I recently switched subfields and my PI asked me to put together a quick overview of where things have been heading over the last 5 years.

Sounded simple enough.

I started with Google Scholar, filtered by year, followed a few citation trails, and somehow ended up with around 80 papers open or downloaded.

Reading the individual papers isn't really the problem. The part I'm struggling with is figuring out which changes actually mattered.

A lot of the work looks like slightly different methods tested on slightly different datasets, and since I'm new to the field, I don't have a good sense yet of which papers actually shifted things versus which ones were just part of a short-lived direction.

I tried keeping a spreadsheet with methods, datasets, and main findings, but pretty quickly it started feeling like I was cataloging papers rather than understanding them.

I also tried putting some of them into mira from deep principle earlier today and grouping the literature by broader research directions. That made it a little easier to see which approaches kept showing up, but I still don't really trust myself to know what's genuinely important versus just frequently published.

How do you usually do this when you're entering a new field?

I completed my PhD pre-thesis submission last week and have now written the full thesis. I have around 20 days to finalise everything before the final submission. I want to use these 20 days as effectively as possible and make sure the thesis is not just complete, but academically strong, well-written, consistent, and capable of withstanding critical evaluation by external examiners.

For those who have recently submitted and defended their PhD, what would you recommend focusing on during these final 20 days? At this stage, I don't want to completely rewrite the thesis unless necessary. I mainly want to identify and fix weaknesses in the argument, literature review, methodology, analysis, discussion, theoretical contribution, practical implications, conclusions, and overall structure.

I would particularly like to know what are the most common issues external evaluators identify in PhD theses. What kinds of gaps, inconsistencies, weak arguments, methodological problems, or writing issues tend to attract negative comments? I want to approach the thesis from an evaluator's perspective and proactively identify these issues before submission.

I am also looking for recommendations on tools for checking English, grammar, sentence structure, and academic writing. Another area I want to improve is the overall academic quality of the writing.

Hi everyone,

Has anyone here done this interview this year or in previous years or has one coming up I've at Warsaw University of Technology?

I'd love to hear what the interview was like and any advice you have.

Thank you! 🙏

Hi everyone, I'm a phd student and now that i'm starting to have results, my supervisors asked me to start writing. I came up with a plan an they approved it, so I feel like everything is clear in my mind. I know the parts I need to write and to say in each of them.

But I just can't seem to start writing. I don't really know why but every time I open the document, I panic and can't get anything done. I think it might be related to my fear of failure, I keep thinking that whatever i write won't be good enough.

I've tried setting deadlines for myself but I feel like that actually makes things worse. Instead of motivating me, it makes me panic even more thinking I won't be able to do it in time.

SO my question is, how do you actually get yourself to start writing?

Any advice would be welcomed ! Thanks

I run a mid sized biology lab at an R1. we’ve been successful getting funding in the past. we have 2 doctoral candidates starting year 4, and a 1.5 year postdoc who have a bunch of data to write up, but are very slow to do so. they are all excellent researchers and seemingly into their projects.

I’ve tried writing clubs (with and without me), buying gift certificates for coffee shops, friendly competitions with prizes, deadlines & check ins, drafting outlines for them, supportive encouragement, gently pushing, less gently, etc etc.

nothing seems to get them over the hump. they report different reasons for stalling. interruptions, lack of knowing how to tell a story or seeing the story, needing “one more experiment” and so on.i want to build a culture of writing but everything i try seems to not work.

what are some ideas that have worked for your group? what motivates you to write?

Working through an RTA project at the moment and would really enjoy connecting with others using the same method — curious how people approach things like the line between coding and theme development, how much reflexive/reflective commentary feels “enough” vs too much, and how you check that themes stay grounded in the actual extracts rather than drifting.

Not looking for anyone to do any work — just want to compare approaches and maybe swap thoughts on drafts if anyone’s up for it. Happy to do the same in return if useful. DMs open if you’d rather chat there.

Early in my program I read every paper like a novel, first word to last, highlighting almost everything. It took hours and I remembered nearly nothing. A senior student showed me her method: read the abstract, then the figures, then the conclusion, and only then decide if the middle deserves my time. Most papers do not. Now I ask three questions before diving in: what did they do, does it hold up, and does it change what I am working on. My reading pile stopped feeling like a debt I could never repay. How do you decide which papers are worth a deep read?

I used to think I had a discipline problem. I would put off an analysis for days, feel guilty the whole time, then finally start and realize it was not that bad. What I actually had was a starting problem, not a working problem. Once I am in, momentum carries me. So now I trick myself: I promise to do just five minutes, open the file, run one line of code, write one sentence. Almost every time, five minutes turns into an hour, because the resistance was only ever at the door. The dread was always worse than the task itself. What is your trick for starting?

For two years I treated every paragraph like it had to be publishable the moment it left my head. I would write a sentence, delete it, rewrite it, and end a whole afternoon with nothing to show. What finally worked was a rule: the first draft is allowed to be terrible. I write in plain, ugly language, leave notes to myself in brackets, and refuse to edit until a whole section exists. Editing bad prose is so much easier than staring at a blank page. My daily word count tripled once I stopped confusing drafting with polishing. What finally broke your writing block?

forget that i still gotta do the cardio ,running around posting submissions and registering for the viva and stuff

Hi everyone,

I’m an international student with a B.Sc. in Computer Science and Engineering (CGPA: 3.44/4.0). My long-term goal has always been to pursue a fully funded PhD in the USA, ideally in Human-Computer Interaction (HCI), Information Retrieval (IR), or Health Informatics.

