Assistant Professor. IIIT Hyderabad, India
23, Himalaya Block-D
5th Floor, Software Engineering Research Center
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.
Karthik also poses more than 5 years of industrial experience as an employee and as a consultant in building and deploying ML products/services.
|Nov 11, 2022||Paper published in IEEE Software|
|Aug 10, 2022||I will be a PC member for ICSA 2023|
|Aug 10, 2022||I will be a PC Member for CAIN 2023 (Co-located with ICSE 2023)|
|Jul 13, 2022||Excited and honoured to have joined IIIT Hyderabad as an Assistant Professor|
|Jun 13, 2022||Happy to join the Organizing Committee of ICSA 2023 as a Webchair|
Agile4MLS - Leveraging Agile Practices for Developing Machine Learning-Enabled systems An Industrial ExperienceIn 2022
A Machine Learning Approach to Service Discovery for Microservice ArchitecturesIn Software Architecture - 15th European Conference, ECSA 2021, Virtual Event, Sweden, September 13-17, 2021, Proceedings 2021
Software Architecture for ML-based Systems: What Exists and What Lies AheadIn 1st IEEE/ACM Workshop on AI Engineering - Software Engineering for AI, WAIN@ICSE 2021, Madrid, Spain, May 30-31, 2021 2021
Quantitative Verification-Aided Machine Learning: A Tandem Approach for Architecting Self-Adaptive IoT SystemsIn 2020 IEEE International Conference on Software Architecture, ICSA 2020, Salvador, Brazil, March 16-20, 2020 2020