I've published some papers in artificial intelligence as co-author. No one asked for educational backgrounds. And I've published papers in applied math as sol

I've published some papers in artificial intelligence as co-author. No one asked for educational backgrounds. And I've published papers in applied math as sole author: Again, no one asked about educational background. I do have a relevant Ph.D., but no one asked. I suggest, write a good paper, look for appropriate journals, and submit to one of them. Maybe speed up the process a little: Send a copy of the paper (or PDF file, as they wish) to the editor in chief with a cover letter not making a formal submittal but just asking if, first glance, might this paper be of interest for their journal? I never paid anything, no page fees, etc. to publish. None of the papers, co-author or my sole author papers, got rejected. Here are some hints that might help: (1) Write the paper, especially in the abstract and the first paragraphs, like you really know technically just what the heck you are doing. E.g., I started one sole authored paper where I mentioned that a derivative I was taking was a "dual vector" -- not everyone who writes such applied math pays attention to duality. (2) In each of my sole authored papers, some of the key topics, prerequisites, etc. were advanced and narrow enough that I'd guess that less than 10% of the editors had all the prerequisites. (3) I suggest that write applied math, mathematical statistics, and computer science making important and appropriate use of some relatively advanced pure math. (4) Generally I suggest that just write applied math, with nearly all the content in theorems and proofs, for mathematical statistics, computer science, machine learning, artificial intelligence, etc. The usual criteria for publication are "new, correct, and significant", and new and correct theorems and proofs are big steps forward for these criteria. If the theorems are also, in the paper, relevant to some applications or an applied field, then that can help with "significant". (5) Know quite well just how the heck to write math. A good way to learn this is to have the equivalent of a good undergraduate major in pure math. A good, first start on such writing is a theorem proving course in abstract algebra, one that starts with sets and foundations and, then, all based on just sets, develops groups, rings, fields, the rational, real, and complex numbers, vector spaces, linear independence, linear transformations, subspaces, null spaces, quotent spaces, duality, the adjoint transformation, eigen values and eigen vectors, the Hamilton-Cayley theorem, inner products, Hermitian and Unitary operators, maybe group representations. Then have a good course in linear algebra, e.g., from the classic P. Halmos, Finite Dimensional Vector Spaces (one of the best writers of math). Then a good course in analysis, e.g., from W. Rudin, Principles of Mathematical Analysis, with highly precise writing. With a few more such good, pure math texts, courses, etc. where the homework is essentially all theorems and proofs and graded by a good mathematician who cares, one will no doubt learn how to write math, and the learning will show. In my case, I got a good start in a course in abstract algebra, with a good prof who did well grading my papers, and then learned the rest just by studying really good writers, learning how they wrote, without more good grading. How to write math is no big secret: There're a LOT of beautifully written math texts on the shelves of the research libraries.