My SECRET Research Method To Get Published in High School

Look, chances are you probably won't get an internship submitting a ChatGBT resume to research competitions with 10,000 applications who also chatted their resumes, but it doesn't mean all hope is lost. I want to talk about a

more clear-cut path to getting published that doesn't involve getting blocked by college professors after sending your 10th follow-up email. We've talked a lot on this channel about brainstorming, narrowing your scope, identifying a problem, but then you hit a wall. It

feels like there's always some data set that you need that you don't have access to or that you need 15 Google engineers to actually sit down and figure out how to write the code. How do you actually ascend out of the research trenches and get yourself a ticket to Paperville? I

want to walk through exactly what I would do so you can see that independent research isn't this impossible fairy tale. You just haven't seen all the

tale. You just haven't seen all the angles yet. Now, if you're actually

angles yet. Now, if you're actually serious about this, I need 30 seconds of your undivided attention. Because if you don't follow this next point, you might as well just click off the video and go take a nap. There's no point in watching. The absolute first step in the

watching. The absolute first step in the research process is learning about the topic that you're interested in and you do that by reading papers and these are good quality papers and publications that you can find online. Some of the

best places to start are Google Scholar, you have PubMed, any field specific journals that you want to just go through and read. This is how you get acquainted with what's going on in a field and what are the current key questions that scientists are trying to

answer. Now, here's the catch. You might

answer. Now, here's the catch. You might

be broadly interested in a field like physics for example. But if you go online, look up top physics journals, open up a paper, and start reading.

You're going to be completely lost. And

that's not your fault. It's just that the chances are the first time you go on to read a fulllength journal article, there are going to be so many terms in there that you don't understand. Even

the format of the journal article itself might be something that you're not used to reading. We're in 2025. Just be real

to reading. We're in 2025. Just be real with yourself. When was the last time

with yourself. When was the last time you even read a book, let alone a journal publication? Point being, it's

journal publication? Point being, it's not only hard to just keep your attention span to read through the paper, but given how difficult it is, most people just give up before even reading a handful of papers on the subject they're interested in. I have to

start here because I've spent the last week putting together this video. And

what I don't want to happen is that you see all these different strategies that I talked to you about about reading abstracts, reading papers, you go online, and within the first five papers, you just give up and then never follow up. I'm telling you right now,

follow up. I'm telling you right now, it's supposed to be hard. That's why it matters. If it was easy, someone else

matters. If it was easy, someone else would have done it. All of this leads us to step one of the pipeline, which is exactly why you're here. How do we come up with brand new research ideas that no one else has done before? We're going to

do this by mining ideas from research conferences. And I'm going to show you

conferences. And I'm going to show you exactly how. For think, what are

exactly how. For think, what are research conferences? They're

research conferences? They're essentially gatherings where scientists come together and they share the current research they're working on. Oftent

times, they'll even just share the abstracts for their work. So, the

general concept, their early results without even having the full paper or manuscript ready. The main idea behind

manuscript ready. The main idea behind this and why research conferences are important to us is that these events are where the newest research in every field is being showcased. If you were to just

go online to Google Scholar or PubMed and scroll through recent articles, sure, you can sort by articles that were just published in the last year or so, but at the end of the day, if you're looking for something field specific, you don't know how truly new that

research is. It might have been

research is. It might have been officially published a month ago, but scientists were actually working on it for 2 years. Sometimes that whole publication process itself is really long and tedious. But when you look at research that's being showcased at a

conference, you have that guarantee that it's brand new. People were just working on it. This is an absolute gold mine for

on it. This is an absolute gold mine for us because within each field that you might be interested in, there's a whole range of conferences that are happening year round. Almost every, you know,

year round. Almost every, you know, couple of weeks, couple of months, there's going to be some conference that just happened. And by looking at what

just happened. And by looking at what questions researchers or doctors or scientists are tackling at these conferences, we can get inspiration for our own projects. Our goal with this exercise is to spot trends and in turn

gaps in the research field. Because at

the end of the day, if you're going to go on to publish, what does that actually mean? Being able to put

actually mean? Being able to put together a publication means that you answered a research question that addressed a gap in a field. You identify

that gap by looking at different trends that you learned from reading abstracts from research conferences. You get the gist, bro. Now, I'm literally itching to

gist, bro. Now, I'm literally itching to pull up the screen recording and show you guys exactly how we're going to do this. But there is one more point that

this. But there is one more point that we have to talk about because this is the secret sauce for exactly how we're going to come up with the key ideas that are going to get us those pubs. One

takeaway from this video that sticks with you for the rest of your research career. It's this. You do not have to

career. It's this. You do not have to reinvent the wheel when it comes to your project. Pique, you just spent the last

project. Pique, you just spent the last 30 seconds building up to that point.

