◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

V. Nair

4 papers hereh-index 318 citations15 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author2
  • first author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • eess.SY2
same name
  • V. Nair — 38 papers, h 39
  • V. Nair — 18 papers, h 30
  • V. Nair — 7 papers, h 17
  • V. Nair — 6 papers, h 9
  • V. Nair — 5 papers, h 1
  • V. Nair — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

eess.SY2026

Multiobjective optimization-based design and dispatch of islanded, hybrid microgrids for remote, off-grid communities in sub-Saharan Africa

Vineet Jagadeesan Nair

Reliable, affordable electricity remains inaccessible to over 600 million people in sub-Saharan Africa (SSA), where islanded hybrid microgrids combining renewable generation, batte…

eess.SY2026

Dynamic resource coordination can increase grid hosting capacity to support more renewables, storage, and electrified load growth

Vineet Jagadeesan Nair, Morteza Vahid-Ghavidel, Anuradha M. Annaswamy

We show that dynamic coordination of distributed energy resources (DERs) can increase the capacity of low- and medium-voltage grids, improve reliability and power quality, and redu…

cs.LG2024

Improving accuracy and convergence of federated learning edge computing methods for generalized DER forecasting applications in power grid

Vineet Jagadeesan Nair, Lucas Pereira

This proposal aims to develop more accurate federated learning (FL) methods with faster convergence properties and lower communication requirements, specifically for forecasting di…

cs.LG2024

Enhanced physics-informed neural networks (PINNs) for high-order power grid dynamics

Vineet Jagadeesan Nair

We develop improved physics-informed neural networks (PINNs) for high-order and high-dimensional power system models described by nonlinear ordinary differential equations. We prop…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.