a UBC Computer Science Graduate TA Award and Department Student Service Award for the 2017 academic year. Thank you!
• 05/2018 [Talk]: I presented a poster and gave a talk on my research at the UBC CyberSecurity Summit. The video is available here.
• 04/2018 [Misc]: My term as the CSGSA president has ended. Thus marks the end of a fun year!
• 12/2017 [Talk]: I'm giving a talk at UofT, hosted by Prof. David Lie's group. Thank you for hosting me!
• 04/2017 [Misc]: I was elected as the president of the CSGSA.
• 09/2016 [Misc]: The genesis block. My first day at UBC as a new Master's student.