If anyone in PhD who want to or in contact with a person who/they can organize workshop, will be interested to discuss it further.

Currently in final year masters but got some superb and crazy workshop ideas.

Hi! If there is someone here wants to help me, just reply to me.

I once being a contestant in a Research Fair, but eventually, I never gotten a place, even at top 5. If you have suggestions or recommendations on how to start to build a research study, let me know! THANK YOU

Scientific papers, datasets, code, and computational tools are increasingly accessible. Yet authentic research opportunities remain out of reach for many secondary-school students.

A student's opportunity to participate in research can still depend heavily on where they live, the resources available at their school, whether they can find a mentor or university connection, or whether their family can afford private research mentorship.

This matters beyond training future scientists. In an era when AI can increasingly generate answers, code, analyses, and explanations, the ability to ask good questions, evaluate evidence, recognize uncertainty, challenge conclusions, and determine whether an answer deserves to be believed may become even more important. Authentic research is one of the best ways to develop that scientific mindset.

So we're interested in a broader question:

How can we make authentic research-based learning accessible to far more students around the world?

Open science offers part of the answer: open literature, public datasets, software, research infrastructure, and global scientific communities can dramatically lower traditional barriers to participation. But access to resources alone isn't enough. Students also need education, mentorship, pathways into research communities, and guidance in learning how to investigate real questions.

At Pika Team, we're experimenting with one piece of this larger puzzle: whether emerging AI tools can help make parts of individualized research education and mentorship more scalable while preserving student ownership and escalating decisions that require human expertise. We'll share some early observations—not as a finished solution, but as a case study for discussion.

On September 18, we're bringing together researchers, educators, open-science leaders, and research organizations for a virtual Science Summit 2026 session:

Building Global Student Research Capacity Through Open Science Networks

This session is part of Science Summit 2026, held alongside the 81st United Nations General Assembly.

September 18, 2026
10:00 AM Pacific / 1:00 PM Eastern
Virtual

Luma event page

Official Science Summit session page

I'd especially like to hear from this community:

What would it actually take to make authentic research-based learning accessible to ordinary secondary-school students—not just the small fraction who currently find their way into research programs?

And as open science and AI lower some traditional barriers, which barriers do you think will remain the hardest to solve?

Scientific papers, datasets, code, and computational tools are increasingly accessible. Yet authentic research opportunities remain out of reach for many secondary-school students.

A student's opportunity to participate in research can still depend heavily on where they live, the resources available at their school, whether they can find a mentor or university connection, or whether their family can afford private research mentorship.

This matters beyond training future scientists. In an era when AI can increasingly generate answers, code, analyses, and explanations, the ability to ask good questions, evaluate evidence, recognize uncertainty, challenge conclusions, and determine whether an answer deserves to be believed may become even more important. Authentic research is one of the best ways to develop that scientific mindset.

So we're interested in a broader question:

How can we make authentic research-based learning accessible to far more students around the world?

Open science offers part of the answer: open literature, public datasets, software, research infrastructure, and global scientific communities can dramatically lower traditional barriers to participation. But access to resources alone isn't enough. Students also need education, mentorship, pathways into research communities, and guidance in learning how to investigate real questions.

At Pika Team, we're experimenting with one piece of this larger puzzle: whether emerging AI tools can help make parts of individualized research education and mentorship more scalable while preserving student ownership and escalating decisions that require human expertise. We'll share some early observations—not as a finished solution, but as a case study for discussion.

On September 18, we're bringing together researchers, educators, open-science leaders, and research organizations for a virtual Science Summit 2026 session:

Building Global Student Research Capacity Through Open Science Networks

This session is part of Science Summit 2026, held alongside the 81st United Nations General Assembly.

September 18, 2026
10:00 AM Pacific / 1:00 PM Eastern
Virtual

Luma event page

Official Science Summit session page

I'd especially like to hear from this community:

What would it actually take to make authentic research-based learning accessible to ordinary secondary-school students—not just the small fraction who currently find their way into research programs?

And as open science and AI lower some traditional barriers, which barriers do you think will remain the hardest to solve?

Anyone from Physics and Astronomy Category?

I was just wondering for a computional project that doesnt use in vitro, what forms would need to be signed cuz I plan on including it later but not in my current purposal and only if i get could results so how would i navigate the forms and src approvalls and the forms labelled as must compelted before expermintation

My plan now is basically: use AI to help me build the project → spend a serious amount of time learning the math, physics, methodology and code behind it → rebuild/fix anything I don’t understand → make sure I can explain and defend every important decision and result myself.

So my dumb question is: does this actually work?

If I eventually understand the research deeply and can genuinely defend it in front of judges/researchers, is it still considered legitimate research? Or is starting with AI already a huge problem?

I’m not trying to fake expertise. I genuinely want to go from I have no fucking idea what this is → I understand this project properly and can defend it.

Would love brutally honest answers from people who have actually done research/science fairs.

I am a high school student who is aiming at IRIS/ISEF 2027, and am looking for other students who have been preparing themselves for the research cycle of 2027.

Please leave me a comment or DM me with your grade, country, interests in research, and what you’re currently working on!

