I'm Boel, and I'm passionate about learning. In fact, I like learning so much that I decided to work full-time with learning... which is why I'm a researcher!
When it comes to research, my favorite topic is privacy (in all forms and flavors). In particular, I have a soft spot for differential privacy. Generally, I like to explore holistic approaches to privacy. That is, I try to understand if and how computer systems can potentially leak information, and how we can go about either mitigating or quantifying the leakage.
Currently, I'm working as a postdoc at University of Copenhagen. Prior to joining UCPH, I was a postdoc in the Logic and Semantics group at Aarhus university, working on anonymous communication with Aslan Askarov. I earned my PhD (dissertation, topic: differential privacy) from Chalmers University of Technology. My PhD supervisor was David Sands.
- [Popular-science]: Anonymization is dead... and here is why
- [Conference presentation]: Efficient Error Prediction for Differentially Private Algorithms
- Boel Nelson, "Efficient Error Prediction for Differentially Private Algorithms", In The 16th International Conference on Availability, Reliability and Security (ARES 2021), August 17–20, 2021, Vienna, Austria. ACM, New York, NY, USA, 12 pages. https://doi.org/10.1145/3465481.3465746.
- Boel Nelson; Jenni Reuben, "SoK: Chasing Accuracy and Privacy, and Catching Both in Differentially Private Histogram Publication", Transactions on Data Privacy 13:3 (2020) 201-245.
- Mathias Johanson; Jonas Jalminger; Emmanuel Frecon; Boel Nelson; Tomas Olovsson; Mats Gjertz, "Joint Subjective and Objective Data Capture and Analytics for Automotive Applications", 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), Toronto, ON, 2017, pp. 1-5, doi: 10.1109/VTCFall.2017.8288366
- Boel Nelson; Tomas Olovsson, "Introducing Differential Privacy to the Automotive Domain: Opportunities and Challenges", 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), Toronto, ON, 2017, pp. 1-7, doi: 10.1109/VTCFall.2017.8288389.
- Boel Nelson; Tomas Olovsson, "Security and Privacy for Big Data: A Systematic Literature Review", 2016 IEEE International Conference on Big Data (Big Data), Washington, DC, 2016, pp. 3693-3702, doi: 10.1109/BigData.2016.7841037.
- Boel Nelson; Aslan Askarov, "With a Little Help from My Friends: Transport Deniability for Instant Messaging", arxiv preprint
- Boel Nelson, "Randori: Local Differential Privacy for All", arxiv preprint
- Boel Nelson; Jenni Reuben, "Survey of Differentially Private Accuracy Improving Techniques for Publishing Histograms and Synthetic Data", at PUT held in conjunction with PETS'19
- Boel Nelson, "Randori: Differentially Private Data Collection Made Accessible", at EuroS&P'19