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researcher

P. Jha

25 papers hereh-index 9284 citations66 works total

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

author position
  • sole author1
  • first author6
  • middle author15
  • last author2

Across the 24 of 25 papers where every author was matched, so the position is known.

fields
  • cs.NI14
  • cs.IT5
  • eess.SP4
  • cs.CR1
  • cs.ET1
same name
  • P. Jha — 24 papers, h 25
  • P. Jha — 21 papers, h 45
  • P. Jha — 18 papers, h 32
  • P. Jha — 6 papers, h 5
  • P. Jha — 5 papers, h 17
  • P. Jha — 5 papers, h 5

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

activity
20172025
most citedConnecting the Unconnected: Towards Frugal 5G Network Architecture and Standardization

51 citations · 75 across the 22 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.NI2025

ITU-T Y.2325: NGN Evolution Towards Future

Rashmi Kamran, Shwetha Kiran, Pranav Jha +3

International Telecommunications Union (ITU) defined Next Generation Network (NGN) underlies most wireline and wireless packet-based telecommunications networks. A key design princ…

cs.ET2025

AI/ML in 3GPP 5G Advanced -- Services and Architecture

Pradnya Taksande, Shwetha Kiran, Pranav Jha +1

The 3rd Generation Partnership Project (3GPP), the standards body for mobile networks, is in the final phase of Release 19 standardization and is beginning Release 20. Artificial I…

cs.NI2025

Energy-Aware 6G Network Design: A Survey

Rashmi Kamran, Mahesh Ganesh Bhat, Pranav Jha +3

6th Generation (6G) mobile networks are envisioned to support several new capabilities and data-centric applications for unprecedented number of users, potentially raising signific…

cs.CR2025

Adversarial Machine Learning: Attacks, Defenses, and Open Challenges

Pranav K Jha

Adversarial Machine Learning (AML) addresses vulnerabilities in AI systems where adversaries manipulate inputs or training data to degrade performance. This article provides a comp…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.