What does that mean? So many people are inspired to get into this research sphere because they hear about someone's like insane, super clever, crazy project and they want to recreate something similar. But the truth is the majority

similar. But the truth is the majority of research projects are simply taking one step forward from a long line of people who have worked on research projects on similar things before them.

Your goal is to look at everything they're doing in a field and take one step forward. Answer one small new

step forward. Answer one small new question that no one else has looked at.

So here's the really clever thing that we're going to do. People in different fields are conducting research on different things. So for example,

different things. So for example, imagine that you want to do research in the broad field of medicine. I'm a

medical school student. Let's just roll with that. Within medicine, there's an

with that. Within medicine, there's an infinite number of subcategories that you could explore. Maybe you want to do research in cardiology. Maybe you want to do something related to pediatrics or something related to psychology. Each of

these individual fields has its own set of top journals and its own set of questions that have or have not been answered. This leads us to two key

answered. This leads us to two key points. First of all, given that fields

points. First of all, given that fields within something like medicine are very different and they have different journals and they publish at different rates, some research areas are just going to be more developed than others.

So for example fields like cardiology, pulmonology, emergency medicine, these have a very high volume output of research being conducted and research papers because there are a ton of key questions to explore. It's very popular

in these fields to answer the question.

Now at the same time we have point number two which is the fact that within fields of medicine there's tons of overlap in ways that you wouldn't necessarily expect. Let's start with a

necessarily expect. Let's start with a very simple example. Cardiology and

cardiothoracic surgery are two distinct fields within medicine. However, because

they both involve the heart, there's a ton of overlap between the two.

Cardiology has its own journals and conferences and so does cardiothoracic surgery. Now, let's just imagine for the

surgery. Now, let's just imagine for the sake of our example that cardiothoracic surgery had more research output. There

were a lot more questions being answered there. Our goal would be to take

there. Our goal would be to take inspiration from some research that's being done very recently in CT surgery and apply it to cardiology. Let's use a specific research question to help make this very clear. Say that we're going

through the abstracts from a very recent CT surgery conference and we come across a paper that's looking at studying the match rates of students from medical school who are trying to apply into CT residency programs. This particular

study is looking at the average number of publications that students had and what residency program they were able to match into it because of it. Now, let's

say we like this idea. We think it's pretty interesting. We can now go into

pretty interesting. We can now go into the cardiology literature and see what has been done. We can go through PubMed.

We can go through online searches. go

ahead and look up all the different keywords surrounding this particular idea to see what scientists have already done. In an ideal world, we're looking

done. In an ideal world, we're looking through the cardiology literature and we realize that this same question hasn't been applied here. No one has done a study looking at the number of publications med school students had who are interested in applying to cardiology

programs as opposed to CT programs which has been studied. This is what I mean when I say we don't have to reinvent the wheel. someone has answered a question

wheel. someone has answered a question in another field and you can go take inspiration from that paper to apply it to another similar field where the question hasn't been answered. Let's go

ahead and jump right into it and do something completely different. In all

these research videos, I always talk about like my own personal epilepsy research in high school. So, let's do something related to neurology. Okay, in

our previous example, we were looking at cardiology versus cardiothoracic surgery, which are two similar but distinct fields. Now, let's pick

distinct fields. Now, let's pick neurology and then another field within the umbrella of medicine that has some connections but also some differences to neurology. I'm personally thinking

neurology. I'm personally thinking sports medicine. Now, how did I just

sports medicine. Now, how did I just come to the conclusion of sports medicine? Personally, I watch sports. I

medicine? Personally, I watch sports. I

love watching the NBA finals right now.

