Karthik Vaidhyanathan

Assistant Professor. IIIT Hyderabad, India

karthik_circle_profile.png

509, 5th Floor

Software Engineering Research Center, Himalaya Block-D

IIIT Hyderabad, Gachibowli, India 500032

Karthik Vaidhyanathan is an Assistant Professor at the Software Engineering Research Center, IIIT-Hyderabad, India where he is also associated with the leadership team of smart city living lab. He obtained his Ph.D. from the Gran Sasso Science Institute, Italy and did his postdoc at the University of L’Aquila, Italy. His main research interests lie in the intersection of software architecture and machine learning with a specific focus on building sustainable software systems. His research focuses on how machine learning techniques can be leveraged to better architect self-adaptive systems and further how to better define architecting practices for developing Machine Learning-enabled software systems. As a part of his research activities, he serves as a reviewer/organizing committee member in various workshops, conferences, and journals. He is also an editorial board member (SE Radio) of IEEE Software

Karthik also poses more than 5 years of industrial experience as an employee and as a consultant in building and deploying ML products/services.

selected publications

  1. Agile4MLS - Leveraging Agile Practices for Developing Machine Learning-Enabled systems An Industrial Experience
    Vaidhyanathan, Karthik, Chandran, Anish, Muccini, Henry, and Roy, Regi
    In 2022
  2. A Machine Learning Approach to Service Discovery for Microservice Architectures
    Caporuscio, Mauro, Toma, Marco De, Muccini, Henry, and Vaidhyanathan, Karthik
    In Software Architecture - 15th European Conference, ECSA 2021, Virtual Event, Sweden, September 13-17, 2021, Proceedings 2021
  3. Software Architecture for ML-based Systems: What Exists and What Lies Ahead
    Muccini, Henry, and Vaidhyanathan, Karthik
    In 1st IEEE/ACM Workshop on AI Engineering - Software Engineering for AI, WAIN@ICSE 2021, Madrid, Spain, May 30-31, 2021 2021
  4. Quantitative Verification-Aided Machine Learning: A Tandem Approach for Architecting Self-Adaptive IoT Systems
    Cámara, Javier, Muccini, Henry, and Vaidhyanathan, Karthik
    In 2020 IEEE International Conference on Software Architecture, ICSA 2020, Salvador, Brazil, March 16-20, 2020 2020