Publications

We’ve published in many reputed conferences and journals such as

, , , , , International Conference on Automated Software Engineering (ASE) and ACM Symposium on Applied Computing (SAC).

Our Recent Publications

  1. Bhatt, Hiya, Sahil, Karthik Vaidhyanathan, Rahul Biju, Deepak Gangadharan, Ramona Trestian, and Purav Shah. “Architecting Digital Twins for Intelligent Transportation Systems.” Workshop at the 2025 IEEE International Conference on Software Architecture (ICSA 2025). arXiv.

  2. Matathammal, Akhila, Kriti Gupta, Larissa Lavanya, Ananya Vishal Halgatti, Priyanshi Gupta, and Karthik Vaidhyanathan. “EdgeMLBalancer: A Self-Adaptive Approach for Dynamic Model Switching on Resource-Constrained Edge Devices.” Workshop at the 2025 IEEE International Conference on Software Architecture (ICSA 2025). arXiv.

  3. Arun, Shrikara, Tedla, Meghana, and Karthik Vaidhyanathan. “LLMs for Generation of Architectural Components: An Exploratory Empirical Study in the Serverless World” accepted at the 2025 IEEE International Conference on Software Architecture (ICSA 2025). Read the preprint.

2024

  1. Vaidhyanathan, Karthik, Mauro Caporuscio, Stefano Florio, and Henry Muccini. “ML-Enabled Service Discovery for Microservice Architecture: a QoS Approach.” In Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, SAC 2024, Avila, Spain, April 8-12, 2024, edited by Jiman Hong and Juw Won Park, 1193–1200. ACM, 2024. https://doi.org/10.1145/3605098.3635942.
  2. Marda, Arya, Shubham Kulkarni, and Karthik Vaidhyanathan. “SWITCH: An Exemplar for Evaluating Self-Adaptive ML-Enabled Systems.” In Proceedings of the 19th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2024, Lisbon, Portugal, April 15-16, 2024, edited by Luciano Baresi, Xiaoxing Ma, and Liliana Pasquale, 143–49. ACM, 2024. https://doi.org/10.1145/3643915.3644105.
  3. Viswanadh, K. S., Akshit Gureja, Nagesh Walchatwar, Rishabh Agrawal, Shiven Sinha, Sachin Chaudhari, Karthik Vaidhyanathan, et al. “Engineering End-to-End Remote Labs Using IoT-Based Retrofitting.” CoRR abs/2402.05466 (2024). https://doi.org/10.48550/ARXIV.2402.05466.
  4. Marda, Arya, Shubham Kulkarni, and Karthik Vaidhyanathan. “SWITCH: An Exemplar for Evaluating Self-Adaptive ML-Enabled Systems.” CoRR abs/2402.06351 (2024). https://doi.org/10.48550/ARXIV.2402.06351.
  5. Dhar, Rudra, Karthik Vaidhyanathan, and Vasudeva Varma. “Can LLMs Generate Architectural Design Decisions? -An Exploratory Empirical Study.” CoRR abs/2403.01709 (2024). https://doi.org/10.48550/ARXIV.2403.01709.
  6. Bhatt, Hiya, Shrikara Arun, Adyansh Kakran, and Karthik Vaidhyanathan. “Towards Architecting Sustainable MLOps: A Self-Adaptation Approach.” CoRR abs/2404.04572 (2024). https://doi.org/10.48550/ARXIV.2404.04572.
  7. Donakanti, Raghav, Prakhar Jain, Shubham Kulkarni, and Karthik Vaidhyanathan. “Reimagining Self-Adaptation in the Age of Large Language Models.” CoRR abs/2404.09866 (2024). https://doi.org/10.48550/ARXIV.2404.09866.
  8. Tedla, Meghana, Shubham Kulkarni, and Karthik Vaidhyanathan. “EcoMLS: A Self-Adaptation Approach for Architecting Green ML-Enabled Systems.” CoRR abs/2404.11411 (2024). https://doi.org/10.48550/ARXIV.2404.11411.

