Conference Information

ISAI' 2027: International Symposium on AI

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Submission Date:
2026-12-05 Due in 77 days
Notification Date:
2027-01-05
Conference Date:
2027-04-23
Location:
Chengdu, China
Years:
Viewed: 10244   Tracked: 4   Attend: 1

Conference Partner Index (CP-I)

49.8 / 100
Ranked #1,617 of 5,682 conferences · Top 29%
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%)
56
Community attention (10%)
29
Public record completeness (15%)
55

Inputs used: Editions on record: 7 · Researchers following it here: 4 · Researchers who opened this page in the past 24 months: 5

Missing from the public record: Historical acceptance rates (+4.5) · 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 2026-09-19

Call For Papers

ISAI' 2027 (International Symposium on AI) is an academic conference held in Chengdu, China on 2027-04-23. The paper submission deadline is 2026-12-05. Acceptance notifications are sent on 2027-01-05.

ISAI 2027, 2027 the 7th International Symposium on AI, will be held in Chengdu, China during April 23-25, 2027. We invite the submission of technical papers for the main technical track of the conference. Submissions should be significant, original, and previously unpublished results on all aspects of artificial intelligence. We especially encourage papers on AI techniques for novel application domains. Topics of interest for submission include, but are not limited to: Track 1. AI and Machine Learning Advances Track Chair: TBA ◆ Deep & Reinforcement Learning Transformer Models & Attention Mechanisms Meta-Learning & Few-Shot Learning Self-Supervised Learning Neural Architecture Search (NAS) ◆ Explainable & Trustworthy AI Interpretability in Deep Learning Bias and Fairness in AI Systems AI Accountability & Regulation Robustness & Adversarial Defense ◆ Optimization & Scalability Distributed & Federated Learning Quantum Machine Learning TinyML & Edge AI Energy-Efficient AI Track 2. Intelligent Systems for Cybersecurity & Data Science Track Chair: TBA ◆ AI-Driven Security Solutions Zero-Day Attack Detection with AI AI in Malware & Phishing Detection AI for Network Intrusion Detection Secure Multi-Agent Systems ◆ Privacy & Trust in AI Homomorphic Encryption & AI Differential Privacy in ML AI for Anomaly Detection Federated Learning for Privacy ◆ Big Data & AI Integration AI for Real-Time Stream Processing Graph Neural Networks for Data Mining AI in Cloud & Edge Data Analytics Scalable AI for IoT Data Track 3. Natural Language Processing and Cognitive Computing Track Chair: TBA ◆ Large Language Models (LLMs) & Beyond Multimodal & Embodied AI Retrieval-Augmented Generation (RAG) AI for Low-Resource Languages LLM Fine-Tuning & Optimization ◆ Knowledge & Reasoning Systems Neuro-Symbolic AI Integration Automated Knowledge Graph Construction Commonsense Reasoning in AI AI for Legal Document Analysis ◆ Speech & Human-AI Interaction Emotion & Sentiment Recognition Conversational AI & Chatbots AI in Virtual & Augmented Reality Accessibility Technologies with NLP Track 4. AI for Industrial and Real-World Applications Track Chair: TBA ◆ AI in Healthcare & Life Sciences Medical Imaging & Diagnostics AI for Drug Discovery Predictive Healthcare Analytics AI in Genomics & Precision Medicine ◆ Autonomous & Robotic Systems Self-Driving Vehicles & Drones AI for Industrial Robotics Swarm Intelligence Human-Robot Collaboration ◆ AI for Smart & Sustainable Systems AI in Energy Grid Optimization Climate Modeling with AI AI for Agriculture & Food Security Smart Manufacturing & Industry 4.0
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