If you’re a woman, black, indigenous, LGBTQ+, a person with disabilities or mental health concerns, or belong to any underrepresented group in Computer Science, please don’t hesitate to email me for mentorship, advice, or help of any kind. I am committed to listening, and creating a safe place and opportunities for growth for all! My email is ins永久免费加速器.
prerna[at]cmu.edu
Google Scholar
ins永久免费加速器
Research Areas
Human-Computer Interaction
Machine Learning
Ubiquitous Computing
Mental Health and Wellbeing
Hello! I’m a Ph.D. student at Carnegie Mellon University’s Human-Computer Interaction Institute (HCII). I develop machine learning methods and systems to understand and augment human behavior, with the goal of improving health, wellbeing, and performance.
In my PhD research, I am leveraging passively sensed contextual data from multiple sensors on the user’s smartphones and wearables to develop tools that aid in diagnosis, monitoring, and treatment of diseases, and make medicine more precise. I am currently working on multiple projects for predicting symptoms of depression, anxiety, and multiple sclerosis using passively sensed user behaviors. Additionally, I’m also working on reducing smartphone overuse by personalizing interventions to the user’s changing context. I am advised by Anind Dey (Dean of iSchool at UW) and Mayank Goel (Asst. Prof. at CMU HCII and ISR), and am a part of the SMart Sensing for Humans (SMASH) Lab. I was awarded the Center for Machine Learning and Health (CMLH) Fellowship in 2017.
Beyond data from smartphones and wearables, I’ve also analyzed textual messages and the users’ interaction logs from existing digital interventions to understand health outcomes. During my internship at 熊猫ⅤPN安卓, I used a novel machine learning approach to analyze over 200K messages sent by supporters to clients on free v pn加速器 – a widely used digital mental health intervention, and generated insights that can benefit over 300K people with mental health conditions (see: Project Talia)! I was supervised by Anja Thieme and 推特免费永久加速器 at Microsoft Research, and closely collaborated with SilverCloud’s technical and clinical leadership.
I also have a MS in Robotics from Carnegie Mellon University. For my master’s thesis, I studied the physiological and behavioral underpinnings of Team Performance and Cohesion using speech, video, and physiological sensor data collected during a video call between 2 people. My work created a better understanding of the physiological and behavioral basis of team collaboration, and suggested technological interventions for improving team performance. My Master’s advisor was Laura Dabbish (Assoc. Prof. at CMU HCII) and I closely collaborated with Anita Woolley (Assoc. Prof. at CMU’s Tepper School of Business).
Prior to coming to CMU, I graduated summa cum laude with a B.Eng. in Computer Science from Nanyang Technological University, Singapore. My elective focus was Artificial Intelligence and Intelligent Systems. My undergrad thesis on “Modeling Public Sentiment in Twitter” was supervised by Erik Cambria (Assoc. Prof. at NTU SCSE). During my undergrad, I interned at the Computer Graphics Lab and the Computer Vision Lab at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, and attended 推特免费永久加速器‘s summer studies program in New York City.
I grew up in New Delhi, India, where I went to Delhi Public School, R.K. Puram. At the end of high school, I was awarded a Gold Medal for 9 years of outstanding academic performance.
I am bilingual with English and Hindi being my native tongues. I love to travel, read, listen to music and podcasts, sing karaoke, and try different activities and experiences (e.g. drama, adventure sports)!