The MANDA Lab Odyssey

 https://x.com/MakrandParanspe/status/2041313900533096692 Unfortunately, I have to agree with this take. I can speak from my experience as someone who does both experimental and computational work in cognitive science. If your work can be done on a normal computer using existing datasets, it is possible to publish steadily. But such work is less likely to be truly groundbreaking. Usually, datasets are shared after the original authors have already addressed the most immediate and critical questions that can be answered using them. This is why institutional support for experimental science matters so much. Setting up an ambitious experimental program takes time, space, infrastructure, administrative clarity, and patience. Early-career faculty who are trying to build something genuinely new often have to spend years bringing in grants, designing facilities, planning equipment, developing protocols, hiring and training people, and building analytical pipelines before the most exciting...

From Running Analyses to Doing Research: Lessons from My First Paper Anuska Maity Introduction When I entered IIIT Hyderabad, I knew that I wanted to pursue research. I believed that even small contributions could have lasting impact, but my understanding of what research involved was limited. I assumed it primarily meant reading prior work, proposing something novel, and validating ideas through analyses. This post reflects on how that understanding evolved during the process of working on my first research paper. In particular, I discuss how I learned that research is not only about running analyses or achieving statistically significant results, but about carefully testing assumptions, diagnosing failures, curating data responsibly, and using visualization as a tool for reasoning and debugging. I hope this reflection is useful for students who are just beginning their research journeys. Phase 1: Learning the Task Without Understanding the Process My initial months in the lab were la...

... but life gets better when we shift our attention to the positives in our life. This may sound   clichéd, but  the sheer number of people (including myself sometimes) who suffer due to focusing on "what could have been" is astounding. For most of us, if we could take a moment to think of all the very plausible ways in which life could have been much worse than it is right now, we would be much happier!  For me, so many things could have gone wrong, right from college when, in the initial two years, I was NOT doing well at academics. Soon, I had a mentor who agreed to guide me on physics research. I complained about his unavailability; there was even an entire year when he was gone and didn't respond to emails, but in hindsight, the fact that back in 2006-7, I even got to do research as a clueless undergrad in India was not something a lot of others had access to and I should have been thankful to that adviser whose courses actually taught me quite a bit about nonlinear...

I have made an observation in the last 4.5 years of working in Indian academia. Visionary leadership in academia is a scarce commodity. However, I have found some good examples of academic leadership in my limited experience and will talk about that.  One such experience was the IIT Mandi HCI Foundation/iHub call for proposals. I was shortlisted but when I got to IIT Mandi, the iHub leadership (their CEO, the institute director, etc.) said, "You all were shortlisted because you were the strongest on paper. We are not particularly interested in the specific ideas you wrote in your proposals but our aim was to get the best people together and connect you all so that you can come up with ambitious ideas that you wouldn't have been able to in isolation." And thus was born a consortium project with a startup and 3 other institutions (IIT Rourkee, IIIT Gwalior, and BITS Pilani Hyderabad) with a grand vision that was very different from each of our individual proposals. The DST ...

This year has been the most productive one for our lab so far, but of course, the groundwork for it was laid in the preceding 3 years. This semester, I had a high teaching load but also managed to make significant progress on my postdoc paper that still needs to be submitted. This is the first year, really, where we are able to share with the world some of the research we'd been working away on in the past few years. While we have published some decent conference papers already, we are beginning to submit some substantial journal papers (see the preprints below). I am confident that these will be published sometime next year. Note that most of this work was done with no funding other than institute support for students. Some of our folks are also applying to grad school, and I'm curious to see how their training and work here translate into PhD offers. After my talk at FAIL? '25 and the institute talk I gave about my work on traveling waves (in preparation for my Wave Club...

I was genuinely surprised recently when someone told me they didn’t believe there was a real distinction between fundamental and applied work. They asked, “What do you mean by fundamental? You keep implying that some of us don’t do it.” I tried to explain that “fundamental” does not mean “superior,” and that my point wasn’t a criticism but simply a statement about the type of science we were discussing. I wasn’t successful in convincing them, so I’m writing this post in the hope that it will clarify the distinction for students and for anyone else who may share that misconception. The distinction between fundamental/basic and applied science has a long history. While I'm sure we can find some references to such distinctions in ancient philosophy, most people trace the distinction back to Vannevar Bush, who made the distinction when coming up with policy advice for the US president. This article , for example, describes that distinction and identifies an issue with how " basic...