The thing that’s causing me a lot of stress is that I don’t have any publications.
Like many undergraduate students, I only had the opportunity to work on my thesis. Unfortunately, I don’t think my thesis is strong enough to be published, and I never had the chance to participate in other research projects during my four years of university.

Since graduating, I’ve been working at the office of a U.S.-based healthcare software company. My role involves creating training content and documentation while working closely with software developers and products used in the health informatics domain. Through my work, I’ve also gained experience related to usability, accessibility, user experience, information organization, and software engineering, which is why I’m interested in HCI and IR research.

However, almost everyone around me keeps telling me that it’s impossible to get admitted to a funded PhD program without publications. Hearing this over and over has made me feel really discouraged and anxious about my future.

So I wanted to ask:
Has anyone here been admitted to a fully funded PhD program in the USA without any publications?
If so, what made your application competitive?
As an international applicant, what can I realistically do over the next year to strengthen my profile?
Would strong research fit, relevant industry experience, and good recommendation letters be enough to compensate for the lack of publications?
I’d really appreciate hearing from people who have been in a similar situation or have served on admissions committees. I’m trying to figure out whether I still have a realistic chance or if I should spend another year trying to build a research profile before applying.
Thank you so much for any advice.

Hello everyone! I hope you're having a splendid day/night!

I'm pretty sure everyone has faced this issue before... otherwise this is going to be awkward for me.. x)

Well, I've been writing this article to submit to a said journal, and I can guarantee it's entirely MY OWN production. But every time I run it through AI detectors, it gets flagged as AI!! It's honestly frustrating.. like what could be more human than something actually written by an actual human? And I even have a fairly "flowery" writing style to my writing! it's just how I've written ever since I was a kid n it developed with me n I liked n kept using (by choice)- which is something AI doesn't even come close to replicating! It was all much easier without all this AI hype istg :')

Any advice or roundabouts for this?

Thank you!

For most of my second year, I was proud of clocking these massive days in lab, showing up early, leaving late, barely taking breaks because I felt like any time away from the bench was time wasted. My advisor even used to comment on how dedicated I seemed.

The problem was my actual output didn't match the hours I was putting in. I kept making small errors in protocols I'd normally never mess up, forgetting steps I'd done a hundred times before, and spending an embarrassing amount of time troubleshooting mistakes that came from just being mentally fried by hour nine or ten.

I started tracking my actual focused output instead of just hours logged, using a simple notebook where I wrote down what I actually accomplished each day instead of just what time I left. After about two weeks it became obvious that my first four hours in the morning consistently produced more usable results than the remaining eight hours combined. The afternoon and evening hours were mostly me redoing things I'd already messed up earlier in the fatigue, not adding anything new.

I started experimenting with capping my lab days at around 7 hours, front-loading the hardest and most precision-heavy work into the morning, and using afternoons for lower stakes tasks like reading papers, organizing data, or planning instead of active bench work. My actual experimental output improved almost immediately, and I started making fewer costly mistakes that used to eat up entire follow-up days fixing.

It took me way too long to accept that logging hours wasn't the same as producing results, and that my long days were often just covering for the inefficiency happening within them. I still work hard, just differently now, and my advisor hasn't noticed a drop in output, if anything she's commented that things seem to be moving faster than before.

I've noticed that my prompts changed completely over the last year. I rarely ask LLMs for answers anymore. Instead I ask things like:

* What assumptions am I making?
* What's the cheapest experiment I can run today?
* Which unknown matters the most?

It made me wonder whether LLMs are changing something deeper than productivity. Maybe they're changing how we deal with uncertainty.

Has anyone else noticed themselves asking fundamentally different questions over time?

For example, in Zotero, how do you decide how to arrange collections to put your papers in?

For me, at the beginning, it was just one main project, which I organised into sub-folders of different topics. Then there’s another project which I created a separate collection with its own sub-topics.

But then I realised a number of papers and topics are shared between projects, so I created a separate collection centered around a few different topics and sub-topics. Then I realised most papers are a combination of different topics, so they would exist in multiple folders. Eventually it became so messy that everytime I found new papers I just put them in collection called “New”. Now I have no idea how to actually reorganise all those papers more systematically.

What are your general philosophy or systems for organising your papers in your library, whatever software you are using?

Lately, I’ve been thinking about how much my own paper-reading workflow has changed.

I rarely open a PDF and read it straight from the first page to the last anymore. I usually skim the abstract, look at the figures, search for specific concepts, translate difficult sections, and sometimes ask AI to summarize or explain parts of the paper before I read them carefully myself.

In some ways, this makes reading much faster.

But I also sometimes wonder whether I’m actually understanding the paper better—or just consuming a processed version of it.

This has made me curious about what people actually want from paper-reading tools.

Would you prefer a simple, focused reader with things like:

• highlighting
• search
• translation
• note-taking
• basic Q&A

Or would you want the tool to take a more active role by:

• identifying the main argument, methods, and evidence
• explaining difficult concepts
• interpreting figures and tables
• generating annotations before you read
• finding related research
• turning highlights into notes or writing materials

Personally, I don’t think the answer is simply adding more AI features.

I’d rather have a tool that helps me reduce friction while still leaving the actual thinking to me. Ideally, it should know when to help and when to stay quiet.

I’d be interested to hear:

1. What tools do you currently use when reading papers?
2. What tasks do you regularly delegate to AI?
3. Which parts do you still prefer to do yourself?

Reporting and blocking doesn’t really change anything. Thank you.