CARAML Lab effiCient, fAir, Robust, and Active ML Lab


We are a diverse team of highly motivated and collaborative researchers working on various aspects of machine learning, focusing on going beyond accuracy and achieving other desiderata such as compute and memory efficiency, human interaction, label efficiency, robustness, fairness, etc. As a team, we value all our members’ diverse views and experiences, and they strengthen us. Thanks to a caring team, we have a friendly, inclusive, and healthy environment in our lab. For each team member, success means something different, and we encourage each other to develop and pursue individual passions. Our current team includes graduate students, undergraduate students.

Currently, we are seeking highly motivated students with a broad interest in machine learning and optimization in general. In addition, if you are interested in our work and want to discuss it further, please do not hesitate to contact us. In addition, we welcome collaborations with researchers on the topics of Efficient ML, Active Learning, Semi-Supervised Learning, Robust and Fair ML.

Join the Team


  • Independent Study Students at UT Dallas (one semester of research supervised by me)

    • Ayush Dobhal, Jiten Girdhar, Savan Visalpara
  • M.Tech Students at IIT Bombay (Co-supervised with Ganesh Ramakrishnan)

    • Sandeep Subramanian, Sukalyan Bhakat, Abhishek Rathore, Jatin Mittal, Narsimha Raju
  • Former Interns

    • Khoshrav Doctor, Pratik Dubal, Rohan Mahadev, Vivswan Shitole, David Golub, John Moore

Collaborations (Active)

  • Sriraam Natarajan (UT Dallas)

  • Feng Chen (UT Dallas)

  • Murat Kantarcioglu (UT Dallas)

  • Ganesh Ramakrishnan (IIT Bombay)

  • Abir De (IIT Bombay)

  • Himanshu Asanani (TIFR, Bombay)

  • Sumit Shekhar (Adobe)

  • Pradeep Shenoy (Google)

  • Gaurav Aggarwal (Google)

  • Ashish Tendulkar (Google)

  • Lucian Popa (IBM)

  • Marina Danilevsky (IBM)

  • Baharan Mirzasoleiman (UCLA)

  • Jeff Bilmes (University of Washington, Seattle)

  • John Halloran (UC Davis)

  • Matthai Philipose (Microsoft Research)