Recently, I had one of my papers rejected by a journal to which I had submitted it. They were kind enough to write back, stating that while they found the paper interesting, it was not a good fit for their publication. Interestingly enough, I basically agree with their conclusion and have since submitted the paper to another journal that seems more suitable.
Rejection is actually a fairly common occurrence in my academic life, happening to me about one or two times a year on average. I occasionally mention this fact to my students and colleagues, who are sometimes surprised to learn that my rejection rate is far from zero. Over time, I’ve come to realize that our field tends to publicize successes while keeping failures under wraps, unless those failures are somehow controversial.
In sharing this experience, I want to delve a bit deeper into the process and feelings surrounding rejection:
**The Experience of Rejection**
I once had an interesting experience with a rejection. A co-author and I had nearly solved a conjecture, only to have the paper rejected by a journal on the grounds that we hadn’t solved the entire problem. Later, when we finally proved the full conjecture, the same journal rejected us again, this time because the improvement was only for an epsilon term.
**The Selection and Workflow of Reviewers**
This incident sparked a discussion about the selection and workflow of reviewers. Some commenters noted that the choice of reviewers can sometimes be arbitrary, with personal biases and opinions influencing the process. There was a suggestion that papers should be anonymous to reviewers to avoid such biases.
**Deep Dive into AI**
It’s also worth mentioning that I’ve invested a significant amount of effort into the field of AI. On multiple occasions, I’ve discussed the potential of AI in mathematics and science, believing that the combination of AI and human intelligence will lead to a new era in mathematics.
Here are some key takeaways from my experiences and thoughts:
– Rejection is a normal part of the research process.
– The selection and workflow of reviewers is a contentious issue in academia.
– My work in AI suggests that the synergy between AI and human intelligence will pave the way for new breakthroughs in mathematics.
Below is a formatted version of my story for a WordPress blog post:
—
In the realm of academic research, rejection is an all-too-familiar shadow looming over the endeavors of scholars worldwide. Recently, I found myself in this common predicament when a journal decided that my paper did not align with their publication’s focus. Yet, rather than harboring disappointment, I embraced this feedback with a sense of acceptance and immediately sought a more suitable venue for my work.
It’s a tale I share not with a sense of defeat but with a researcher’s pragmatism. On average, I face this scenario once or twice a year. Such rejections are not openly discussed in our field, where successes are lauded and failures often kept silent, unless they stir controversy. However, I believe there’s value in transparency and in the lessons learned from these experiences.
**A Tale of Rejection**
One memorable instance of rejection involved a paper that my co-author and I had crafted with meticulous care. We had nearly cracked a long-standing conjecture, but our victory was bittersweet. The journal’s response was that our partial solution did not suffice. Later, when we did manage to solve the conjecture completely, we were met with another rejection from the same journal, this time criticizing the incremental nature of our improvement.
**The Review Process: A Balancing Act**
This narrative sparked a lively debate about the review process in academia. The choice of reviewers and their approach to evaluating papers became a focal point of discussion. Suggestions emerged about maintaining anonymity to strip away potential biases and ensure a fair assessment.
**Explorations in AI**
Beyond my experiences with rejection, my journey in the field of AI has been one of profound exploration. I’ve delved into the applications of AI in mathematics and science, envisioning a future where AI and human intellect merge to forge new paths in mathematical discovery.
In reflecting on these experiences, I am reminded that rejection is not merely a setback but a catalyst for growth and learning. It is a testament to the iterative nature of research and the continuous pursuit of knowledge. As we navigate the complexities of the academic world, we must remember that each rejection is a step towards a better understanding and a chance to contribute to the ever-expanding horizon of human knowledge.
—
Note: The formatting here is tailored for a WordPress blog post, with headings and a narrative style that maintains a balance between the rigor of scientific discourse and the human element of the researcher’s journey.
