Janardan Misra - Homepage - Publications [Domain-Wise]

Publications (Domain-Wise)

Sustainable Enterprise AI, Reliability & Software Analytics

These publications address the core enterprise challenge of making AI-enabled and software-intensive systems measurable, reliable, cost-aware, and sustainable at scale. The work spans LLM inference energy, response-length efficiency, AI cost and carbon optimization, ML reliability, defect-log suitability, incident-repository mining, data-driven application maintenance, source-code clustering, knowledge transition, and software decision support.

Together, this category reflects a research agenda focused on moving AI and software intelligence from experimentation to governed enterprise deployment — where cost, reliability, maintainability, latency, energy use, and carbon impact are treated as first-class engineering and management concerns. It signals an ability to translate research into evaluation methods, optimization levers, operational intelligence, and enterprise-scale technology capabilities.

Janardan Misra, Vikrant Kaulgud, Adam Burden, Sanjay Podder. Rethinking Build vs. Buy Decisions in Enterprise Software: Navigating Trade-offs through a Structured Decision-Support Approach. Jun 2026. arXiv.
Soham Poddar, Paramita Koley, Janardan Misra, Niloy Ganguly, and Saptarshi Ghosh. Brevity is the soul of sustainability: Characterizing LLM response lengths. In Findings of the Association for Computational Linguistics: ACL 2025, pp. 21848–21864, Association for Computational Linguistics, Vienna, Austria, July 2025. Link.
Soham Poddar, Paramita Koley, Janardan Misra, Niloy Ganguly, and Saptarshi Ghosh. Towards Sustainable NLP: Insights from Benchmarking Inference Energy in Large Language Models. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1: Long Papers, pp. 12688–12704, Association for Computational Linguistics, Albuquerque, New Mexico, Apr 2025. Link.
Janardan Misra and Nisha R. Reliability Analysis of Machine Learning based Data-Driven Software. Tech Briefing Talk in the Innovation in Software Engineering Conference 2021 (ISEC'21).
Janardan Misra and Sanjay Podder. Association of Defect Log Suitability for Machine Learning with Performance: An Experience Report. In proceedings of the Innovation in Software Engineering Conference 2021 (ISEC'21), ACM.
Janardan Misra and Sanjay Podder. Mining Text in Incident Repositories: Experiences and Perspectives on Adopting Machine Learning Solutions in Practice. Presented in SEI'19 (First International Workshop on Software Engineering Intelligence - co-located with ASE'19), San Diego, CA, USA, Nov 2019.
Janardan Misra, et. al. Data-Driven Application Maintenance: Experience from the Trenches. In proceedings of the 4th International Workshop on Software Engineering Research and Industrial Practice (SER&IP), IEEE Press, pp. 48-54, May 2017. Link (arXiv).
Janardan Misra, KM Annervaz, Vikrant Kaulgud, Shubhashis Sengupta, and Gary Titus. Software Clustering: Unifying Syntactic and Semantic Features. In proceedings of the 19th Working Conference on Reverse Engineering (WCRE), IEEE, pp. 113-122, Kingston, Ontario, Canada, Oct 2012. Link (companion draft @ arXiv).
Vikrant Kaulgud, KM Annervaz, Janardan Misra, and Gary Titus. Comprehension Support during Knowledge Transitions: Learning from Field. In proceedings of the 22nd International Conference on Program Comprehension (ICPC '14), ACM, pp. 205-206, Hyderabad, India, 2014. Link.
Annervaz K M, Vikrant Kaulgud, Janardan Misra, Shubhashis Sengupta, Gary Titus, Azmat Munshi. Code Clustering Workbench. In proceedings of the 13th IEEE Source Code Analysis and Manipulation (SCAM), IEEE, pp. 31-36, 2013. Link.
(Invited Talk) Future of AI Enterprise. Agile and Automation Conclave 2018 at SolutionsIQ. Slides.

Enterprise NLP & Knowledge Systems

These publications address enterprise text as a strategic data asset by extracting meaning, entities, terminology, priorities, clusters, and semantic relationships from natural language. The category shows a sustained ability to convert NLP and information-retrieval research into enterprise-grade capabilities for requirements intelligence, search, ambiguity resolution, prioritization, and decision support.

Janardan Misra. Terminological Inconsistency Analysis of Natural Language Requirements. Information and Software Technology (IST), Vol. 74, pp. 183-193, Elsevier, June 2016. Link.
Janardan Misra and Subhabrata Das. Entity Disambiguation in Natural Language Text Requirements. In proceedings of the 20th Asia-Pacific Software Engineering Conference (APSEC), IEEE Computer Society, pp. 239-246, Dec 2-5, 2013, Bangkok, Thailand. Best Paper Award. Link.
Janardan Misra, Shubhashis Sengupta, and Sanjay Podder. Topic Cohesion Preserving Requirements Clustering. In proceedings of RAISE 2016 (5th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering), ACM, pages 22-28, 17th May 2016, Austin, TX, USA. Link.
Janardan Misra, Shubhashis Sengupta, and Subhabrata Das. Latent Semantic Centrality based Automated Requirements Prioritization. In proceedings of the 7th India Software Engineering Conference (ISEC '14), ACM, pp. 5:1-5:10, Feb 2014, Chennai, India. Link.

