Aryan Deshwal

587 total citations
20 papers, 296 citations indexed

About

Aryan Deshwal is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Aryan Deshwal has authored 20 papers receiving a total of 296 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 8 papers in Electrical and Electronic Engineering and 5 papers in Computer Networks and Communications. Recurrent topics in Aryan Deshwal's work include Advanced Multi-Objective Optimization Algorithms (5 papers), Interconnection Networks and Systems (4 papers) and Advanced Bandit Algorithms Research (3 papers). Aryan Deshwal is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (5 papers), Interconnection Networks and Systems (4 papers) and Advanced Bandit Algorithms Research (3 papers). Aryan Deshwal collaborates with scholars based in United States. Aryan Deshwal's co-authors include Janardhan Rao Doppa, Syrine Belakaria, Cory M. Simon, Partha Pratim Pande, Biresh Kumar Joardar, Dae Hyun Kim, Zhiyuan Zhou, Krishnendu Chakrabarty, Deukhyoun Heo and Trong Nghia Hoang and has published in prestigious journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Advanced Materials Technologies and Journal of Artificial Intelligence Research.

In The Last Decade

Aryan Deshwal

18 papers receiving 291 citations

Peers

Aryan Deshwal

CTM

EEE

CVPR

Syrine Belakaria United States

Yuzong Liu United States

Qingying Deng China

Mahboobeh Houshmand Iran

Zicong Chen China

Stefano Pastore Italy

K. Koteswara Rao India

Mattia Vallerio Belgium

Qinghua Su China

Syrine Belakaria United States

Aryan Deshwal

93 ×0.9

CTM

82 ×0.9

9 ×0.1

138 ×2.2

EEE

43 ×1.1

CVPR

Citations per year, relative to Aryan Deshwal Aryan Deshwal (= 1×) peers Syrine Belakaria

Countries citing papers authored by Aryan Deshwal

Since Specialization

Citations

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

Fields of papers citing papers by Aryan Deshwal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aryan Deshwal

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

All Works

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20 of 20 papers shown

Karpatne, Anuj, Aryan Deshwal, Xiaowei Jia, et al.. (2025). AI-enabled scientific revolution in the age of generative AI: second NSF workshop report. 1(1).

Deshwal, Aryan, et al.. (2025). Constraint-Adaptive Policy Switching for Offline Safe Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 39(15). 15722–15730.

Chen, Chuchu, et al.. (2024). Machine Learning Enabled Design and Optimization for 3D‐Printing of High‐Fidelity Presurgical Organ Models. Advanced Materials Technologies. 10(1). 7 indexed citations

Deshwal, Aryan, et al.. (2024). Offline Model-Based Optimization via Policy-Guided Gradient Search. Proceedings of the AAAI Conference on Artificial Intelligence. 38(10). 11230–11239. 2 indexed citations

Deshwal, Aryan, et al.. (2023). Multi-fidelity Bayesian optimization of covalent organic frameworks for xenon/krypton separations. Digital Discovery. 2(6). 1937–1956. 22 indexed citations

Deshwal, Aryan, et al.. (2023). Dynamic Power Management in Large Manycore Systems: A Learning-to-Search Framework. ACM Transactions on Design Automation of Electronic Systems. 28(5). 1–21. 1 indexed citations

Deshwal, Aryan, Syrine Belakaria, Janardhan Rao Doppa, & Dae Hyun Kim. (2022). Bayesian Optimization over Permutation Spaces. Proceedings of the AAAI Conference on Artificial Intelligence. 36(6). 6515–6523. 10 indexed citations

Belakaria, Syrine, Aryan Deshwal, & Janardhan Rao Doppa. (2021). Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization. Journal of Artificial Intelligence Research. 72. 667–715. 9 indexed citations

Deshwal, Aryan, Cory M. Simon, & Janardhan Rao Doppa. (2021). Bayesian optimization of nanoporous materials. Molecular Systems Design & Engineering. 6(12). 1066–1086. 65 indexed citations

10.

Joardar, Biresh Kumar, Aryan Deshwal, Janardhan Rao Doppa, Partha Pratim Pande, & Krishnendu Chakrabarty. (2021). High-Throughput Training of Deep CNNs on ReRAM-Based Heterogeneous Architectures via Optimized Normalization Layers. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 41(5). 1537–1549. 9 indexed citations

11.

Belakaria, Syrine, Aryan Deshwal, & Janardhan Rao Doppa. (2020). Multi-Fidelity Multi-Objective Bayesian Optimization: An Output Space Entropy Search Approach. Proceedings of the AAAI Conference on Artificial Intelligence. 34(6). 10035–10043. 24 indexed citations

12.

Belakaria, Syrine, et al.. (2020). Design and Optimization of Energy-Accuracy Tradeoff Networks for Mobile Platforms via Pretrained Deep Models. ACM Transactions on Embedded Computing Systems. 19(1). 1–24. 25 indexed citations

13.

Zhou, Zhiyuan, Syrine Belakaria, Aryan Deshwal, et al.. (2020). Design of Multi-Output Switched-Capacitor Voltage Regulator via Machine Learning. 502–507. 13 indexed citations

14.

Belakaria, Syrine, et al.. (2020). Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization. Proceedings of the AAAI Conference on Artificial Intelligence. 34(6). 10044–10052. 33 indexed citations

15.

Belakaria, Syrine, Aryan Deshwal, & Janardhan Rao Doppa. (2019). Max-value Entropy Search for Multi-Objective Bayesian Optimization. Neural Information Processing Systems. 32. 7823–7833. 46 indexed citations

16.

Bogdan, Paul, Fan Chen, Aryan Deshwal, et al.. (2019). Taming extreme heterogeneity via machine learning based design of autonomous manycore systems. 1–10. 3 indexed citations

17.

Joardar, Biresh Kumar, Aryan Deshwal, Janardhan Rao Doppa, & Partha Pratim Pande. (2019). A Machine Learning Framework for Multi-Objective Design Space Exploration and Optimization of Manycore Systems. 1–6. 1 indexed citations

18.

Deshwal, Aryan, Janardhan Rao Doppa, & Dan Roth. (2019). Learning and Inference for Structured Prediction: A Unifying Perspective. 6291–6299. 3 indexed citations

19.

Ma, Chao, et al.. (2019). Randomized Greedy Search for Structured Prediction: Amortized Inference and Learning. 5130–5138. 2 indexed citations

20.

Deshwal, Aryan, et al.. (2019). MOOS. ACM Transactions on Embedded Computing Systems. 18(5s). 1–23. 21 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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