Pardis Emami-Naeini, Ph.D.
pardis at cs dot washington dot edu
I am currently a postdoctoral scholar in the School of Computer Science at University of Washington (UW), working with Prof. Yoshi Kohno and Prof. Franzi Roesner. Prior to UW, I received my PhD and MSc in Computer Science at Carnegie Mellon University (CMU) under Prof. Lorrie Cranor and Prof. Yuvraj Agarwal in 2020 and 2018, respectively.
At CMU, I was working on devising tools and methods to better inform people's privacy and security decision-making in the world of Internet of Things (IoT). During the summer of 2019, I completed an awesome research internship at the Cryptography and Privacy Research group under Kristin Lauter and Kim Laine, and in Summer 2017, I completed another fantastic internship at Intel Corporation under Mohammad Reza Haghighat. Prior to CMU, I received my BSc in Computer Engineering from Sharif University of Technology in Tehran, Iran in 2015, where I was advised by Prof. Ali Movaghar.
Best Paper Award
Over the years, I have worked with many amazing, smart, and creative undergraduate and graduate students at CMU and UW, including:
IoT consumers are concerned about the privacy and security of their smart devices, but they cannot do much about it at the time of purchase as such information is not available to them when making a purchase decision, at least in the United States and most countries. In the past few years, countries such as Finland, UK, and Singapore started designing a label for IoT devices to inform consumers about the privacy and security practices of smart devices at the point of sale. We believe US consumers have the same right to know what their devices are doing with their information, therefore we decided to bring this much-needed transparency to consumers at the time of purchase.
By conducting a series of studies and incorporating inputs from thousands of consumers and experts, we developed an informative and usable privacy and security label for IoT devices. In addition, to help manufacturers easily create these labels for their products, we developed a tool to generate the human and machine readable formats of the labels. Unlike other international efforts in labeling IoT devices, our labels are designed in such a way to not only inform consumers’ purchase decision making, but also to educate the average consumers about the most critical privacy and security information about their devices.
If you are interested in knowing more, check out our project website.
For as long as I remember, doodling has been a meditation for me. I draw chaos and find meaning in it.