2023

  1. Alipour, Mina, Mahyar Tourchi Moghaddam, Karthik Vaidhyanathan, and Mikkel Baun Kjærgaard. “Emoticontrol: Emotions-Based Control of User-Interfaces Adaptations.” Proc. ACM Hum. Comput. Interact. 7, no. EICS (2023): 1–29. https://doi.org/10.1145/3593227.
  2. Karre, Sai Anirudh, Karthik Vaidhyanathan, and Y. Raghu Reddy. “A Tool Based Experiment to Teach Elicitation and Specification Of Virtual Reality Product Requirements.” In Proceedings of the ACM Conference on Global Computing Education Vol 2, CompEd 2023, Hyderabad, India, December 5-9, 2023, edited by Venkatesh Choppella, Deepak B. Phatak, Andrew Luxton-Reilly, and Michelle Craig, 195. ACM, 2023. https://doi.org/10.1145/3617650.3624936.
  3. Alipour, Mina, Mahyar Tourchi Moghaddam, Karthik Vaidhyanathan, Tobias Kristensen, and Nicolai Krogager Asmussen. “Emotional Internet of Behaviors: A QoE-QoS Adjustment Mechanism.” In Artificial Intelligence in HCI - 4th International Conference, AI-HCI 2023, Held as Part of the 25th HCI International Conference, HCII 2023, Copenhagen, Denmark, July 23-28, 2023, Proceedings, Part I, edited by Helmut Degen and Stavroula Ntoa, 14050:3–22. Lecture Notes in Computer Science. Springer, 2023. https://doi.org/10.1007/978-3-031-35891-3_1.
  4. Kulkarni, Shubham, Arya Marda, and Karthik Vaidhyanathan. “Towards Self-Adaptive Machine Learning-Enabled Systems Through QoS-Aware Model Switching.” In 38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023, Luxembourg, September 11-15, 2023, 1721–25. IEEE, 2023. https://doi.org/10.1109/ASE56229.2023.00172.
  5. Alipour, Mina, Mahyar Tourchi Moghaddam, Karthik Vaidhyanathan, and Mikkel Baun Kjærgaard. “Toward Changing Users Behavior with Emotion-Based Adaptive Systems.” In Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2023, Limassol, Cyprus, June 26-29, 2023, 85–95. ACM, 2023. https://doi.org/10.1145/3565472.3595614.
  6. Gureja, Akshit, Rishabh Agrawal, Sachin Chaudhari, Karthik Vaidhyanathan, and Venkatesh Choppella. “Software Architecture for Multi-User Multiplexing to Enhance Scalability in IoT-Based Remote Labs.” In 9th IEEE World Forum on Internet of Things, WF-IoT 2023, Aveiro, Portugal, October 12-27, 2023, 1–7. IEEE, 2023. https://doi.org/10.1109/WF-IOT58464.2023.10539512.
  7. Pranavasri, VJS, Leo Francis, Ushasri Mogadali, Gaurav Pal, SVSLN Surya Suhas Vaddhiparthy, Anuradha Vattem, Karthik Vaidhyanathan, and Deepak Gangadharan. “Scalable and Interoperable Distributed Architecture for IoT in Smart Cities.” In 9th IEEE World Forum on Internet of Things, WF-IoT 2023, Aveiro, Portugal, October 12-27, 2023, 1–6. IEEE, 2023. https://doi.org/10.1109/WF-IOT58464.2023.10539501.
  8. Kulkarni, Shubham, Arya Marda, and Karthik Vaidhyanathan. “Towards Self-Adaptive Machine Learning-Enabled Systems Through QoS-Aware Model Switching.” CoRR abs/2308.09960 (2023). https://doi.org/10.48550/ARXIV.2308.09960.
  9. Lewis, Grace A., Henry Muccini, Ipek Ozkaya, Karthik Vaidhyanathan, Roland Weiss, and Liming Zhu. “Software Architecture and Machine Learning (Dagstuhl Seminar 23302).” Dagstuhl Reports 13, no. 7 (2023): 166–88. https://doi.org/10.4230/DAGREP.13.7.166.

2022

  1. Vaidhyanathan, Karthik, Anish Chandran, Henry Muccini, and Regi Roy. “Agile4MLS - Leveraging Agile Practices for Developing Machine Learning-Enabled Systems: An Industrial Experience.” IEEE Softw. 39, no. 6 (2022): 43–50. https://doi.org/10.1109/MS.2022.3195432.
  2. Menna, Federico Di, Henry Muccini, and Karthik Vaidhyanathan. “FEAST: a Framework for Evaluating Implementation Architectures Of Self-Adaptive IoT Systems.” In SAC ’22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25 - 29, 2022, edited by Jiman Hong, Miroslav Bures, Juw Won Park, and Tomás Cerný, 1440–47. ACM, 2022. https://doi.org/10.1145/3477314.3507146.