Formal Methods, Verification & Reliable Systems

These publications provide the formal and analytical foundations for reasoning about correctness, reliability, security, reachability, and system behavior. The work spans temporal logics, timeout models, real-time verification, model checking, ownership/declassification, collaborative security, threat modeling, and verification-oriented testing, signaling deep technical judgment in reliability-critical systems that is directly relevant to trustworthy AI and governed enterprise technology.

Suman Roy, Janardan Misra, and Indranil Saha. A Simplification of a Real-time Verification Problem. Software: Testing Verification and Reliability, Vol. 26, pp. 548-571, Wiley, Dec 2016. Link (arXiv).
Janardan Misra and Suman Roy. A Decidable Timeout based Extension of LTL. Journal of Applied Non-Classical Logics (JANCL), Vol. 24, Issue 3, pp. 262-291, Taylor & Francis, Nov 2014. Full Text.
Janardan Misra. A Framework for Specification and Verification of Timeout Models of Real-Time Systems. In proceedings of the 4th International Conference on Contemporary Computing (IC3), S. Aluru et al. (Eds.): CCIS vol. 168, pp. 146-157. Springer, Heidelberg, 2011. Link.
Indranil Saha, Janardan Misra, and Suman Roy. Timeout and Calendar based Finite State Modeling and Verification of Real-Time Systems. In proceedings of the 5th International Symposium on Automated Technology for Verification and Analysis (ATVA), LNCS, Vol. 4762, pp. 284-299, Springer, 2007. Link.
Janardan Misra and Suman Roy. Techniques for Distributed Reachability Analysis with Partial Order and Symmetry based Reductions. arXiv.
Janardan Misra. A Note on Digitization of Real-Time Models and Logics. arXiv.
Pradeep Kumar and Janardan Misra. Owners as Trusters: Trusted Ownership Declassification With Neighborhood. In proceedings of the 6th International Workshop on Aliasing, Capabilities and Ownership (IWACO '14), in association with ECOOP 2014, Uppsala, Sweden, July 2014. Full Text.
Amitabh Saxena, Janardan Misra, and Aritra Dhar. Increasing Anonymity in Bitcoin. In proceedings of BITCOIN 2014: 1st International Workshop on Bitcoin Research, Springer, LNCS, pp. 122-139, Mar 2014, Barbados. Full Text.
[Book Chapter] Janardan Misra. Towards a Framework for Collaborative Enterprise Security. In Threats, Countermeasures, and Advances in Applied Information Security, Manish Gupta, John Walp, and Raj Sharman, editors, IGI Global, Chap. 16, pp. 309-334, 2012. Link.
Janardan Misra and Indranil Saha. A Reinforcement Model for Collaborative Security and Its Formal Analysis. In proceedings of the New Security Paradigm Workshop (NSPW), ACM, pp. 101-114, 2009. Full Text.
Janardan Misra. A Recursive PLS (Partial Least Squares) based Approach for Enterprise Threat Management. arXiv.
C.P. Ravikumar, Janardan Mishra, Nirmalya Haldar, Kamal Kiran, and Senthil Arasu. Static Verification of Burn-in Test Vectors. TI Test Symposium, 2002.

Computational Social Science & AI for Social Good

These publications apply AI, social media analytics, and data-driven modeling to human-centered and societal problems, including public health, vaccine opinions, drug addiction, mental health, COVID-19 socioeconomic concerns, and social-good solution design. The category demonstrates the ability to connect AI methods with responsible technology, public-impact analytics, and complex socio-technical decision contexts.

