Journal Selector#

Match papers to the right venue — maximizing acceptance odds and impact.

Input Needed#

Provide one or more of:

• Full paper draft
• Abstract
• Key contributions list
• Current submission status (new / revision / rejected)
• Author preference: speed vs. prestige, theory vs. application, impact factor priority

Output: Venue Recommendations#

For each suggested venue, provide:

FieldDescriptionVenueFull name + abbreviationFit Score1-10, how well paper matchesMatch ReasoningWhy this paper fits this venueRiskReach / Safe / SafetyReview SpeedFast (3-6mo) / Medium (6-9mo) / Slow (9-18mo)Impact FactorIf knownKey ConcernsWhat might cause rejection hereStrategy TipHow to position the paper for this venue

Risk Classification#

• Reach: Top-tier, low acceptance rate, high impact if accepted
• Safe: Lower-tier, higher acceptance, less prestige
• Safety: Almost certain acceptance, but limited impact

Review Speed Classification#

• Fast: Conferences (ICRA, CDC, ACC), some letters journals
• Medium: IEEE TIE, TCST, Neurocomputing
• Slow: IEEE TAC, Automatica, Springer journals

Venue Categories for Control/AI Research#

Tier 1 — High Prestige, Low Acceptance#

• IEEE Transactions on Automatic Control (TAC)
• Automatica
• International Journal of Robotics Research (IJRR)

Tier 2 — Strong, Balanced#

• IEEE Transactions on Industrial Electronics (TIE)
• IEEE Transactions on Control Systems Technology (TCST)
• IEEE Transactions on Robotics (TRO)
• Systems & Control Letters
• International Journal of Adaptive Control and Signal Processing

Tier 3 — Applied / Specialized#

• IEEE Transactions on Aerospace and Electronic Systems
• Journal of the Franklin Institute
• Asian Journal of Control
• IET Control Theory & Applications

Tier 4 — Fast Conference Track#

• CDC (IEEE Conf. on Decision and Control)
• ACC (American Control Conference)
• ICRA (IEEE Intl. Conf. on Robotics and Automation)
• IROS (IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems)
• ECC (European Control Conference)

AI / Learning + Control#

• IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
• IEEE Transactions on Artificial Intelligence
• Pattern Recognition and Machine Intelligence (PRAMI)

See references/venue-database.md for full venue profiles including IF, review speed, scope, and tips.

Decision Factors#

1. Paper's theory-to-application ratio — Pure theory → TAC/Automatica; Applied → TIE/TCST
2. Novelty level — Incremental → Mid-tier; Breakthrough → Top-tier
3. Author timeline — Need publication fast → Conference first; Can wait → Journal
4. Target audience — Robotics community → ICRA/IROS; Control theory → CDC/ACC/TAC
5. Revision history — Rejected from top? Suggest next-tier before re-review

Workflow#

1. Analyze paper: extract topic, method, contribution strength, application domain
2. Map to venue categories (tier + type)
3. Score fit for 8-12 candidate venues
4. Select top 5-8 with varied risk levels
5. Sort by fit score descending
6. Include reach/safe/safety spread for author choice

Warning Signs#

• Paper is too theoretical for applied journal → expect desk rejection
• Paper lacks experiments for IEEE Transactions → risky
• Novelty is incremental but targeting top-tier → high rejection risk
• Mixing control + learning communities without clear contribution to either → positioning problem

See references/venue-database.md for detailed venue profiles.