A step-by-step guide with a real case study for busy industry professionals to write quality AI papers without burnout.
If you’re reading this, chances are you’re an AI professional juggling a demanding full-time job and wondering how to get your research out there without losing your mind.
Publishing a paper at a top AI conference might seem like a daunting, time-consuming task reserved for academics with endless hours to spare. But it does not have to be that way.
Instead of just some advice and theoretical framework, I will explain with an example of a medical AI paper (as it is my research area), particularly medical text summarization, so that at the end, you will have a brand new research idea for a paper with you.
A real-life case study on perspective-aware summarization. I will also share my thought process and reasoning at each step, so that you can easily use it for your own use case.
I am currently pursuing a postdoc at Stanford Medicine. To learn more about my research portfolio, please visit https://roysoumya.github.io/
Table of Contents
· Motivation
· Step 1: Shared Tasks — Your Fast Track to Publication
∘ Healthcare AI Opportunities
∘ Multi-modal Challenges
∘ Competition-Based Publications
· Practical Example for Step 1
∘ What is the PerAnsSumm: Perspective-aware Healthcare answer summarization task?
∘ Why did we choose this task?
· Step 2: Target National Conferences
· Your 6-Month Action Plan
· What Employers Actually Want to See
· Common Pitfalls to Avoid
· The Bigger Picture
· Final Words
Motivation
Whether you’re working on a new model, experimenting with data, or applying AI in innovative ways at your job, publishing your work can open doors, boost your career, and connect you with the research community.
The Reality Check: Getting a top-tier paper takes 1–2 years. But you do not need to publish in the top-tier Nature journal at the start of your publishing journey — you need credibility by publishing a good conference paper and getting your foot into the door.
I have a few papers in international AI and NLP conferences (check my research portfolio for more details), or go through my talk on this topic.
My research talk for my IJCAI 2024 paper www.ijcai.org/proceedings/2024/683
Step 1: Shared Tasks — Your Fast Track to Publication
Shared tasks provide everything except the solution: datasets, evaluation metrics, and clear problem statements. You focus purely on methodology.
Healthcare AI Opportunities
- What it is: Test if AI models give accurate medical information
- Why it’s strategic: Huge industry need for reliable healthcare AI
- Your advantage: Engineering background in system reliability testing
- What it is: Answer patient questions using medical records
- Industry relevance: Direct application in healthcare tech startups
- Skills gained: Natural language processing + domain knowledge
Multi-modal Challenge
BioLaySumm 2025 (Radiology + Text)
- The opportunity: Translate complex medical reports into patient-friendly language
- Why it matters: 200+ teams participated in 2024 — this is hot
- Career boost: Multi-modal AI skills are highly valued
Competition-Based Publications
To increase visibility and engagement with the research community, many top-tier AI conferences like KDD, SIGIR, and WSDM also organize data science competitions in the fields of Retrieval-Augmented Generation, Recommender Systems; these problems typically are primarily from industry partners and sometimes from research institutes.
KDD Cup (https://kdd2024.kdd.org): The Olympics of data science
- Direct industry connections
- Real-world problems
- High visibility among tech recruiters
SIGIR LiveRAG Challenge (https://liverag.tii.ae/): Real-time information systems
- Applicable to search engines, chatbots, and customer service
- Growing market demand
Practical Example for Step 1
We will select the PerAnsSumm Shared Task of the CL4Health Workshop, colocated with the 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL 2025).
NAACL is a top-tier (Core A) conference in the Natural Language Processing domain held in New Mexico from April 29 to May 4, 2025 (so extremely recent).
What is the PerAnsSumm: Perspective-aware Healthcare answer summarization task?
Quoting the details from their website (https://peranssumm.github.io/docs/)
Given a question Q, a set of answers A, and perspective categories (‘cause’, ‘suggestion’, ‘experience’, ‘question’, and ‘information’), you are assigned the following two tasks:
Task A: Identify the spans in the user answers that reflect a particular perspective and classify the span to the correct perspective.
Task B: Generate a concise summary that represents the underlying perspective contained within the spans across all answers.
Why did we choose this task?
This is a vast topic in itself on which I can talk for hours. But simply put,
- A very recent dataset from a reputable conference. This, in turn, means that there is less chance of poor data quality issues. Being recent, the motivation and problem relevance are already established, making it easier to defend from a reviewer.
- Although summarization space is very saturated, perspective-aware summarization is brand-new as far as I know. This type of insight is hardest to learn on your own, so you may ask senior team members to help you out.
- Shared tasks almost always publish an overview paper where they compare the performance of the different teams on both the public and private test datasets. In our case, please refer to Tables 2 and 3 of the PerAnsSumm overview paper. This means that if you get access to the evaluation data they used, you can directly report the same values in your paper.
- From the overview paper, you already have an idea of which teams perform the best. In our example, Section 6 of the overview explains the models and systems used by the top-performing teams.
- More good news. The top-performing teams themselves write individual papers describing their models in more detail. These articles form our baseline models for our research paper. In our case, a simple Google Scholar search gave the following result
Through this exercise, we achieved the following:
- Clear and relevant motivation of the paper — that will help us write the Abstract and Introduction section
- Methodologies used by top-performing teams, what works and does not work — help us write the Methodology section
- Performance comparison tables and evaluation setup of PerAnsSumm task — help us write the Evaluation Setup and Experimental Results section
In essence, we together collected all the components of a research paper.
I am confident that using this framework, you can successfully replicate it for a problem in your research area.
Step 2: Target National Conferences
If you are working in India, COMSNETS and CODS-COMAD offer solid reputations with realistic acceptance rates for newcomers.
Why This Works:
- Faster review cycles (3–4 months vs 12+ for journals)
- More open to interdisciplinary approaches
- Strong networking with the Indian tech industry
- Reviewers understand career transition contexts
Your 6-Month Action Plan
Months 1 and 2: Choose 2–3 shared tasks aligned with your strengths.
Months 3 to 5: Develop solutions, iterate based on leaderboard feedback
Month 6: Submit papers to target conferences
What Employers Actually Want to See
Not just any publication, but evidence of:
- Problem-solving transfer: How you applied engineering thinking to data problems
- Domain commitment: You’re not just checking boxes
- Technical depth: Beyond basic machine learning tutorials
Common Pitfalls to Avoid
❌ Don’t: Try to become a computer scientist overnight ✅ Do: Leverage your engineering intuition as a differentiator
❌ Don’t: Target only top-tier venues initially ✅ Do: Build momentum with achievable wins
❌ Don’t: Work in isolation ✅ Do: Engage with shared task communities early
The Bigger Picture
Your first publication is a stepping stone, not the destination. It demonstrates:
- You can contribute to data science research
- You understand the field’s challenges and methods
- You’re committed to the transition
If you like this fast-track journey for a research publication, then I invite you to pursue a long-term journey by targeting a top-tier, international conference.
My following articles provide a clear framework for AI and NLP conferences.
Final Words
Remember, your full-time job is not a liability — it’s your secret weapon. The key is finding problems where this background creates genuine value.
Six months from now, you could have a conference paper submission and be networking at data science events. The pathway exists; you just need to choose your first step strategically.
If you want me to cover some other topics, please do let me know in the comments or email me.
Thank you for taking the time to go through this article. I wish you all the very best in your research journey.
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