Srivatsan Krishnan

1.2k total citations · 1 hit paper
20 papers, 729 citations indexed

About

Srivatsan Krishnan is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Hardware and Architecture. According to data from OpenAlex, Srivatsan Krishnan has authored 20 papers receiving a total of 729 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Electrical and Electronic Engineering, 7 papers in Computer Vision and Pattern Recognition and 6 papers in Hardware and Architecture. Recurrent topics in Srivatsan Krishnan's work include Parallel Computing and Optimization Techniques (6 papers), Advanced Memory and Neural Computing (5 papers) and Robotic Path Planning Algorithms (5 papers). Srivatsan Krishnan is often cited by papers focused on Parallel Computing and Optimization Techniques (6 papers), Advanced Memory and Neural Computing (5 papers) and Robotic Path Planning Algorithms (5 papers). Srivatsan Krishnan collaborates with scholars based in United States, Netherlands and United Kingdom. Srivatsan Krishnan's co-authors include Eriko Nurvitadhi, Debbie Marr, Jaewoong Sim, Suchit Subhaschandra, Duncan J. M. Moss, Aleksandra Faust, Vijay Janapa Reddi, Asit Mishra, Randy Huang and Guy Boudoukh and has published in prestigious journals such as Pattern Recognition, Machine Learning and ACM Transactions on Computer Systems.

In The Last Decade

Srivatsan Krishnan

19 papers receiving 705 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.

Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Neural Networks?

2017 287 citations Eriko Nurvitadhi, Ganesh Venkatesh et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Srivatsan Krishnan United States	11	343	296	225	178	151	20	729
Hiroki Nakahara Japan	16	485 1.4×	511 1.7×	321 1.4×	202 1.1×	110 0.7×	98	971
Chen Yang China	17	241 0.7×	278 0.9×	255 1.1×	198 1.1×	153 1.0×	78	820
Indranil Saha India	15	253 0.7×	353 1.2×	404 1.8×	168 0.9×	198 1.3×	50	1.1k
Joo-Young Kim South Korea	17	300 0.9×	620 2.1×	176 0.8×	146 0.8×	192 1.3×	80	940
Yingyan Lin United States	19	522 1.5×	393 1.3×	472 2.1×	141 0.8×	187 1.2×	81	1.1k
Iraklis Anagnostopoulos United States	13	528 1.5×	240 0.8×	159 0.7×	213 1.2×	253 1.7×	79	1.1k
Jong Hwan Ko South Korea	16	300 0.9×	290 1.0×	156 0.7×	67 0.4×	76 0.5×	88	702
John Glossner United States	13	285 0.8×	358 1.2×	276 1.2×	260 1.5×	264 1.7×	69	986
Libo Huang China	15	192 0.6×	202 0.7×	100 0.4×	243 1.4×	202 1.3×	115	779
Ramyad Hadidi United States	15	314 0.9×	261 0.9×	210 0.9×	329 1.8×	391 2.6×	31	781

Countries citing papers authored by Srivatsan Krishnan

Since Specialization

Citations

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

Fields of papers citing papers by Srivatsan Krishnan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Srivatsan Krishnan. 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 Srivatsan Krishnan. The network helps show where Srivatsan Krishnan may publish in the future.

Co-authorship network of co-authors of Srivatsan Krishnan

This figure shows the co-authorship network connecting the top 25 collaborators of Srivatsan Krishnan. A scholar is included among the top collaborators of Srivatsan Krishnan 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 Srivatsan Krishnan. Srivatsan Krishnan 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

Krishnan, Srivatsan, et al.. (2023). ArchGym: An Open-Source Gymnasium for Machine Learning Assisted Architecture Design. 1–16. 5 indexed citations

Krishnan, Srivatsan, Zishen Wan, Kshitij Bhardwaj, et al.. (2022). Automatic Domain-Specific SoC Design for Autonomous Unmanned Aerial Vehicles. 300–317. 27 indexed citations

