Srivatsan Krishnan
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Artificial Intelligence top 5%
- Hardware and Architecture top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Eriko NurvitadhiDebbie MarrJaewoong SimSuchit SubhaschandraDuncan J. M. MossVijay Janapa ReddiAleksandra FaustAsit Mishra
- Topics
- Parallel Computing and Optimization Techniques (6 papers)Advanced Memory and Neural Computing (5 papers)Robotic Path Planning Algorithms (5 papers)
- Partner nations
- United StatesNetherlandsUnited Kingdom
In The Last Decade
Srivatsan Krishnan
19 papers receiving 705 citations
Hit Papers
Peers
Comparison fields: 5 of 70
- Computer Vision and Pattern Recognition 343
- Electrical and Electronic Engineering 296
- Artificial Intelligence 225
- Hardware and Architecture 178
- Computer Networks and Communications 151
Countries citing papers authored by Srivatsan Krishnan
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 27 | |
| 3 | 23 | |
| 4 | 16 | |
| 5 | 0 | |
| 6 | 8 | |
| 7 | 26 | |
| 8 | 20 | |
| 9 | 27 | |
| 10 | Learning to Seek: Deep Reinforcement Learning for Phototaxis of a Nano Drone in an Obstacle Field | 4 |
| 11 | 7 | |
| 12 | Toward Exploring End-to-End Learning Algorithms for Autonomous Aerial Machines | 2 |
| 13 | A Customizable Matrix Multiplication Framework for the Intel HARPv2 Xeon+FPGA Platform A Deep Learning Case Study | 7 |
| 14 | Why Compute Matters for UAV Energy Efficiency | 3 |
| 15 | 60 | |
| 16 | 58 | |
| 17 | Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Neural Networks?breakdown → | 287 |
| 18 | 10 | |
| 19 | 129 | |
| 20 | 10 |
About Srivatsan Krishnan
Srivatsan Krishnan is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design, having authored 20 papers that have together received 729 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (6 papers), Advanced Memory and Neural Computing (5 papers) and Robotic Path Planning Algorithms (5 papers). The work is most often cited by research in Hardware and Architecture (178 citations), Computer Vision and Pattern Recognition (343 citations) and Computational Mathematics (7 citations). Srivatsan Krishnan has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Eriko Nurvitadhi, Debbie Marr, Jaewoong Sim, Suchit Subhaschandra, Duncan J. M. Moss, Vijay Janapa Reddi, Aleksandra Faust, Asit Mishra, Guy Boudoukh and Ganesh Venkatesh. Their work appears in journals such as Pattern Recognition, Machine Learning and ACM Transactions on Computer Systems.
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.