Viplove Arora
Data Science Researcher @ SISSA | PhD in Industrial Engineering
Research Expertise
Publications
An Introduction to Multiobjective Simulation Optimization
ACM Transactions on Modeling and Computer Simulation / Jan 24, 2019
Hunter, S. R., Applegate, E. A., Arora, V., Chong, B., Cooper, K., Rincón-Guevara, O., & Vivas-Valencia, C. (2019). An Introduction to Multiobjective Simulation Optimization. ACM Transactions on Modeling and Computer Simulation, 29(1), 1–36. https://doi.org/10.1145/3299872
Action-based Modeling of Complex Networks
Scientific Reports / Jul 27, 2017
Arora, V., & Ventresca, M. (2017). Action-based Modeling of Complex Networks. Scientific Reports, 7(1). https://doi.org/10.1038/s41598-017-05444-4
Modeling topologically resilient supply chain networks
Applied Network Science / Jul 09, 2018
Arora, V., & Ventresca, M. (2018). Modeling topologically resilient supply chain networks. Applied Network Science, 3(1). https://doi.org/10.1007/s41109-018-0070-7
A Multi-objective Optimization Approach for Generating Complex Networks
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion / Jul 20, 2016
Arora, V., & Ventresca, M. (2016, July 20). A Multi-objective Optimization Approach for Generating Complex Networks. Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion. https://doi.org/10.1145/2908961.2908966
Examining the variability in network populations and its role in generative models
Network Science / Jan 17, 2020
Arora, V., Guo, D., Dunbar, K. D., & Ventresca, M. (2020). Examining the variability in network populations and its role in generative models. Network Science, 8(S1), S43–S64. https://doi.org/10.1017/nws.2019.63
De novo prediction of RNA–protein interactions with graph neural networks
RNA / Aug 25, 2022
Arora, V., & Sanguinetti, G. (2022). De novo prediction of RNA–protein interactions with graph neural networks. RNA, 28(11), 1469–1480. https://doi.org/10.1261/rna.079365.122
Evaluating the Natural Variability in Generative Models for Complex Networks
Studies in Computational Intelligence / Dec 02, 2018
Arora, V., & Ventresca, M. (2018). Evaluating the Natural Variability in Generative Models for Complex Networks. In Complex Networks and Their Applications VII (pp. 743–754). Springer International Publishing. https://doi.org/10.1007/978-3-030-05411-3_59
Action-Based Model for Topologically Resilient Supply Networks
Complex Networks & Their Applications VI / Nov 27, 2017
Arora, V., & Ventresca, M. (2017). Action-Based Model for Topologically Resilient Supply Networks. In Studies in Computational Intelligence (pp. 658–669). Springer International Publishing. https://doi.org/10.1007/978-3-319-72150-7_53
Dynamic Generative Model of the Human Brain in Resting-State
Complex Networks & Their Applications VI / Nov 27, 2017
Guo, D., Arora, V., Amico, E., Goñi, J., & Ventresca, M. (2017). Dynamic Generative Model of the Human Brain in Resting-State. In Studies in Computational Intelligence (pp. 1271–1283). Springer International Publishing. https://doi.org/10.1007/978-3-319-72150-7_103
Inverse backscattering problem for perturbations of biharmonic operator
Inverse Problems / Sep 07, 2017
Tyni, T., & Harju, M. (2017). Inverse backscattering problem for perturbations of biharmonic operator. Inverse Problems, 33(10), 105002. https://doi.org/10.1088/1361-6420/aa873e
Identifying the source of an epidemic using particle swarm optimization
Proceedings of the Genetic and Evolutionary Computation Conference / Jul 08, 2022
MaGee, J., Arora, V., & Ventresca, M. (2022, July 8). Identifying the source of an epidemic using particle swarm optimization. Proceedings of the Genetic and Evolutionary Computation Conference. https://doi.org/10.1145/3512290.3528711
Optimal resource allocation to minimize errors when detecting human trafficking
IISE Transactions / Mar 28, 2023
Ray, A., Arora, V., Maass, K., & Ventresca, M. (2023). Optimal resource allocation to minimize errors when detecting human trafficking. IISE Transactions, 56(3), 325–339. https://doi.org/10.1080/24725854.2023.2177364
On Arxiv Moderation System
Jan 01, 2023
Silagadze, Z. (2023). On Arxiv Moderation System. https://doi.org/10.2139/ssrn.4392249
Investigating cognitive ability using action-based models of structural brain networks
Journal of Complex Networks / Jun 29, 2022
Arora, V., Amico, E., Goñi, J., & Ventresca, M. (2022). Investigating cognitive ability using action-based models of structural brain networks. Journal of Complex Networks, 10(4). https://doi.org/10.1093/comnet/cnac037
AN OASIS OF PURE AEROTHERMAL DILEMMAS:INTEGRATING TURBINES WITH ROTATING DETONATION COMBUSTOR
Recent progress in detonation for propulsion / Jul 31, 2019
PANIAGUA, G., BRAUN, J., MEYER, T., ATHMANATHAN, V., & ROY, S. (2019, July 31). AN OASIS OF PURE AEROTHERMAL DILEMMAS:INTEGRATING TURBINES WITH ROTATING DETONATION COMBUSTOR. Recent Progress in Detonation for Propulsion. https://doi.org/10.30826/iwdp201924
Challenges for machine learning in RNA-protein interaction prediction
Statistical Applications in Genetics and Molecular Biology / Jan 01, 2022
Arora, V., & Sanguinetti, G. (2022). Challenges for machine learning in RNA-protein interaction prediction. Statistical Applications in Genetics and Molecular Biology, 21(1). https://doi.org/10.1515/sagmb-2021-0087
De novo prediction of RNA-protein interactions with Graph Neural Networks
Sep 30, 2021
Arora, V., & Sanguinetti, G. (2021). De novo prediction of RNA-protein interactions with Graph Neural Networks. https://doi.org/10.1101/2021.09.28.462100
Education
Purdue University
Phd, Industrial Engineering / December, 2019
Indian Institute of Technology Delhi
Bachelors, Production and Industrial Engineering / May, 2014
Experience
International School for Advanced Studies
Postdoc / October, 2020 — October, 2023
Purdue University
Postdoc / January, 2020 — September, 2020
Links & Social Media
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