I love watching football. And so, to me, seeing people get hit with like a crazy tackle and then ending up having some kind of CTE down the line or some kind of a stroke, that's really interesting, right? What can we do to protect our

right? What can we do to protect our players? What can you do to help prevent

players? What can you do to help prevent these injuries? If there's a field that

these injuries? If there's a field that you're interested in, chances are the more you learn about it, you'll come to find that there are different connections to other fields or other aspects. We don't need to dig too deep

aspects. We don't need to dig too deep on that here. Let's just run with this example for now. We have neurology and we have sports science. So, if we want to take ideas from, for example, sports science and apply them to neurology.

We're going to need to start by looking at conferences that have sports science research. Just like we talked about at

research. Just like we talked about at the start of the video, we can just start by looking up sports science uh medicine research conferences

and we'll just say 2025. We're now given just a list of links that you can go through one by one on your own time.

What pops out to me personally is I see this one are American Orthopedic Society for Sports Medicine. They have a 2025 annual meeting. You can go to their

annual meeting. You can go to their website and you can go ahead and just scroll through some of the details here.

Now, in particular, what we're looking for is a website that actually gives us a bunch of the abstracts that are being presented at these conferences. Most

conference websites will have this, but it also depends a little bit on the timing. If people are still submitting

timing. If people are still submitting their abstracts to the conference at this time that they're likely not going to have that updated list of just abstracts that you can go ahead and read through. Just going back here, you can

through. Just going back here, you can go ahead in your own time and scroll through every single one of these, right? Go to the website, read about it,

right? Go to the website, read about it, what kind of research is being done.

Just to skip us a little bit of time, I went ahead and found one particular conference that's going on right now.

The website we're on is looking at the Clinical Journal of Sports Medicine. And

if we just scroll down here, this issue, we are proud to bring you all of the abstract presentations from two of our major affiliate society membership organizations ahead of their 2025 society annual conferences. Right? And I

have a bunch of other details here. This

is like the AM SSM annual meeting.

Doesn't really matter to us. What

matters to us is if we scroll down here, we immediately see a couple of these editor picks, right? these

abstracts/papers that we can go ahead and read. Doesn't matter which one we

and read. Doesn't matter which one we pick. I'm just going to go ahead and

pick. I'm just going to go ahead and pick this one. So, go ahead, click download on the PDF. And here we now have a 9page article going over the particular study. We're a little bit

particular study. We're a little bit lucky here because we have the entire manuscript to read through and learn about. A lot of times you'll only just

about. A lot of times you'll only just see the abstract, but it doesn't really matter. The whole point here is we want

matter. The whole point here is we want to get a gist of what the actual project idea is, not the exact technical details of what their results were or how they went about doing it. I just took a minute to go ahead and read through the article. It's relatively

article. It's relatively straightforward. Basically, what they're

straightforward. Basically, what they're looking at is what tools and metrics physicians used to decide whether or not like players after getting a concussion from like a sporting event are good to return back to play. And so,

specifically what these like results or findings are showing us is that for physicians, they rely a lot more on like symptom checklists as opposed to a computerized neurocognitive test. These

authors are using these findings to basically say, hey, there's a strong need for a more like reliable or consistent way to determine whether or not players are returned to be fit and there's a gap here that people in future studies should explore. Now that we've

read the paper and we have some understanding of it, the next step is the very critical one because this is where we come up with our own idea. Our

goal is to apply this to neurology. So,

we need to start thinking, hey, what other adjacent ideas or something similar can be done within that field on problems that are more closely related to us, things that we know about. I

spent a good amount of time actually brainstorming with this specific paper and I'll give you my pitch for what someone could do with it. This

particular study if we actually like go through and read it and I really recommend that you guys do too. I'll put

a link to it in the description. What

they're basically doing is surveying people at a bunch of different levels.

They're surveying sports medicine professionals about how they're handling cases related to this range of different athletes. So, we have like Olympian

athletes. So, we have like Olympian level athletes, professional, college, that sort of thing. Now, if we scroll back up to the title of the paper, right, they talk about return to play.

