2026 Sriram Sankaranarayanan: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	45	7139	6931	3129	3010	217	9464

Overview

Sriram Sankaranarayanan is affiliated with the University of Colorado Boulder in the United States. Their research spans multiple areas within computer science and engineering, focusing on both theoretical and applied aspects of the field.

Their work includes contributions to the following main fields of study:

Computer Science
Engineering

Within these fields, their publications address several subfields:

Artificial Intelligence
Computational Theory and Mathematics
Management Science and Operations Research
Software
Automotive Engineering

The core topics covered in their research include:

Formal Methods in Verification
Software Testing and Debugging Techniques
Adversarial Robustness in Machine Learning
Simulation Techniques and Applications
Machine Learning and Algorithms
Autonomous Vehicle Technology and Safety
Human-Automation Interaction and Safety

Sankaranarayanan has frequently published in venues such as:

arXiv (Cornell University)
Proceedings of the International Conference on Automated Planning and Scheduling
Diabetes Technology & Therapeutics
2022 IEEE 61st Conference on Decision and Control (CDC)
2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)

Frequent collaborators in their research include:

Georgios Fainekos
Emily Jensen
Brandon J. Pitts
Andrea Lodi
Kandai Watanabe

Some recent papers published by Sankaranarayanan demonstrate a range of topics and applications:

"Multi-Hour Blood Glucose Prediction in Type 1 Diabetes: A Patient-Specific Approach Using Shallow Neural Network Models," 2020, Diabetes Technology & Therapeutics
"Trajectory Tracking Control for Robotic Vehicles Using Counterexample Guided Training of Neural Networks," 2021, Proceedings of the International Conference on Automated Planning and Scheduling
"Local Repair of Neural Networks Using Optimization," 2021, arXiv (Cornell University)
"Learning fixed-complexity polyhedral Lyapunov functions from counterexamples," 2022, 2022 IEEE 61st Conference on Decision and Control (CDC)
"An Application of SAT Solvers in Integer Programming Games," 2025, arXiv (Cornell University)

In addition to journal and conference papers, Sankaranarayanan has contributed to book publications, including:

Tools and Algorithms for the Construction and Analysis of Systems, 2023, published by Springer Science+Business Media

Best Publications

Flow*: an analyzer for non-linear hybrid systems

Xin Chen;Erika Ábrahám;Sriram Sankaranarayanan

650
Citations
S-taliro: a tool for temporal logic falsification for hybrid systems

Yashwanth Annapureddy;Che Liu;Georgios Fainekos;Sriram Sankaranarayanan

541
Citations
Linear invariant generation using non-linear constraint solving

Michael A. Colon;Sriram Sankaranarayanan;Henny B. Sipma

466
Citations
Non-linear loop invariant generation using Gröbner bases

Sriram Sankaranarayanan;Henny B. Sipma;Zohar Manna

379
Citations
Specification-Based Monitoring of Cyber-Physical Systems: A Survey on Theory, Tools and Applications

Ezio Bartocci;Jyotirmoy V. Deshmukh;Alexandre Donzé;Georgios Fainekos

339
Citations
LOLA: runtime monitoring of synchronous systems

B. D'Angelo;S. Sankaranarayanan;C. Sanchez;W. Robinson

335
Citations
Output Range Analysis for Deep Feedforward Neural Networks

Souradeep Dutta;Susmit Jha;Sriram Sankaranarayanan;Ashish Tiwari

315
Citations
Scalable analysis of linear systems using mathematical programming

Sriram Sankaranarayanan;Henny B. Sipma;Zohar Manna

271
Citations
Taylor Model Flowpipe Construction for Non-linear Hybrid Systems

Xin Chen;Erika Abraham;Sriram Sankaranarayanan

257
Citations
Probabilistic Temporal Logic Falsification of Cyber-Physical Systems

Houssam Abbas;Georgios Fainekos;Sriram Sankaranarayanan;Franjo Ivančić

214
Citations
Probabilistic program analysis with martingales

Aleksandar Chakarov;Sriram Sankaranarayanan

204
Citations
Collecting Statistics Over Runtime Executions

Bernd Finkbeiner;Sriram Sankaranarayanan;Henny B. Sipma

177
Citations
Simulation-guided lyapunov analysis for hybrid dynamical systems

James Kapinski;Jyotirmoy V. Deshmukh;Sriram Sankaranarayanan;Nikos Arechiga

167
Citations
Monte-carlo techniques for falsification of temporal properties of non-linear hybrid systems

Truong Nghiem;Sriram Sankaranarayanan;Georgios Fainekos;Franjo Ivancić

164
Citations
Reachability analysis for neural feedback systems using regressive polynomial rule inference

Souradeep Dutta;Xin Chen;Sriram Sankaranarayanan

159
Citations
Fast and accurate static data-race detection for concurrent programs

Vineet Kahlon;Yu Yang;Sriram Sankaranarayanan;Aarti Gupta

158
Citations
Constraint-Based Linear-Relations Analysis

Sriram Sankaranarayanan;Henny B. Sipma;Zohar Manna

155
Citations
Static analysis in disjunctive numerical domains

Sriram Sankaranarayanan;Franjo Ivančić;Ilya Shlyakhter;Aarti Gupta

145
Citations
Falsification of temporal properties of hybrid systems using the cross-entropy method

Sriram Sankaranarayanan;Georgios Fainekos

144
Citations
Static analysis for probabilistic programs: inferring whole program properties from finitely many paths

Sriram Sankaranarayanan;Aleksandar Chakarov;Sumit Gulwani

141
Citations
Constructing invariants for hybrid systems

Sriram Sankaranarayanan;Henny B. Sipma;Zohar Manna

120
Citations

Frequent Co-Authors

Franjo Ivancic Google (United States)

Aarti Gupta Princeton University

Georgios Fainekos Arizona State University

Henny B. Sipma Aarno Labs

Zohar Manna Stanford University

Ashish Tiwari Microsoft (United States)

Fabio Somenzi University of Colorado Boulder

Antoine Girard University of Paris-Saclay

Sanjit A. Seshia University of California, Berkeley

Bernd Finkbeiner Saarland University

External Links

Personal website of Sriram Sankaranarayanan Google Scholar page

If you think any of the details on this page are incorrect, let us know.

Related Online Degrees & Career Pathways

Exploring computer science education in the USA offers students a range of flexible online degree pathways. For those seeking a head start, online associates programs are a popular entry point. These two-year degrees focus on foundational skills and can lead to entry-level tech jobs or serve as a stepping stone to a bachelor’s degree.

Graduate learners may benefit from the quickest online masters degree options available, helping students upskill and advance their careers with minimal time investment. It’s important to consider the most useful masters degrees, especially those in high demand fields like artificial intelligence, software engineering, and data science.

Cost is often a key consideration when choosing a pathway. Prospective students can research the cheapest online college options to minimize debt while maximizing educational value. By carefully exploring these online paths, students can tailor their journey to fit their personal goals, timelines, and budgets.