Dear Authors,
We regret to inform you that your manuscript has not been accepted for publication…
I’ve gotten this email more times than I’d like to admit. And I’ll get it again. Probably soon.
Currently, I have 9 papers under review. Statistically, at least 3-4 will be rejected. Maybe more.
Here’s how I’ve learned to handle it—and why rejection isn’t failure, it’s just part of the process.
The first 30 minutes: feel the feelings
When that rejection email lands, I let myself feel disappointed. Sometimes frustrated. Occasionally angry if the reviews are unfair.
I don’t immediately open the reviews. I don’t forward them to co-authors yet. I just… sit with it.
Why? Because if I read reviews while emotional, I’ll either:
Take every criticism as a personal attack, or Dismiss valid critiques because I’m defensive Neither is productive.
So: 30 minutes. Coffee. A walk. Maybe grumble to a colleague. Then I’m ready to engage rationally.
The first read: categorize the rejection
Not all rejections are equal. I mentally sort them into three categories:
Category 1: “We were wrong / the paper needs major rework”
Reviewers identified genuine methodological flaws Our claims were overclaimed We missed critical related work The contribution isn’t as novel as we thought Action: Major revision. Sometimes this means starting over.
Example: An early draft of our source localization work got (rightly) criticized for not comparing to enough baselines. We added 5 more methods, reran everything, and the paper got much better—and eventually published in Journal of Neural Engineering.
Category 2: “Wrong venue / minor issues”
The work is solid, but it doesn’t fit the journal’s scope Reviewers wanted more detail in areas we condensed The contribution is real but needs better framing Action: Revise and resubmit elsewhere (or to the same venue if minor revision is allowed).
Example: Our first federated learning paper was rejected from a pure ML conference because it lacked theoretical guarantees. We reframed it for a biomedical engineering audience, added clinical context, and it was accepted at IEEE FLTA with a spotlight.
Category 3: “Reviewer misunderstanding / bad luck”
Reviewers clearly didn’t understand the method Contradictory feedback (“too technical” vs. “not rigorous enough”) Comments that show they didn’t read carefully Action: Appeal if possible, or resubmit elsewhere with better explanation upfront.
Example: A reviewer once said our tensor regression method “doesn’t account for time.” Our method is literally a temporal model. We realized our intro didn’t make this clear enough. Fixed it, resubmitted, accepted.
The co-author conversation
I forward the reviews to co-authors with my initial categorization:
“This is Category 2—solid work, wrong framing. I think we should revise and submit to [Journal X] instead. Thoughts?”
Then I wait. Co-authors often see things I missed. Especially senior collaborators (shoutout to Prof. Liesbet Peeters and Prof. Marc Van Hulle)—they’ve seen this pattern before and can identify when to persist vs. pivot.
Pro tip: If you’re a student and your paper gets rejected, talk to your advisor before spiraling. They’ve been through this dozens of times. You haven’t.
The decision tree:
Here’s my mental flowchart for what to do next:
If reviewers identified real flaws: → Fix them. This might take months. That’s okay.
If the work is solid but wrong venue: → Identify 2-3 alternative venues. Reframe for the new audience. Resubmit within 2-4 weeks.
If reviews are contradictory or unfair: → Check with co-authors: do they see something I’m missing? → If not: resubmit elsewhere with a clearer intro.
If I’m genuinely unsure: → Talk to someone outside the project. Fresh eyes help.
If the paper has been rejected 3+ times: → Consider whether this is the right contribution at the right time. Sometimes you’re ahead of the field. Sometimes you’re just wrong. Hard to tell.
Real examples from my own work:
Paper 1: Finger Movement Decoding (BTTR)
Submitted to: Journal A Rejected: “Too computational, not enough neuroscience” Revised for: IEEE Transactions on Neural Networks and Learning Systems Outcome: Accepted. 14.25 impact factor. Became my most-cited work. Paper 2: Neural Networks for Connectivity
Submitted to: High-profile neuroscience journal Rejected: “Not enough mechanistic insight” Revised for: Applied Sciences Outcome: Accepted, but lower impact. Still contributed to the field. Paper 3: Federated BTTR (FBTTR)
Submitted to: ML conference Rejected: “Lacks theoretical guarantees” Revised for: IEEE FLTA (applications-focused) Outcome: Accepted with spotlight. Got way more attention from healthcare researchers than a pure ML venue would have given. Paper 4: (Still under review)
Submitted to: Machine Learning: Science and Technology Status: Waiting Backup plan: If rejected, will reframe for JBHI (more clinical angle) What I’ve learned:
Rejection is not a reflection of your worth as a researcher Even Nobel laureates get papers rejected. It’s part of the process.
Reviews are feedback, not verdicts Sometimes reviewers are wrong. Sometimes they’re right. Often it’s somewhere in between. Your job is to extract the useful signal.
Venue fit matters as much as quality A paper rejected from one journal might be a perfect fit for another. Match your contribution to the audience.
Persistence pays off—if you’re working on something real If reviewers consistently say “this doesn’t matter,” maybe it doesn’t. But if they say “this needs more work,” do the work.
Every rejection makes the paper better My BTTR method went through 3 rejections before the IEEE TNNLS acceptance. Each round of reviews forced me to clarify, add baselines, and strengthen claims. The final version was 10x better than the first submission.
The papers I’m waiting on (and what I’ll do if rejected):
Vertical Federated BTTR (under review at ML:ST): If rejected, will submit to JBHI with more clinical framing Cross-subject ECoG (under review at IEEE TBME): If rejected, will add more subjects and resubmit Cirrhosis prediction (under review at JBHI): If rejected, will strengthen statistical analysis based on feedback AF clustering (under review at JBHI): If rejected, will simplify and submit to conference for feedback I’m prepared for rejections. They’re coming. And when they do, I’ll follow the process above.
To students and early-career researchers:
If your paper just got rejected, I’m sorry. It sucks. Take the 30 minutes to feel bad.
Then:
Read the reviews carefully Categorize the rejection (fatal flaw vs. wrong venue vs. misunderstanding) Talk to your co-authors and advisor Make a plan: revise, resubmit, or pivot You’re not a bad researcher. You just hit a normal part of the research process.
And remember: Every published paper you’ve ever read was probably rejected at least once somewhere. You’re in good company.
Currently: 9 papers under review. 17 published (journal + conference). Countless rejections along the way. Still here, still submitting.
#AcademicPublishing #ResearchLife #PeerReview #PhDLife #PostdocLife #RejectionIsRedirection