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Engineering and Technology

D-Index
55
Citations
10652
World Ranking
3018
National Ranking
903

Overview

Ram Rajagopal is affiliated with Stanford University in the United States and specializes in engineering with a focus on electrical and electronic engineering. Their research encompasses several subfields including automotive engineering, global and planetary change, renewable energy, sustainability and the environment, as well as computer vision and pattern recognition.

The main topics of Ram Rajagopal's work include smart grid energy management, electric vehicles and infrastructure, advanced battery technologies research, energy and environment impacts, energy load and power forecasting, microgrid control and optimization, and optimal power flow distribution.

Frequent collaborators in their research include Chad Zanocco, June A. Flora, Zhecheng Wang, Yang Weng, and Siobhan Powell.

Rajagopal has published extensively across various venues, with numerous publications in arXiv (Cornell University), Applied Energy, SSRN Electronic Journal, Nature Energy, and IEEE Transactions on Smart Grid.

Recent papers authored by or coauthored with Rajagopal include the following:

  • Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption, 2022, Nature Energy
  • Improving Probabilistic Load Forecasting Using Quantile Regression NN With Skip Connections, 2020, IEEE Transactions on Smart Grid
  • Scalable probabilistic estimates of electric vehicle charging given observed driver behavior, 2022, Applied Energy
  • Urban2Vec: Incorporating Street View Imagery and POIs for Multi-Modal Urban Neighborhood Embedding, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Global changes in electricity consumption during COVID-19, 2021, iScience

In addition to journal articles, Ram Rajagopal has contributed to book literature, including a publication with Springer Nature titled Data Science and Applications for Modern Power Systems released in 2023.

Best Publications

  • Determinants of residential electricity consumption: Using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants' behavior

    Amir Kavousian;Ram Rajagopal;Martin Fischer

  • Household Energy Consumption Segmentation Using Hourly Data

    Jungsuk Kwac;June Flora;Ram Rajagopal

  • Bringing Wind Energy to Market

    Eilyan Y. Bitar;Ram Rajagopal;Pramod P. Khargonekar;Kameshwar Poolla

  • DeepSolar: A Machine Learning Framework to Efficiently Construct a Solar Deployment Database in the United States

    Jiafan Yu;Zhecheng Wang;Arun Majumdar;Ram Rajagopal

  • Smart Meter Driven Segmentation: What Your Consumption Says About You

    Adrian Albert;Ram Rajagopal

  • Arterial travel time estimation based on vehicle re-identification using wireless magnetic sensors

    Karric Kwong;Robert Kavaler;Ram Rajagopal;Pravin Varaiya

  • PaToPa: A Data-Driven Parameter and Topology Joint Estimation Framework in Distribution Grids

    Jiafan Yu;Yang Weng;Ram Rajagopal

  • Distributed Energy Resources Topology Identification via Graphical Modeling

    Yang Weng;Yizheng Liao;Ram Rajagopal

  • Detection and Statistics of Wind Power Ramps

    Raffi Sevlian;Ram Rajagopal

  • Optimal bidding strategy for microgrids in joint energy and ancillary service markets considering flexible ramping products

    Jianxiao Wang;Haiwang Zhong;Wenyuan Tang;Ram Rajagopal

  • Context-Aware Generative Adversarial Privacy

    Chong Huang;Peter Kairouz;Xiao Chen;Lalitha Sankar

  • Optimal dynamic parking pricing for morning commute considering expected cruising time

    Zhen (Sean) Qian;Ram Rajagopal

  • Urban MV and LV Distribution Grid Topology Estimation via Group Lasso

    Yizheng Liao;Yang Weng;Guangyi Liu;Ram Rajagopal

  • In-pavement wireless sensor network for vehicle classification

    Ravneet Bajwa;Ram Rajagopal;Pravin Varaiya;Robert Kavaler

  • Risk-limiting dispatch for integrating renewable power

    Ram Rajagopal;Eilyan Bitar;Pravin Varaiya;Felix Wu

  • Data-driven planning of distributed energy resources amidst socio-technical complexities

    Rishee K. Jain;Junjie Qin;Ram Rajagopal

  • Network-Based Consensus Averaging With General Noisy Channels

    R Rajagopal;M J Wainwright

  • Scalable probabilistic estimates of electric vehicle charging given observed driver behavior

    Unknown

  • A scaling law for short term load forecasting on varying levels of aggregation

    Raffi Sevlian;Ram Rajagopal

  • PaToPaEM: A Data-Driven Parameter and Topology Joint Estimation Framework for Time-Varying System in Distribution Grids

    Jiafan Yu;Yang Weng;Ram Rajagopal

  • The role of co-located storage for wind power producers in conventional electricity markets

    E. Bitar;R. Rajagopal;P. Khargonekar;K. Poolla

  • System and method for signal matching and characterization

    Ram Rajagopal;Lothar Wenzel;Dinesh Nair;Darren Schmidt

  • FedGAN: Federated Generative Adversarial Networks for Distributed Data.

    Mohammad Rasouli;Tao Sun;Ram Rajagopal

Frequent Co-Authors

Pravin Varaiya
Pravin Varaiya University of California, Berkeley
Yang Weng
Yang Weng Arizona State University
Anne S. Kiremidjian
Anne S. Kiremidjian Stanford University
Baosen Zhang
Baosen Zhang University of Washington
Abbas El Gamal
Abbas El Gamal Stanford University
June A. Flora
June A. Flora Stanford University
H. Vincent Poor
H. Vincent Poor Princeton University
Ramesh Johari
Ramesh Johari Stanford University
Andrea Goldsmith
Andrea Goldsmith Stony Brook University
Kameshwar Poolla
Kameshwar Poolla University of California, Berkeley

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