Showing posts with label PhD studies. Show all posts
Showing posts with label PhD studies. Show all posts

Saturday, June 13, 2026

Am I Running a Ponzi Scheme? On Visions, Promises, and the Responsibility of a Supervisor

 Paul Krugman published a piece this week calling Elon Musk a "human Ponzi scheme." The argument is sharp: Musk sustains the valuation of today's ventures by selling belief in tomorrow's promises — Hyperloops, Mars colonies, fully autonomous taxis — always just a few years away, recycled indefinitely. The scheme works not because anything is delivered, but because new promises replenish the credibility consumed by the old ones. It is, Krugman argues, structurally fraudulent.

I read it, and an uncomfortable question formed. I had just uploaded a post on Petri-net-based implementations of hydrological systems — a vision that is, let me be honest, far from realized. I have done this before: kinetic theories of unsaturated flow, new theories about stomatal resistance, new variational frameworks still being written up. Big ideas, posted with enthusiasm, with real students working in the lab. Am I doing the same thing? Am I a human Ponzi scheme in miniature, dressed in academic clothing?

I want to think through this carefully — not to exonerate myself cheaply, but because the question matters to the people who work with me.


What makes a Ponzi scheme a Ponzi scheme

The defining feature is not the gap between vision and reality. That gap exists in all serious science. The defining feature is the concealment of that gap, combined with the use of new promises to discharge the accountability created by old ones. Musk's Mars colony of 2025 was never reexamined; it simply became Mars 2030, and no one was asked to reckon with the intervening silence.

There is also an asymmetry of information that is deliberate. Musk knows his timelines are fantasy. His investors — retail and institutional alike — are not in the same epistemic position. That asymmetry is where the fraud lives.

Science works differently, at least in principle. When I post about Petri nets as a future architecture for hydrological modeling, I am not claiming the code exists. The blog is not a prospectus. Specialists who read it know immediately where the idea sits on the spectrum from speculation to implementation. The gap is not hidden; it is the point.

So no, I am not running a Ponzi scheme in the Krugman sense. But that is not quite a clean acquittal.



The real risk: exploration as a tax on completion

The honest concern is subtler. A lab led by someone who genuinely loves imagining new frameworks can develop a culture in which exploration is always more exciting than consolidation. A new formalism on Monday, a new variational principle by Thursday, a blog post by Friday. The momentum feels like productivity. It may be, for the professor. For a PhD student two years into a thesis, it can feel like the ground is perpetually shifting.

The danger is not that the visions are false. It is that students absorb — implicitly, without anyone saying it — that finishing is less prestigious than imagining. That the real work of the lab happens at the frontier of speculation, and that the careful, slow, unglamorous work of implementation and validation is somehow secondary. This is a subtle tax on completion rates, and it falls hardest on the students who are temperamentally builders rather than theorists, which is most students.

I have to be honest with myself: I do not know with certainty that I have always avoided this. The Petri net post, the kinetic theory papers, the O-EPN trilogy (which is actually still undisclosed)— these are genuine intellectual commitments. But I cannot assume their excitement is equally distributed across the lab. For some of my students, each new horizon I announce may be one more reason to feel that where they are is not where the interesting things are happening.


What the antidote looks like

The solution is not to stop imagining. That would impoverish the science and, frankly, it is not something I am constitutionally capable of. The solution is to maintain two registers, strictly separated.

The first register is the frontier: blog posts, preprints, EGU talks, kinetic theories, Petri nets, variational frameworks. This is where I think out loud, and it should remain open and speculative and sometimes wrong.

The second register is the accountability register: what each student is finishing, by when, with what criteria for success. This register has to exist independently of where the frontier is pointing. If the Petri net vision shifts the direction of the lab in five years, fine. But Giulia's (an invented name) thesis on snow redistribution is due in eighteen months, and its completion conditions cannot migrate because I posted something exciting on a Tuesday.

The two registers must not contaminate each other. The blog can run ahead; the supervision contract cannot.

This also means I owe my students something explicit: a clear statement, periodically renewed, of what they are responsible for completing, in terms that do not depend on the broader vision landing. Not "your chapter on the kinetic theory will matter when the whole framework is published," but "your chapter is complete when it answers these three questions, and it will stand on its own regardless of what happens to the rest."


The asymmetry I have not yet named

There is a further complication I owe my students, and it sharpens the concern rather than resolving it.

What appears on this blog — the Petri net post, the kinetic theory papers — is not the full picture of what I am working on. There are deeper theoretical threads, more fundamental unifications, that I have deliberately kept undisclosed while they mature. Over the coming months I will begin to publish them. When I do, some of what my students have been building will suddenly acquire a context they could not have seen from inside it.

I want to be clear about why I work this way: ideas need to consolidate before they are exposed to the world. Posting a half-formed framework does more harm than good, both to the science and to the students who might try to build on it. The sequencing is intentional.