That's their general concept. return to

play. What if we made a similar study for neurology that was all about return to learn? So instead of looking at how

to learn? So instead of looking at how sports medicine doctors determine whether or not athletes are ready to return to playing their game, we can look at how neurologists or even like school level health professionals are

able to determine whether or not someone just in your local high school are ready to return to learn after some kind of concussion or traumatic brain injury. If

we want like a realistic way of doing the data collection here, you as a high school student could send out surveys to all of the local health professionals in your local school district. Or if you want to go one step higher, you send out surveys to neurologists or pediatricians

in your area and ask them how they go about doing this. What tools or criteria do they use? How confident do they feel?

What things would make them feel more confident in their decision? Are there

particular aspects of the test or certain tests they wish they could run but they're not able to? Your end goal is to look for a range of different things, right? any trends, any gaps, any

things, right? any trends, any gaps, any questions answered. But at the end of

questions answered. But at the end of the day, it's this pipeline of reading abstracts online, things and research that people have already done, and trying to put your own new spin on it.

And notice how we're not just ripping off the exact same research question either. We're strategically taking

either. We're strategically taking something that has been done, taking inspiration on it, taking that one step forward, and then applying it to a new field that we want to focus on. When it

comes to streamlining your research process, especially at a high school level, I am a big believer in leveraging AI wherever you can. So, for example, if I'm going through and reading these new abstracts, learning a bunch of new concepts, I would very much prefer to

have something like chat GBT open in a window right next to me so I can continuously just look up keywords or ask for summaries or ask for explanations of concepts that I don't understand. There's going to be so many

understand. There's going to be so many new terms and jargon that you're going to get exposed to when you're going through this. You can speed up your

through this. You can speed up your workflow and just literally just absorb knowledge if you constantly are getting explanations from chat in a way that works for you. Now, the one thing I don't recommend doing here is you can't just take everything that we've done in

this video and ask chat to do it for you. You can't ask chat to come up with

you. You can't ask chat to come up with all these ideas for a very practical reason. It's the fact that these AI

reason. It's the fact that these AI models are trained on the papers that are out there. So, when it comes to actually like unique original thought, I mean, you're trying to come up with an idea that hasn't been done before. The

model is only going to be able to give you answers back on things that it knows or it has seen. So, if you ask it for ideas, chances are it's just going to tell you a bunch of ideas that are already out there, that already exist.

I'm telling you because I have tried it.

It just hallucinates like crazy. It will

literally tell you that an idea it's giving you is brand new. It's never been done before. And all you do is go on

done before. And all you do is go on PubMed, look up the main keywords surrounding that project, and you will find 10, 100 papers on the exact same topic that it's telling you nothing has been done before. However, if you need some introlevel inspiration, right, what

are some good field connections? What's

a little bit unique? Where can I start?

That's where it could be useful. Now, if

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point, we've gone through the main research pipeline and so hopefully you should be set to go on to create your own ideas. But now we need to talk about

own ideas. But now we need to talk about the practicals of how you're actually going to take that idea and get it published. Here's the truth. I won't

published. Here's the truth. I won't

sugarcoat it. To get published, you need a research mentor. This idea of like independent research is a little bit of a misnomer because at the end of the day, if you want to submit two journals, the journals are not just going to let

you as an individual high school student just throw your journal out to them. And

I had to learn that the hard way. When I

was in high school doing my epilepsy research, I pretty much did the entire thing on my own. and I came up with the ideas, coded the algorithms, did the testing, set the pace and direction of the project, I had a couple of different like small external mentors, but really

they were just there to provide a little bit of like guidance or feedback if I had a question or two. But when it came time to eventually submitting to journals, the very first round of feedback that I got from everyone was, hey, you need to have a mentor on this

paper or else we're not going to take it seriously. And looking back on it now,

seriously. And looking back on it now, it does make sense, right? Imagine that

you're like a top journal. You're not

even a high school journal. like a a top official journal in these respective fields. Are you just going to let a

fields. Are you just going to let a random high schooler with no prior publication history and no affiliations with any institutions just publish? What

kind of guarantee do you have that any of the results are not just like completely made up? If you're publishing in a high school level journal, which I personally think is totally fine to get started. I've published in Ji. I think

started. I've published in Ji. I think

they're great. Your mentor can literally be as simple as your high school science teacher. As long as you know them well

teacher. As long as you know them well and they're willing to give your manuscript like one read through just to prove it, then you're good to go. In

this scenario, you're very likely, like 99% chance you'll be able to get a mentor who's one of your teachers, but at the same time, you're very likely going to do 99% of the work. It's more

so that you're bringing them onto this paper as like a formality and to give you that stamp of like authority than actually having them be a big part of this research process, unless that's something you've specifically talked to them about. Now, the second option here

them about. Now, the second option here is to aim one level higher than that.

