Join Us
There is no single right way to contribute to this work. Whether you have two hours a month or fifteen hours a week, whether you bring domain expertise or the ability to think across domains — there is likely a fit here. Read what each role actually involves before deciding.
Systems Researcher / Research Assistant
Systems researchers work on synthesising across domains, finding the contradictions that matter, and red-teaming logic until it holds or breaks cleanly. The work is forensic, cross-disciplinary, and documentation-heavy. You won't be spoon-fed tasks; you will be given a problem space and trusted to navigate it.
Researchers who join formalise their work into a report or preprint and publish it on Zenodo under the lab, as first author. The research record is yours — the lab is the context that makes it possible.
The Lab: High Agency, High Freedom
- High Freedom. No red tape. No exclusivity — your original thoughts stay yours. If you find a rabbit hole worth following, follow it. We don't do mind games or secret tests. Take us literally.
- High Agency. We don't expect full-time commitment, but we expect 100% on the tasks you say yes to. Work async, be independent, and look things up before reaching out.
- The human truth. Self-care matters more than anything we produce. Say no if you are low on energy. We respect a no more than a half-hearted yes.
We are not assessing whether you are good enough. We are checking whether this environment energises you and aligns with how you think and work. You shine either way.
The number one thing you can do as a researcher is know that your ideas are not you. Your papers and your outputs are separate entities. Neither glamorous citations nor failed experiments define who you are. A bad idea does not make you bad. This keeps you honest, curious, and unafraid of being wrong.
If this sounds like a nightmare, it's not about you — there will always be tasks where you feel energised. If this sounds interesting, research may work for you.
The Dead Link Hunt. Finding a specific government regulation mentioned in a 2014 news article, only to find the original PDF is gone — then digging through the Wayback Machine to recover the actual text.
The Definition Duel. Comparing how two different agencies define the same word — like "Health Supplement" — and writing a one-page memo on why that three-word difference is causing a trade bottleneck.
The Reference Rabbit Hole. Checking a citation's citation until you find the original "fact" was a typo from 1998 that everyone kept copying.
The Data Cleaning Purgatory. Manually verifying 200 entries because a script can't tell "MTR Spices" from "M.T.R. Spice Ltd."
The Single-Paper Pivot. Designing a system architecture for three days, then finding a paper published last month that proves your approach has a fatal flaw — and figuring out how to use that flaw as a new feature.
The Edge Case Stress Test. Trying to break a solution by coming up with ten weird scenarios that current law doesn't cover.
The Technical Translation. Explaining a complex systems constraint using only a pressure-cooker analogy so a policy-maker can understand why it matters.
The Manual Scrape. When a website blocks your scraper and you spend an afternoon copy-pasting data from fifty pages while questioning every life choice.
The Prompt Engineering Loop. Spending four hours trying to get an AI to extract a table from a grainy 1992 PDF, only to realise it's faster to just type it out yourself.
The Formatting Marathon. Three hours in LaTeX trying to get a table to fit on one page — because if the reviewer can't read it, the logic doesn't exist.
Attempt one of the three problems below. There is no trick. No hidden correct answer. We are not testing whether you are right — we are seeing how you think when the answer isn't obvious.
Find a subdomain whose classification logic contradicts or creates constraints with that of another system. Analyse the point of clash: is it a design error, or was it the only viable option at the time? If it was the only option then, is there another option today? On what basis is that option designed? Justify your choices with at least three valid sources. If a novel aspect isn't directly citable, decompose it to first principles and cite sources that support that foundation, even indirectly. Analyse where the system fails reality, and why.
Choose one foundational document from each of three different domains. Analyse the accessibility of each — both in wording and the tools required to use it. Who is it accessible to, and who is it not? Does it serve its intended target? If not, why — and what constraints was it made under? If it were made digital today, how would you present the same information, and why? Back it up with sources.
Choose three of the lab's published papers from three different domains. Break each apart in every way you can. For each break point: was it an intentional limitation or a genuine fault line? Say how you would want it rewritten, and why. Support your argument with at least three valid sources per paper.
Send your response to lalithaar.research@gmail.com with the subject line [RESEARCHER APPLICATION — Problem 0X]. Include a brief note on what drew you to the problem you chose and what you are currently working on or thinking about.
Salutations to the Goddess who dwells in all beings in the form of intelligence. I bow to her again and again.
Subject Matter Expert
SMEs are consulted when a specific question in their domain arises. We reach out, you engage at your convenience. The ask is never for validation or reassurance — we are looking for someone who will break the logic until only the unbreakable part remains. If you contribute substantively to a research output, you are credited as a co-author.
We are currently seeking experts in the following domains for the Indian Food Informatics Data project:
- Nutrition ScienceTo review the accuracy of our taxonomical groupings against nutritional and biochemical definitions.
- Corporate & Regulatory LawTo situate the framework within FSSAI compliance, balancing consumer safety with brand-side business constraints.
- Linguistics & NLPTo validate the mapping of regional name variants to standardised identifiers — particularly where transliteration is ambiguous.
- AI Ethics & GovernanceTo review the framework for algorithmic fairness and data integrity. Specifically: ensuring the taxonomy does not systematically favour certain industrial nomenclatures over regional ones, and that variant-to-standard mappings are explainable and transparent.
- Business Administration & CSRTo help us understand how the framework interacts with corporate objectives — where it creates operational ease, and where it creates friction worth anticipating.
If you work in one of these areas and are open to being reached out to, register your interest at lalithaar.research@gmail.com with the subject line [SME — DOMAIN]. No commitment required at this stage.
Industry Data Partner
The Indian Food Informatics Data project requires real-world ingredient and label data at scale. If you are in the food and beverage industry and are willing to contribute anonymised or open-licensed data, you are directly shaping infrastructure that will serve your sector — as well as regulators, researchers, and consumers.
Data contribution is acknowledged in the dataset. There is no financial arrangement and no influence over how the data is used or what the framework concludes. The data becomes a public asset under CC BY 4.0.
To discuss a data partnership, write to lalithaar.research@gmail.com with the subject line [DATA PARTNER].
Monetary Support
The lab is currently unfunded. If you believe in the work, the funding page explains what contributions go toward and how you can support it — whether as a general lab supporter or by sponsoring a specific researcher or workstream.