Conference Information

ICPC2T 2025: International Conference on Power, Control, and Computing Technologies

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ICPC2T
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Submission Date:
2024-10-15 Extended
Notification Date:
2024-11-15
Conference Date:
2025-01-20
Location:
Raipur, India
Years:
4
Viewed: 6928   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

42.2 / 100
Ranked #4,117 of 5,687 conferences · Top 73%
Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
43
Community attention (10%)
8
Public record completeness (15%)
35

Inputs used: Editions on record: 4 · Researchers who opened this page in the past 24 months: 2

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-25

Call For Papers

ICPC2T 2025 (International Conference on Power, Control, and Computing Technologies) is an academic conference held in Raipur, India on 2025-01-20. The paper submission deadline is 2024-10-15 (extended). Acceptance notifications are sent on 2024-11-15.

Conference Tracks/Topics Papers are invited in the following areas of interest, but not limited to: Power Systems Power Quality Green Technology Renewable Energy Smart Grid Cyber Security for electrical systems High Voltage Technologies HVDC and FACTS Devices Power Electronics and Drives Electric Transportation Systems Instrumentation and Control Process Control and Automation Signal and Image Processing Techniques Cyber Physical Systems for electrical systems Internet of Things Data Mining Cloud Computing Data Analytics Artificial Intelligence and Machine Learning for electrical systems Optimization Techniques for electrical systems Deep Learning for electrical systems Control Engineering
Last updated by Dou Sun on

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