Let's say that you want to publish in like an official journal or you're a little bit earlier on in the research process and you genuinely do need like a little bit of guidance or some kind of institute affiliation to maybe get

access to PubMed or some kind of databases then I think it's absolutely worth your time to reach out to college professors. Now nine times out of 10 if

professors. Now nine times out of 10 if you're reaching out to people this is going to be cold emailing but you are way way more likely to get a response and here's why. When you already have an idea, professors are 10 times more

likely to actually be willing to respond to your email and get onto your project.

Especially if this research is in their field. Professors love it when students

field. Professors love it when students show initiative. Right? You already have

show initiative. Right? You already have the idea. You've done the leg work.

the idea. You've done the leg work.

You're coming to them asking them if they just be willing to support you on this journey. You're taking the front

this journey. You're taking the front seat. You just want them to be there to

seat. You just want them to be there to guide you. And if you want to know how

guide you. And if you want to know how to email or approach a professor, boom, 13 minute 4-second guide already made for you. literally a step-by-step guide

for you. literally a step-by-step guide with a copy paste email template. I know

you guys want me to roast more college applications, but I spend so long making these videos only for them to go triple plastic. I literally wrote the email

plastic. I literally wrote the email template for you. How much easier does it get? I think as we enter the next

it get? I think as we enter the next chunk of this video, it would be insanely helpful to talk about the different types of studies and papers that you can do. If you're doing this research work for home, which is very, very likely, there are certain types of

research that are easier to pull off than others. And you also want to know

than others. And you also want to know what all the options are. So, as you're going through and you're reading different manuscripts and you're getting inspiration, you have all those different dots in your head to put together a new idea or a new concept.

One option is to do a literature review, which is a little bit different than like the empirical science that we've been talking about. In the case of a literature review, what you're basically doing is reviewing all of the different studies and concepts around a particular

topic and then compiling a summary of them. You're surveying and synthesizing

them. You're surveying and synthesizing what is already known to highlight key trends or findings that would be useful to someone who is just entering the field. For a lot of papers, you'll do a

field. For a lot of papers, you'll do a literature review as part of putting together your introduction to set the stage for your research. However, you

can also publish a literature review.

I'm not going to go into the exact details here because there's a ton to talk about, but I want to keep on your radar so that you guys can look into it on your own time. One step further from this would be like a systematic review where instead of just broadly analyzing

the literature on a topic, you're actually reviewing all the relevant articles. And so, you have a very

articles. And so, you have a very specific rigorous methodology for finding all the relevant papers and then putting together the information. That's

another option for you to look into.

Bring it back to our empirical more traditional question and answer style. I

think that trend studies in data comparisons are also very very common at this stage. As you're reading papers in

this stage. As you're reading papers in a particular field, familiarize yourself with what the publicly available data sets are. You never know when you'll

sets are. You never know when you'll come across a particular gap that someone hasn't answered using a publicly available database or if you can leverage it to answer some other question. Just to give you a couple very

question. Just to give you a couple very simple ideas to get the, you know, the gears in your brain going. Things like

time analysis, looking at particular trends over a period of time, things related to COVID are also very, very common. These are easy starting points

common. These are easy starting points for you. Or even if there's like a

for you. Or even if there's like a monetary angle here, maybe you're looking at socioeconomic factors and how they're impacting people. Or if you're looking at patients in medicine, for example, does the impact of certain patients coming from more

socio-economically underprivileged areas lead to them having worse healthcare?

