Geeticka Chauhan is a PhD student focused on machine learning in healthcare. Chauhan works in CSAIL’s Clinical Decision Making Group with Dr. Peter Szolovits. Prior to CSAIL, Chauhan completed her undergraduate degree at Florida International University in Miami.

During Chauhan’s tenure at Florida International University, she worked on various AI related projects, one of which was in the domain of Natural Language Processing. Chauhan’s supervisor encouraged and motivated her to pursue a PhD in AI related fields.

Chauhan learned there was a vast variety of ML related research going on at CSAIL. She chose to apply because she thought that the EECS program would offer her the greatest flexibility to explore her research interests. After applying to MIT, she eventually found her home at CSAIL.

Dr. Szolovits advises Chauhan at CSAIL. She mentions how he encourages his students to pursue their own passions and gently guides everyone in the right direction.

“My group is highly motivated and working on a breadth of problems from Medical Imaging, Natural Language Processing and Machine Learning for Healthcare,” she said. “They successfully lead multiple projects and motivate me to be productive in my research, while providing helpful comments on presentation style.”

Like so many students, Chauhan’s education path has impacted her research interests. While she began her research journey with Natural Language Processing-related projects, she found herself fascinated by the healthcare domain working in Dr. Szolovits’ group. Her current interests lie in joint representation learning of chest radiographs and radiology reports towards the goal of patient disease trajectory mapping.

“My research will help doctors in more effectively providing care to their patients by accessing relevant radiographs and reports from the patient history, and be able to access a prediction of disease assessment from a machine learning model,” Chauhan said.

Chauhan’s research is driven highly by the technical insights her work could produce, and the rich collaborations between clinicians and machine learning researchers.

“I often think about the technical and clinical concepts that I could learn through the project that I undertake, and this gets me excited to wake up for a new day of research,” Chauhan said. “Another guiding factor for my research is the real-world impact in revolutionizing healthcare through the use of machine learning, which would allow clinicians to focus their attention on patient interaction as opposed to database manipulation.”

Outside of research, Chauhan has represented graduate students by serving as a student advisor to President Rafael Reif on MIT’s Presidential Advisory Cabinet. The cabinet discusses issues relevant to the MIT community and administration. Through the course of this advisory panel, Chauhan has been able to discuss student voices throughout several offices on campus, including the International Students Office, College of Computing and Student Life.

“As an incoming leader of Sidney Pacific graduate dormitory, I will represent voices of 700 graduate students to the administration and to the Graduate Student Council.” Chauhan said. “During the time of the [COVID-19] crisis, I have worked towards bringing the community together by organizing virtual events to help students connect with each other and get back to normalcy faster.”

Chauhan hasn’t decided her next move after CSAIL. She is debating between academia and industry at the moment but says her dream job involves motivating people, fostering learning, as well as technical contributions. While not directly related to her research, Chauhan has worked on streamlining EHR data extraction for the MIMIC dataset commonly used in clinical ML (

Additionally, you can read more about Chauhan’s master’s work related to streamlining Relation Extraction for the medical domain here: