The good, the bad, and the ugly: A reflection on Indian academia at the five year mark
On June 30, 2026, I will complete 5 years as faculty in Indian academia. Here are some quick reflections.
The good (great)
The students. With its population, India is blessed with plenty of talent. Finding the right people to nurture and to see them develop into well-rounded scientists ready for the next step is a privilege that words cannot truly express. Now, the students we train are quite unlike the students who end up in the best universities in the US or elsewhere. These are people who haven't had that kind of exposure. For example, people who get admitted to PhD programs in the US typically already have significant research experience with a few publications to their name. So it is especially fulfilling when our students get into top PhD programs or do well otherwise after a stint in the lab. Our PhD scholars tend to start from scratch, and that also requires significant early investment of time for training the basics. Most of them are ambitious and passionate about what they do, so they pick things up quickly.
Teaching. Even though attendance is low around the globe (I'll put that in the bad category), the few who attend are super smart and engaged in my classes, and I really do enjoy teaching.
Highly accomplished faculty colleagues. I have been lucky to forge collaborations with people who are academics in the truest sense of the word: they are intellectually curious, open to learning from working with a cognitive scientist (and teaching me what they know!), and maintain the highest levels of professionalism. For example, one of my closest collaborators at IIITH and I have an unspoken rule that we will be joining project meetings on time (+- 2 min). When we can't, which is rare, we let each other know in advance. I like people who respect my time. Over these five years, I have also made friends from the broader cog sci community in India. Being a small community compared to other fields, it is important that we support each other, and I have experienced nothing but positivity from this community so far.
Lack of departmental boundaries at IIITH. I am not restricted from teaching courses that cross over to other disciplines, and I can collaborate with whoever I want and co-guide pretty much any student in the institute. These are luxuries that are not readily available in other institutions as far as I understand.
Some staff members. There are truly exceptional people who really do the job of 2-3 people. These departments tend to be understaffed, and so there are people who go beyond the call of duty and help faculty do their jobs.
The bad
Some people. People who refuse to give others credit for the work they've done. People who do not show up on time for meetings. Folks (especially those who are prone to complaining about every little thing) who don't believe in saying "thank you" to the people who helped them succeed. Just basic lack of professionalism and respect. However, none of these are "ugly" because we have agency over who we work with, and once you see a red flag, take early action. Do not fall into the sunk-cost fallacy. I have made that mistake myself early on but fixed hiring practices in the lab and how I decide who to collaborate with, and life is a lot easier now. Of course, some of this also boils down to fit. Even if both faculty and students have the best intentions, sometimes their styles of working and expectations do not match, and that can lead to friction. Friction is inherently not bad. Both parties can learn from it if they take steps to overcome it. It is only bad when one or both parties refuse to try.
Prior cogsci training. Even those who come in with master's degrees in cognitive science tend to miss many basic skills, and that is an indictment of master's programs in the country and says nothing about the students (please see what I said about these students under The good). I mean no offense to anyone who may be contributing to such programs, but we have a lot of work to do to upgrade our cognitive science programs to include not just courses on verbal theories in the different domains of cognition but also to focus on developing rigor in designing experiments, statistical analysis, some mathematical modeling of phenomena where applicable, etc., ideally through the thesis work. As of now, I see low-quality theses from many places when people apply to work in the lab. The reason for this is quite often that faculty are overloaded. These programs exist to make money for institutes and for faculty to justify their existence in those institutes. This business aspect sometimes affects the quality of the programs because we try to expend as little energy as possible when designing programs. So courses we already teach may be repurposed and applied to these programs. However, this is the wrong approach. The right way to go about this is to hire more qualified faculty and design the curriculum with input from both national and international experts, with attention to the job and academic prospects of the students after the program. No one cares if you know a bunch of facts like Miller's magic number. People care if you can read journal articles with a real critical eye, develop experiments with tight controls, develop custom code for careful data analysis, apply appropriate statistical procedures (and if using AI, have enough expertise with coding to be able to test the code for accuracy), etc. Folks with some combination of these skills are the ones I would be looking to hire as PhD scholars in the lab.
The ugly
Some people. Now this group of people, you cannot ignore. They are administrators and other folks who are supposed to do their job to support the activities of research labs in institutions. These people can be grant administrators; they can be institute-level administrators. The folks I'm talking about here do not respond to important work emails. The end result is that despite the heavy load that an early career faculty member is under, they have to follow up every other week to get basic things done. When emails do not work, we have to go wait outside offices to talk to these important people. So faculty end up having to do many more jobs that they are paid to do. It costs us months of productivity per year just chasing after people to do their jobs.
Inequity. Rules exist for some people, not for others. I cannot say more on a public forum, unfortunately. This issue is serious enough that it leads to faculty attrition in many institutions.
Ethical issues. Now you might think I'm going to talk about students here. No. While students do cheat, misuse AI, etc., they are only following the cue from more senior folks. Again, I cannot say much on a public forum (see the point about COI for a clue).
Lab space and other institutional support. Even when you bring in funds, it is a major fight to get space for setting up experimental infrastructure. I hear that this is a common issue across institutions in India except for a few places. Indian scientists are capable of producing good science. They do so despite the lack of support and not because of it. Imagine how much more can be accomplished if institutions impose a high bar when hiring but then fully support the faculty they do hire!
Research funding agencies. ANRF is taking some steps to improve. Not sure about the others. As of now, funding is available primarily to those who can make promises of commercializable research products within 2-3 years of working on a problem. A smaller pool of money is available for more ambitious long-term research problems, but there is an incredible amount of competition for it, and various factors other than the quality of the research proposal influence the outcome there as well (e.g., prestige of the institute for that particular domain, prior track record, etc.). So it is hard to get your first grant, but once you execute one or two well, I believe it gets a bit easier.
COI. Conflict of interest is the name of the game in Indian science. Without naming names, I was recently at a meeting with a colleague where an arrangement was made right before me about an upcoming grant opportunity. An "important person" stated that he would be on the panel and that if this faculty included some key words, he would connect them with some research partners, and the grant would go through. Yes, meritorious people still do get grants, but this is after these sorts of cuts. I have also seen senior faculty from another institute talk to someone in front of me about how one of them is on an evaluation committee of the other's grant and what must be done to get it over the line (and promises were made). Some of my more senior and successful colleagues protest when I share this and say that it is all merit-based, but I would ask them to read about survivorship bias. Anytime a junior colleague brings up such issues, a few of the successful senior ones assume that we are being lazy by complaining, instead of writing more grants.
Comments
Post a Comment