Soham Poddar, Mainack Mondal, Janardan Misra, Niloy Ganguly, and Saptarshi Ghosh. Winds of Change: Impact of COVID-19 on Vaccine-Related Opinions of Twitter Users. In Proceedings of the 16th International AAAI Conference on Web and Social Media (ICWSM 2022), Vol. 16, pp. 782-793, AAAI Press, 2022.
Narendranath Sukhavasi, Janardan Misra, Vikrant Kaulgud, and Sanjay Podder. Geo-sentiment trends analysis of tweets in context of economy and employment during COVID-19. Journal of Computational Social Science, Vol. 6, pp. 411-441, Springer Nature, Mar 2023. Link.
Shalmoli Ghosh, Janardan Misra, Saptarshi Ghosh, and Sanjay Podder. Utilizing Social Media for Identifying Drug Addiction and Recovery Intervention. In the International Workshop on Data Analytics for Smart Health (DASH 2020: IEEE BigData).
(Invited Talk) Social Media Analytics for Mental Health: Opportunities and Challenges. Sixth Social Networking Workshop @ COMSNETS 2019. Link.
Janardan Misra, Divya Rawat, and Sanjay Podder. Designing Data-Driven Solutions for Societal Problems: Challenges and Approaches. In proceedings of the ECML PKDD 2018 Workshops, Lecture Notes in Computer Science, vol. 11329, pp. 134-144, Springer, Dublin, Ireland. Link.
Sanjay Podder, Janardan Misra, et al. Designing Intelligent Automation based Solutions for Complex Social Problems. Presented in ICML 2016 workshop #Data4Good (Machine Learning in Social Good Applications), New York City, USA. Link (Full Text).
Anjeline Daniel and Janardan Misra. Understanding Suicides in India: a Socio-Cultural Perspective. Accepted for presentation in the 2nd International Conference on Mental Health and Cultural Psychiatry, Sydney, Australia, 2005.

Complex Systems, Artificial Life & Theoretical Computing

These publications capture the deeper theoretical foundations of the portfolio, spanning artificial life, complex systems, emergence, observability, theoretical computing, DNA computing, probabilistic fusion, 3-SAT, quantum-software decision support, and neural-network hardware foundations. The category signals long-horizon research judgment: the ability to formulate future-facing technical questions, reason about emerging computational paradigms, and connect foundational work to later AI systems thinking.

Janardan Misra and Vikrant Kaulgud. When to Build Quantum Software? Presented in Software Engineering Research in India (SERI) 2021.
Janardan Misra and Indranil Saha. Artificial Neural Networks in Hardware: A Survey of Two Decades of Progress. Neurocomputing, vol. 74, pp. 239-255, Elsevier, 2010. Link (Full Text).
Janardan Misra. A Calculus of Incomplete Fusions. The Computer Journal, Vol. 57(7), pp. 1105-1116, Oxford University Press, July 2014. Full Text (Link).
Subhas Kumar Ghosh and Janardan Misra. A Randomized Algorithm for 3-SAT. Mathematics in Computer Science, special issue Advances in Combinatorial Algorithms II, Birkhauser Base/Springer, Vol. 3, No. 4, pp. 421-431, 2010. (Link) [arXiv].
Gabriel Ciobanu and Janardan Misra. Performance Analysis and Name Passing Errors in Probabilistic Fusion. Scientific Annals of Computer Science, A.I. Cuza University Press, Vol. XVI, pp. 57-76, 2005. Link (Slides).
Rana Barua and Janardan Misra. Binary Arithmetic for DNA Computers. Revised Papers from the 8th International Workshop on DNA Based Computers: DNA Computing (DNA8), Masami Hagiya and Azuma Ohuchi (Eds.), LNCS, Vol. 2568, pp. 124-132, Springer, UK, 2003. Link (Pre-print) [Slides].
Janardan Misra. Observing Evolution in Artificial Life Studies: Algorithmic Considerations. Accepted in the IEEE Symposium on Artificial Life (IEEE-Alife '13), 2013. Program.
Janardan Misra. Algorithmic Feasibility of Entity Recognition in Artificial Life. In proceedings of the 10th European Conference on Artificial Life (ECAL '11), G. Kampis, I. Karsia, and E. Szatmary (Eds.), Part II, LNCS vol. 5778, pp. 246-253, Springer, 2011. Link.
[Monograph] Janardan Misra. Observing Artificial Life: An Abstract Algorithmic Framework. LAMBERT Academic Publishing, Saarbrucken, Germany, ISBN-13: 978-3-8454-1546-8, 2011. Link.
Janardan Misra. Algorithmic Feasibility of Observing Artificial Life Evolution. In proceedings of the 12th International Conference on Synthesis and Simulation of Living Systems (Alife XII), Odense, Denmark, MIT Press, pp. 889-896, 2010. Full Text (Link).
Martin Henz and Janardan Misra. Towards a Framework for Observing Artificial Life Forms. In proceedings of the 1st IEEE Symposium on Artificial Life (IEEE-Alife '07), IEEE Computational Intelligence Society, pp. 23-30, 2007. Link, extended draft @ arXiv.
Janardan Misra. An Inductive Formalization of Self Reproduction in Dynamical Hierarchies. In proceedings of the 10th International Conference on the Simulation and Synthesis of Living Systems (ALife X), pp. 553-558, MIT Press, 2006. arXiv.
Janardan Misra. Observing Artificial Life Evolution: A Formal Algebraic Framework. Master's Thesis, Department of Computer Science, National University of Singapore, 2005. Link.
Janardan Misra. Design of a P System based Artificial Graph Chemistry. arXiv.
Janardan Misra. Thoughts on a Unified Framework for Artificial Chemistries. arXiv.

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