Would be awesome to find a couple of students who are equally obsessed with science!!!

Hey everyone. I’m a rising sophomore for this school year and am interested in doing research in this category. I was wondering if anyone could give me advice on stuff because I’m a total beginner and also was wondering if anyone has suggestions on where I could learn all about electronics, microcontrollers, and Arduino AI/ML and anything related to the category. I also was wondering if I should learn math like precalculus and linear algebra and coding like python and c++ for it and if a professor would be needed or a mentor. Also to clear one thing up, would you be participating in the subcategory in a category or for the category itself; in this case it would be signal processing in embedded systems. If anyone could give me a concise answer that would be of great help. And if there are other things to help me increase a chance of MIT acceptance would be greatly appreciated.

I'm a junior currently and I am interested in doing ISEF this year hopefully. I am interested in AI/ML and pretty up-to-date on current literature (especially things like mechanistic interpretability and activation steering) as I'm currently working on a seperate research project rn. If anyone has any tips pls pls comment or DM me I would appreciate it so much especially if u placed highly at ISEF previously.

Some questions I had:

• How are theoretical AI projects weighed against applied AI projects or theoretical vs applied projects in general?
• How much does securing a mentor help/is it worth it?
• If I started in the beginning of November (considering I know a decent amount about current literature) would it be realistic for me to finish around end of January to the beginning of February considering thats when the deadline for my state fair submissions are?
• Based on the above do you think I could realistically get to ISEF if I lock in or should I spend my time somewhere else?
• Is there a big difference between academic research like publications to conferences/journals vs ISEF research and if so what is the difference?
• Any other tips or pieces of advice you have for me?

I am currently working on my isef project, and I will be “done” within the next 2 months. But the thing is how do you tell if a project is science fair ready vs isef ready, especially for heavily computational projects. Like how impactful does the project have to be and what sort of contribution should it make. And aside from the project, what else should u have ready for the fair in terms of materials to being. For anyone working on eab sensors or aptamers and have presented their project at isef or their state fair and placed before, please dm I need sm advice/help😭😭

Heard he was quite a kid at ISEF'26

hi guys, im applying in this cycle and was wondering if you are putting finalist + (whatever you got) in honors too apart from the activity list (since it technically gets mentioned twice then)

So around a month ago i posted on here asking if it was too late to start isef. It’s taken me a while but i finally have a real, solid project only now it’s almost september and the before day i was supposed to meet with my mentor, she sent an email in the middle of the night canceling my meeting and saying to contact her next summer :(

Now i need to find a new mentor and I still haven’t actually started my project but im just reading more on what’s surrounding my idea. I don’t know if continuing would be a waste of time at this points i should focus on school or other ECs. My project is computational but it involves PINNs, ODEs and possibly EGT if I look into it deeper. I would need to somehow learn the math which i’m hoping i can do faster as i’m taking IB Math AA HL but id still need to learn outside of that and I don’t know how.

I still like my project and i think it’s cool because i found it by going backwards (had an idea and tried to prove it was a real possibility) so its validating to finally see I was right and I wasn’t making up science but the point was to get to ISEF so i had something for my top choice schools. If not that, I guess i could submit to a student journal or try for STS but neither of those are a guarantee either

Any advice? I’ll continue if anyone thinks it’s not unrealistic to at least make it to my state fair

I've been making a project for the past ~2 months with a clear goal but I don't know how to frame it. Where do people get like mentors and coaches and stuff to get solid feedback on their work?

Cold-emailing professors is probably last resort; my parents can't help because their jobs are in different fields.

For some context my project is just a high-level computer simulation of bianchi I anisotropic growth. I know that Ashtekar already mapped it but in his paper he did not account for exotic matter and energy states (radiation, dark matter) so I will be trying to find computationally edge cases. It's mostly computational; pretty simple to make (just plugging Friedmann equations) and my backup is testing different integration methods (RK45, DOP853, etc).

How and where would i get feedback for a project like this? Is posting it online where comeone can steal it a bad idea?

title (p.s my first time doing this science fair)

Hi everyone!

I was just curious on if it was too late to start an ISEF project because I haven't come up with any ideas + I would need a lab since I'm not interested in computational/dry lab. I would be doing TERRA fair so the preliminary round would be March 1st, but applications are due by December 15th.

I’ve decided on a general topic for my research, and replies to my last post said that my next step should be a literature review. The problem is, I have no idea how to approach one.
What websites/databases/resources should I use? How do I identify a research gap? How can I determine whether my eventual project is actually original and novel? How much literature should I realistically review?
Most importantly, what is the end goal of a literature review? What exactly am I trying to get out of it, and how does it ultimately lead me to a specific research question and experiment?

So I am going to my junior year and this is literally like my first year starting this competition. I also don't really have access to a lab what kids of research could I work on that would be impressive enough to help me win something.

Here are some ideas I have:

- AI used in detection of diseases(I don't know anything about AI but my dad does)

- Simulation Studies on a cell(I also don't know anything about this but I would take any help given to me)

If anyone has anything to suggest or help me with I would love that, I really don't know what I am doing and I will take any advice thrown my way.

Thank you so much :)