Susmit Jha

2.9k total citations · 1 hit paper
67 papers, 1.2k citations indexed

About

Susmit Jha is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Software. According to data from OpenAlex, Susmit Jha has authored 67 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Artificial Intelligence, 21 papers in Computational Theory and Mathematics and 10 papers in Software. Recurrent topics in Susmit Jha's work include Adversarial Robustness in Machine Learning (19 papers), Formal Methods in Verification (18 papers) and Machine Learning and Algorithms (9 papers). Susmit Jha is often cited by papers focused on Adversarial Robustness in Machine Learning (19 papers), Formal Methods in Verification (18 papers) and Machine Learning and Algorithms (9 papers). Susmit Jha collaborates with scholars based in United States, United Kingdom and Germany. Susmit Jha's co-authors include Ashish Tiwari, Sumit Gulwani, Sanjit A. Seshia, Sumit Kumar Jha, Ramarathnam Venkatesan, Ramarathnam Venkatesan, Wenchao Li, Souradeep Dutta, Alvaro Velasquez and Sriram Sankaranarayanan and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACM SIGPLAN Notices and Lecture notes in computer science.

In The Last Decade

Susmit Jha

63 papers receiving 1.1k citations

Hit Papers

Oracle-guided component-based program synthesis 2010 2026 2015 2020 2010 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Oracle-guided component-based program synthesis
    2010 299 citations Susmit Jha, Sumit Gulwani et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Susmit Jha United States 16 567 406 288 286 265 67 1.2k
Zachary Tatlock United States 19 586 1.0× 256 0.6× 256 0.9× 384 1.3× 370 1.4× 57 1.2k
Paolo Arcaini Japan 19 621 1.1× 598 1.5× 380 1.3× 271 0.9× 93 0.4× 147 1.3k
Roderick Bloem Austria 24 750 1.3× 810 2.0× 214 0.7× 1.1k 4.0× 306 1.2× 90 1.7k
Emina Torlak United States 19 636 1.1× 562 1.4× 477 1.7× 275 1.0× 447 1.7× 49 1.4k
Taolue Chen United Kingdom 18 449 0.8× 305 0.8× 383 1.3× 283 1.0× 60 0.2× 108 979
Jyotirmoy V. Deshmukh United States 16 376 0.7× 372 0.9× 102 0.4× 473 1.7× 159 0.6× 61 885
Shaoying Liu Japan 17 371 0.7× 780 1.9× 671 2.3× 216 0.8× 72 0.3× 137 1.3k
Natarajan Shankar United States 20 732 1.3× 379 0.9× 160 0.6× 768 2.7× 376 1.4× 53 1.3k
Vu Le United States 16 426 0.8× 922 2.3× 760 2.6× 167 0.6× 236 0.9× 43 1.4k
Alan J. Hu Canada 20 407 0.7× 346 0.9× 121 0.4× 524 1.8× 669 2.5× 73 1.3k

Countries citing papers authored by Susmit Jha

Since Specialization
Citations

This map shows the geographic impact of Susmit Jha's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Susmit Jha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Susmit Jha more than expected).

Fields of papers citing papers by Susmit Jha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Susmit Jha. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Susmit Jha. The network helps show where Susmit Jha may publish in the future.

Co-authorship network of co-authors of Susmit Jha

This figure shows the co-authorship network connecting the top 25 collaborators of Susmit Jha. A scholar is included among the top collaborators of Susmit Jha based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Susmit Jha. Susmit Jha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Spieß, C. Katharina, Michael Pradel, Mohammad Amin Alipour, et al.. (2025). Calibration and Correctness of Language Models for Code. 540–552. 4 indexed citations
2.
Lyu, Weimin, et al.. (2024). Task-Agnostic Detector for Insertion-Based Backdoor Attacks. 2808–2822. 4 indexed citations
3.
Jha, Sumit Kumar, et al.. (2024). Exploring the Predictive Capabilities of AlphaFold Using Adversarial Protein Sequences. IEEE Transactions on Artificial Intelligence. 5(7). 3384–3392. 4 indexed citations
4.
5.
6.
Jha, Sumit Kumar, Susmit Jha, Rickard Ewetz, & Alvaro Velasquez. (2024). Co-Synthesis of Code and Formal Models Using Large Language Models and Functors. 215–220. 1 indexed citations
7.
Jha, Susmit, Sumit Kumar Jha, & Alvaro Velasquez. (2024). Neuro-symbolic Generative AI Assistant for System Design. 75–76. 3 indexed citations
8.
Jha, Sumit Kumar, Susmit Jha, Rickard Ewetz, & Alvaro Velasquez. (2024). Solving Mystery Planning Problems Using Category Theory, Functors, and Large Language Models. 118–121. 1 indexed citations
9.
Jha, Susmit, et al.. (2023). Predicting Out-of-Distribution Performance of Deep Neural Networks Using Model Conformance. 19–28. 3 indexed citations
10.
Jha, Susmit & John Rushby. (2022). Inferring and Conveying Intentionality: Beyond Numerical Rewards to Logical Intentions. arXiv (Cornell University). 1 indexed citations
11.
Lee, Ritchie, et al.. (2020). NASA Formal Methods. Lecture notes in computer science. 1 indexed citations
12.
Jha, Susmit, Steven Lawrence Fernandes, Sumit Kumar Jha, et al.. (2019). Attribution-Based Confidence Metric For Deep Neural Networks. Neural Information Processing Systems. 32. 11826–11837. 19 indexed citations
13.
Jha, Susmit, Ashish Tiwari, Sanjit A. Seshia, Tuhin Sahai, & Natarajan Shankar. (2019). TeLEx: learning signal temporal logic from positive examples using tightness metric. Formal Methods in System Design. 54(3). 364–387. 23 indexed citations
14.
Ghosh, Arup, Faraz Hussain, Susmit Jha, Christopher J. Langmead, & Sumit Kumar Jha. (2014). Discovering rare behaviours in stochastic differential equations using decision procedures: applications to a minimal cell cycle model. International Journal of Bioinformatics Research and Applications. 10(4/5). 540–540. 1 indexed citations
15.
Hussain, Faraz, Sumit Kumar Jha, Susmit Jha, & Christopher J. Langmead. (2014). Parameter discovery in stochastic biological models using simulated annealing and statistical model checking. International Journal of Bioinformatics Research and Applications. 10(4/5). 519–519. 4 indexed citations
16.
Jha, Susmit, et al.. (2014). CAPED. 1–10. 14 indexed citations
17.
Seshia, Sanjit A. & Susmit Jha. (2012). Towards Automated System Synthesis Using SCIDUCTION. 17 indexed citations
18.
Jha, Sumit Kumar, et al.. (2012). Synthesis of insulin pump controllers from safety specifications using Bayesian model validation. International Journal of Bioinformatics Research and Applications. 8(3/4). 263–263. 3 indexed citations
19.
Gulwani, Sumit, Susmit Jha, Ashish Tiwari, & Ramarathnam Venkatesan. (2011). Synthesis of loop-free programs. ACM SIGPLAN Notices. 46(6). 62–73. 128 indexed citations
20.
Jha, Susmit, Sumit Gulwani, Sanjit A. Seshia, & Ashish Tiwari. (2010). Oracle-guided component-based program synthesis. 215–224. 299 indexed citations breakdown →

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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