2021

  1. Caporuscio, Mauro, Marco De Toma, Henry Muccini, and Karthik Vaidhyanathan. “A Machine Learning Approach to Service Discovery for Microservice Architectures.” In Software Architecture - 15th European Conference, ECSA 2021, Virtual Event, Sweden, September 13-17, 2021, Proceedings, edited by Stefan Biffl, Elena Navarro, Welf Löwe, Marjan Sirjani, Raffaela Mirandola, and Danny Weyns, 12857:66–82. Lecture Notes in Computer Science. Springer, 2021. https://doi.org/10.1007/978-3-030-86044-8_5.
  2. Abughazala, Moamin, Mahyar Tourchi Moghaddam, Henry Muccini, and Karthik Vaidhyanathan. “Human Behavior-Oriented Architectural Design.” In Software Architecture - 15th European Conference, ECSA 2021, Virtual Event, Sweden, September 13-17, 2021, Proceedings, edited by Stefan Biffl, Elena Navarro, Welf Löwe, Marjan Sirjani, Raffaela Mirandola, and Danny Weyns, 12857:134–43. Lecture Notes in Computer Science. Springer, 2021. https://doi.org/10.1007/978-3-030-86044-8_9.
  3. Muccini, Henry, and Karthik Vaidhyanathan. “Software Architecture for ML-Based Systems: What Exists and What Lies Ahead.” In 1st IEEE/ACM Workshop on AI Engineering - Software Engineering for AI, WAIN@ICSE 2021, Madrid, Spain, May 30-31, 2021, 121–28. IEEE, 2021. https://doi.org/10.1109/WAIN52551.2021.00026.
  4. De Sanctis, Martina, Henry Muccini, and Karthik Vaidhyanathan. “A User-Driven Adaptation Approach for Microservice-Based IoT Applications.” In IoT ’21: 11th International Conference on the Internet of Things, St. Gallen, Switzerland, November 8 - 12, 2021, 48–56. ACM, 2021. https://doi.org/10.1145/3494322.3494329.
  5. Muccini, Henry, and Karthik Vaidhyanathan. “Software Architecture for ML-Based Systems: What Exists and What Lies Ahead.” CoRR abs/2103.07950 (2021). https://arxiv.org/abs/2103.07950.
  6. Vaidhyanathan, Karthik, Antonio Bruno, Eleonora Mendola, Filippo Mignosi, Mahyar Tourchi Moghaddam, Henry Muccini, and Monica Nesi. “A Service for Supporting Digital and Immersive Cultural Experiences.” CoRR abs/2109.07900 (2021). https://arxiv.org/abs/2109.07900.
  7. Moghaddam, Mahyar Tourchi, Moamin B. Abughazala, Vittorio Cortellessa, Antinisca Di Marco, Henry Muccini, Fabrizio Rossi, and Karthik Vaidhyanathan. “Architecture Design for Human-Driven Systems.” CoRR abs/2109.10073 (2021). https://arxiv.org/abs/2109.10073.

2020

  1. Cámara, Javier, Henry Muccini, and Karthik Vaidhyanathan. “Quantitative Verification-Aided Machine Learning: A Tandem Approach for Architecting Self-Adaptive IoT Systems.” In 2020 IEEE International Conference on Software Architecture, ICSA 2020, Salvador, Brazil, March 16-20, 2020, 11–22. IEEE, 2020. https://doi.org/10.1109/ICSA47634.2020.00010.
  2. De Sanctis, Martina, Henry Muccini, and Karthik Vaidhyanathan. “Data-Driven Adaptation in Microservice-Based IoT Architectures.” In 2020 IEEE International Conference on Software Architecture Companion, ICSA Companion 2020, Salvador, Brazil, March 16-20, 2020, 59–62. IEEE, 2020. https://doi.org/10.1109/ICSA-C50368.2020.00019.
  3. Muccini, Henry, and Karthik Vaidhyanathan. “Leveraging Machine Learning Techniques for Architecting Self-Adaptive IoT Systems.” In IEEE International Conference on Smart Computing, SMARTCOMP 2020, Bologna, Italy, September 14-17, 2020, 65–72. IEEE, 2020. https://doi.org/10.1109/SMARTCOMP50058.2020.00029.
  4. ———. “Towards Self-Learnable Software Architectures.” ERCIM News 2020, no. 122 (2020). https://ercim-news.ercim.eu/en122/special/towards-self-learnable-software-architectures.

2019

  1. Muccini, Henry, and Karthik Vaidhyanathan. “ArchLearner: Leveraging Machine-Learning Techniques for Proactive Architectural Adaptation.” In Proceedings of the 13th European Conference on Software Architecture, ECSA 2019, Paris, France, September 9-13, 2019, Companion Proceedings (Proceedings Volume 2), edited by Laurence Duchien, Anne Koziolek, Raffaela Mirandola, Martı́nez Elena Maria Navarro, Clément Quinton, Riccardo Scandariato, Patrizia Scandurra, Catia Trubiani, and Danny Weyns, 38–41. ACM, 2019. https://doi.org/10.1145/3344948.3344962.
  2. ———. “A Machine Learning-Driven Approach for Proactive Decision Making In Adaptive Architectures.” In IEEE International Conference on Software Architecture Companion, ICSA Companion 2019, Hamburg, Germany, March 25-26, 2019, 242–45. IEEE, 2019. https://doi.org/10.1109/ICSA-C.2019.00050.