The more you dig into a field, the more different angles and ideas you'll have to come up with novel ideas. If you're

completely absolutely lost on where to start, then I think a great place to understand how people are going about doing these research projects and getting some more inspiration from your own is to just start with very widely

used publicly available databases. Every

field has a ton of these. You can just do a quick Google search for what like the publicly available databases are in the field that you want to study and then you can go ahead and find them.

Now, I think what would be a lot more unique and fun and much more likely to get published in a solid journal would be for you to create your own data sets.

Now, this can be specific to whatever question you're trying to answer. So,

for example, I'm just fully going off the dome here. Imagine that you made a database of all the different school mask policies in your state and looked at how those compared to COVID spread

trends. Maybe you individually email

trends. Maybe you individually email each school and ask, "Hey, from uh 2020 to 2024, can you give me the timeline for what your mask policies were?" And

then you take that data, put together your own data set, and then compare that to other trends that you found online.

Understand that the more initiative you're willing to take in data collection you do, the more likely it is that your idea is unique and hasn't already been attempted by the millions of people who are already conducting research. As you're reading through

research. As you're reading through papers and figuring out what's feasible or not, you might have to run through dozens of ideas before you find the one that's truly original and actually

practical. But when you do, and all it

practical. But when you do, and all it takes is one good idea, that's a paper waiting to be written. As you begin your data collection process, you'll realize that the next step from here is to actually do the analysis. And there's a

couple key skills that you'll very likely want to pick up to not only streamline this process, but also add a layer of complexity and originality to your work. I think it's absolutely worth

your work. I think it's absolutely worth learning how to use a statistics focused programming language. So for example,

programming language. So for example, the one that I really recommend is R. I

recommend R because I feel like it's relatively simple. I didn't have much

relatively simple. I didn't have much coding experience when I learned it and I was able to pick it up in a couple of weeks, especially nowadays when you can use Chad GBT models like 04 Mini, which I think is really good for coding. It

does most of the R coding for you. You

just need to have enough of a grounding in the programming language to be able to follow along and debug if AI just starts hallucinating. The reason this is

starts hallucinating. The reason this is valuable is because it lets you really efficiently perform like a ton of important statistical tests. So you

might have learned in school about things like power or an ANOVA or a t test. There's all these different

test. There's all these different statistical terms that you'll pick up as you read more papers or let you do all of these very efficiently. I'm also

always going to encourage you to learn the basics of Python and machine learning. It will help you regardless of

learning. It will help you regardless of whatever field you want to go into. I am

studying medicine and I cannot tell you how many opportunities and doors having a basic understanding of machine learning has opened for me. We talked

about how finding like a unique angle between two fields that intersection point is where there are some new ideas.

Think about how machine learning adds in a new angle there. If I'm surrounded by a bunch of people who are also studying medicine and are very familiar with things like biology and chemistry, it's more likely that projects involving those like basic science concepts are

going to be tackled by people because they're familiar with it. And so if I have the exact same skill set as everyone around me, well then it's very difficult to come up with an original idea because it's likely that someone a couple years ago already tried asking

that question. But if you introduce a

that question. But if you introduce a new skill here, like for example, you're comfortable in coding in Python and you can apply a machine learning algorithm.

Well, that's not something that everyone in medicine is familiar with. And so now I have this new advantage, this new lens that I can look at questions with. And

it opens this whole new world of possibilities for questions that I can tackle and papers that I can eventually write and publish. You want to give yourself a leg up in whatever way you can. And so if you're early in the

can. And so if you're early in the research process, the extra effort you put in now will pay off hundfold down the line. The difference between

the line. The difference between students who are able to publish and those that go unpublished is persistence. Every time you hit a wall,

persistence. Every time you hit a wall, you don't give up. You open up PubMed and you get back to reading papers.

That's exactly what you do. If you keep trying to come up with ideas day in and day out, eventually one will hit and that's all you need. If you're working on a research idea and you want my personal thoughts on it or my feedback on it, feel free to send it in through

my website and I'm happy to help. If

you'd also like me to review your college application or your essays for an upcoming competition or university, I'm happy to also review them on my website. 48 hour turnaround time. You

website. 48 hour turnaround time. You

know that I got you. Thank you all so much for watching. This has been your boy Pratik. Peace.

boy Pratik. Peace.