Plancher, Brian, Srivatsan Krishnan, Colby Banbury, et al.. (2022). Tiny Robot Learning: Challenges and Directions for Machine Learning in Resource-Constrained Robots. Research Repository (Delft University of Technology). 296–299. 23 indexed citations

Krishnan, Srivatsan, et al.. (2022). Roofline Model for UAVs: A Bottleneck Analysis Tool for Onboard Compute Characterization of Autonomous Unmanned Aerial Vehicles. 162–174. 16 indexed citations

Krishnan, Srivatsan, et al.. (2022). Enhanced Route Optimization for Wireless Networks Using Meta-Heuristic Engineering. Computer Systems Science and Engineering. 43(1). 17–26.

Krishnan, Srivatsan, et al.. (2021). The Role of Compute in Autonomous Micro Aerial Vehicles: Optimizing for Mission Time and Energy Efficiency. ACM Transactions on Computer Systems. 39(1-4). 1–44. 8 indexed citations

Krishnan, Srivatsan, et al.. (2021). Air Learning: a deep reinforcement learning gym for autonomous aerial robot visual navigation. Machine Learning. 110(9). 2501–2540. 26 indexed citations

Krishnan, Srivatsan, Jonathan Cruz, Colby Banbury, et al.. (2021). Tiny Robot Learning (tinyRL) for Source Seeking on a Nano Quadcopter. 7242–7248. 20 indexed citations

Krishnan, Srivatsan, Zishen Wan, Kshitij Bhardwaj, et al.. (2020). The Sky Is Not the Limit: A Visual Performance Model for Cyber-Physical Co-Design in Autonomous Machines. IEEE Computer Architecture Letters. 19(1). 38–42. 27 indexed citations

10.

Krishnan, Srivatsan, Jonathan Cruz, Colby Banbury, et al.. (2019). Learning to Seek: Deep Reinforcement Learning for Phototaxis of a Nano Drone in an Obstacle Field. arXiv (Cornell University). 4 indexed citations

11.

Krishnan, Srivatsan, et al.. (2019). Toward Exploring End-to-End Learning Algorithms for Autonomous Aerial Machines. 2 indexed citations

12.

Yuvaraj, D., M. Sivaram, & Srivatsan Krishnan. (2019). Intelligent detection of untrusted data transmission to optimize energy in sensor networks. Journal of Information and Optimization Sciences. 41(3). 799–811. 7 indexed citations

13.

Krishnan, Srivatsan, et al.. (2018). A Customizable Matrix Multiplication Framework for the Intel HARPv2 Xeon+FPGA Platform A Deep Learning Case Study. 107–116. 7 indexed citations

14.

Moss, Duncan J. M., Srivatsan Krishnan, Eriko Nurvitadhi, et al.. (2018). A Customizable Matrix Multiplication Framework for the Intel HARPv2 Xeon+FPGA Platform. 107–116. 60 indexed citations

15.

Krishnan, Srivatsan, et al.. (2018). Why Compute Matters for UAV Energy Efficiency. 3 indexed citations

16.

Krishnan, Srivatsan, et al.. (2018). MAVBench: Micro Aerial Vehicle Benchmarking. 894–907. 58 indexed citations

17.

Nurvitadhi, Eriko, Ganesh Venkatesh, Jaewoong Sim, et al.. (2017). Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Neural Networks?. 5–14. 287 indexed citations breakdown →

18.

Nurvitadhi, Eriko, Davor Capalija, Andrew C. Ling, et al.. (2017). Customizable FPGA OpenCL matrix multiply design template for deep neural networks. 259–262. 10 indexed citations

19.

Nurvitadhi, Eriko, Jaewoong Sim, David Sheffield, et al.. (2016). Accelerating recurrent neural networks in analytics servers: Comparison of FPGA, CPU, GPU, and ASIC. 1–4. 129 indexed citations

20.

Krishnan, Srivatsan & Daniel Raviv. (1995). 2D feature tracking algorithm for motion analysis. Pattern Recognition. 28(8). 1103–1126. 10 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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