P. S. Sastry

8.5k total citations · 2 hit papers
129 papers, 5.5k citations indexed

About

P. S. Sastry is a scholar working on Artificial Intelligence, Molecular Biology and Computer Networks and Communications. According to data from OpenAlex, P. S. Sastry has authored 129 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Artificial Intelligence, 37 papers in Molecular Biology and 17 papers in Computer Networks and Communications. Recurrent topics in P. S. Sastry's work include Machine Learning and Algorithms (15 papers), Optimization and Search Problems (14 papers) and Lipid metabolism and biosynthesis (13 papers). P. S. Sastry is often cited by papers focused on Machine Learning and Algorithms (15 papers), Optimization and Search Problems (14 papers) and Lipid metabolism and biosynthesis (13 papers). P. S. Sastry collaborates with scholars based in India, United States and Canada. P. S. Sastry's co-authors include M.A.L. Thathachar, M. Kates, Aritra Ghosh, Himanshu Kumar, Unnikrishnan Kuzhiumparambil, Srivatsan Laxman, V.V. Phansalkar, Naresh Manwani, L.S. Yengoyan and T. P. Imthias Ahamed and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

P. S. Sastry

124 papers receiving 5.2k citations

Hit Papers

align trajectories

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.

Lipids of nervous tissue: Composition and metabolism

1985 627 citations P. S. Sastry profile →
Robust Loss Functions under Label Noise for Deep Neural Networks

2017 541 citations P. S. Sastry et al. profile →

Peers

P. S. Sastry

AI

MB

CNC

EEE

CVPR

Rong Pan United States

Joshua Knowles United Kingdom

Rong Qu United Kingdom

George Michailidis United States

Yongsheng Ding China

Sheng Li China

Xiaodong Li China

Luonan Chen China

Wei Fang China

Yun Lin China

Rong Pan United States

P. S. Sastry

2.2k ×1.2

AI

1.4k ×1.1

MB

2.4k ×2.6

CNC

874 ×1.2

EEE

1.1k ×1.9

CVPR

Citations per year, relative to P. S. Sastry P. S. Sastry (= 1×) peers Rong Pan

Countries citing papers authored by P. S. Sastry

Since Specialization

Citations

This map shows the geographic impact of P. S. Sastry'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 P. S. Sastry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites P. S. Sastry more than expected).

Fields of papers citing papers by P. S. Sastry

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P. S. Sastry. 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 P. S. Sastry. The network helps show where P. S. Sastry may publish in the future.

Co-authorship network of co-authors of P. S. Sastry

This figure shows the co-authorship network connecting the top 25 collaborators of P. S. Sastry. A scholar is included among the top collaborators of P. S. Sastry 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 P. S. Sastry. P. S. Sastry is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Gurrala, Gurunath, et al.. (2024). Cyber-Physical Modeling and Vulnerability Assessment of Substations for Transmission System Operator. Electric Power Systems Research. 235. 110769–110769. 1 indexed citations

2.

Ibrahim, Ali K., et al.. (2024). Breadth-First Search Approach for Mining Serial Episodes with Simultaneous Events. 36–44.

3.

Song, Qingquan, et al.. (2020). On Robustness of Neural Architecture Search Under Label Noise. Frontiers in Big Data. 3. 2–2. 6 indexed citations

4.

Sastry, P. S.. (2016). Introduction to Pattern Recognition and Machine Learning. Current Science. 110(7). 1366–1367. 5 indexed citations

5.

Manwani, Naresh & P. S. Sastry. (2011). Geometric Decision Tree. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 42(1). 181–192. 55 indexed citations

6.

Manwani, Naresh & P. S. Sastry. (2010). Learning polyhedral classifiers using logistic function. NOT FOUND REPOSITORY (Indian Institute of Science Bangalore). 17–30. 10 indexed citations

7.

Diekman, Casey O., P. S. Sastry, & Unnikrishnan Kuzhiumparambil. (2009). Statistical significance of sequential firing patterns in multi-neuronal spike trains. Journal of Neuroscience Methods. 182(2). 279–284. 4 indexed citations

8.

Sastry, P. S., et al.. (2009). A Team of Continuous-Action Learning Automata for Noise-Tolerant Learning of Half-Spaces. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 40(1). 19–28. 32 indexed citations

9.

Patnaik, Debprakash, P. S. Sastry, & Unnikrishnan Kuzhiumparambil. (2008). Inferring Neuronal Network Connectivity from Spike Data: A Temporal Data Mining Approach. SHILAP Revista de lepidopterología. 3 indexed citations

10.

Sastry, P. S., et al.. (2004). Fingerprint Classification Using a Feedback-Based Line Detector. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 34(1). 85–94. 46 indexed citations

11.

Thathachar, M.A.L. & P. S. Sastry. (2002). Varieties of learning automata: an overview. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 32(6). 711–722. 273 indexed citations

12.

Sastry, P. S., et al.. (1999). Role of feedback in mammalian vision: a new hypothesis and a computational model. Vision Research. 39(1). 131–148. 6 indexed citations

13.

Sastry, P. S., et al.. (1998). Dielectric studies of layer structured sodium - calcium bismuth titanate mixed ceramics. Indian Journal of Engineering and Materials Sciences. 5(2). 83–87. 2 indexed citations

14.

Vaidyanathan, Vadakkanchery V., et al.. (1994). Diacylglycerol Kinase Is Stimulated by Arachidonic Acid in Neural Membranes. Journal of Neurochemistry. 63(4). 1454–1459. 16 indexed citations

15.

Vaidyanathan, Vadakkanchery V., et al.. (1994). Regulation of diacylglycerol kinase in rat brain membranes by docosahexaenoic acid. Neuroscience Letters. 179(1-2). 171–174. 47 indexed citations

16.

Vaidyanathan, Vadakkanchery V., P. S. Sastry, & T. Ramasarma. (1993). Inverse relationship of the dehydrogenase and ADP-ribosylation activities in sodium-nitroprusside-treated glyceraldehyde-3-phosphate dehydrogenase is coincidental. Biochimica et Biophysica Acta (BBA) - Protein Structure and Molecular Enzymology. 1203(1). 36–44. 7 indexed citations

17.

Menon, Ajit, et al.. (1991). An expert system for inferring structures of organic compounds from their mass spectra. Rapid Communications in Mass Spectrometry. 5(4). 206–213. 2 indexed citations

18.

Gupta, Sita D. & P. S. Sastry. (1987). Metabolism of the plant sulfolipid—Sulfoquinovosyldiacylglycerol: Degradation in animal tissues. Archives of Biochemistry and Biophysics. 259(2). 510–519. 11 indexed citations

19.

Sastry, P. S., et al.. (1986). Relaxation Labeling with Learning Automata. IEEE Transactions on Pattern Analysis and Machine Intelligence. PAMI-8(2). 256–268. 34 indexed citations

20.

Sastry, P. S.. (1974). Glycosyl Glycerides. PubMed. 12(0). 251–310. 51 indexed citations

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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