But I cannot pretend this creates no cost. When a student cannot see the architecture their work belongs to, they can feel they are assembling pieces of a puzzle whose picture has not been shown to them. That is not dishonesty — the picture is real, and it will be shown — but it is an asymmetry of information between supervisor and student that I have a responsibility to manage carefully. A Ponzi scheme exploits information asymmetry for extraction. A research program that is being disclosed in sequence is something different, but the asymmetry still creates a burden, and it falls on them, not on me.

What I owe, therefore, is not premature disclosure but enough of the map that each student can locate their work within it. Not the full territory — that is still being charted — but a reliable answer to the question: where does what I am doing sit, and why does it matter, even if I cannot yet see everything it connects to?


A note to my students, directly

If you are reading this and you work with me: the visions I post are real commitments, not performances. I believe the Petri net architecture will eventually be the right way to implement GEOframe components. I believe the kinetic theory will reshape how we think about unsaturated flow. And there are further things I am working toward that I have not yet posted, which will give additional context to work some of you are already doing. You will see them as they become ready.

But none of this means your work depends on my broader bets paying off. Each thesis, each paper, stands on its own — and if it does not, that is a failure of supervision, not a feature of ambitious science.

If you have ever felt that the horizon kept moving before you could reach it, or that you were building without knowing what you were building toward: tell me! That conversation is overdue, and it is one I should be initiating, not waiting for you to start.

The difference between a Ponzi scheme and a research program is that the research program is answerable to reality — and so is its supervisor.


Thursday, July 4, 2024

A Ph.D. position on snow modelling and the related runoff production

 APPLY TODAY ! There is an opening until July 10 (<---Here it is the link) for a Ph.D. position on the SpaceItUP and SUPER projects (Snow and glacier rUnoff Production in alpine RivER basins 1990-2050)


Due to climate change, the Alpine region is experiencing a reduction in snow quantity (snow droughts) and an increase in evapotranspiration losses (green water), with significant consequences for sustainable water resource management and ecosystem preservation. This project aims to develop new models to quantify snowmelt and evapotranspiration losses, providing practitioners with calculation tools that are different from traditional lumped parameter models but simpler than 3D process-based models. The project also intends to study the water content obtained from snow and glaciers, from the present to 2050, in the Po and Adige river basins, assessing both quantitative and temporal variations in contributions. The primary tools for the analyses will be the open-source models of the GEOframe system, integrated, modified, and improved by the new models. The modeling will be supported by the acquisition of Earth observation products derived from the MODIS and Sentinel platforms, and potentially other platforms as data becomes available. The final product of the research, concerning snow forecasts, will be developed on a regular grid of 250 meters, while flow rates will be produced for each section of interest. The analyses for the control period from 1990 to 2022 will be conducted on both daily and hourly scales, providing a valuable "reference data cube." Future projections will be produced on a monthly scale. As part of enhancing the current state of the art, which is typical for a doctoral project, reliability criteria and error estimation methods will be developed for each produced dataset. The work will be done in collaboration with dr. John Mohd Wani as co-advisor. Collaborations can include working and exchanging ideas with dr. Christian Massari (GS), Professor Manuela Girotto (GS), Prof. Stefan Gruber (GS), Giacomo Bertoldi (GS), Kelly Gleason (GS), Marco Borga (GS) and Stefano Ferraris (GS).
Old work on snow and permafrost of the group can be found here (to be updated soon).
 The deadline is approachinf very fast, therefore APPLY! To better understand the policies of the group, please give a reading here 

Sunday, January 1, 2023

Hydrological CVs and Research

 It happens to me, but I suppose the same happens to most of my colleagues to receive many CV, especially from excellent guys developing countries. Some of them are remarkable but they usually do not  meet my requirements. What is the problem ? They are clearly very motivated and smart persons. However there is a constant in their backgrounds. They were trained in using models like HEC-RAS-HMS or SWAT or even MODFLOW and they wrote papers about case studies (regional studies they call them now).  This is not bad at all obviously and that “standard knowledge” should be part of any robust professional. There are other two variations the CVs: the use of machine learning techniques (under standard frameworks) to infer something or the use of Earth observation "products" to extract something of information (often without ground check). Sometimes their work is valuable and again, how can we say that they should not be part of the professional CV ?

However all of this has just a little to do with the research gold medal which stand in investigating processes, learning from them, disentangling their feedbacks, implementing new tools. Their trying to do something new remains within the very limited scope which is allowed by something built by others and not open to modifications and evolutions.  That's what I would like to see instead: these solid bases but also a little spark that try to go out for this standard comfort zone. 

For my critics, it is true that I push my activities  to the extreme, to the point that all discusses, not only processes, but also tools, the way to build them, the way to share them with others. It is true that, it can be seen as an act of high presumption, which prepares, for normal people like me, to a destiny of failures, low productivity and frustration, far away out of the highways of the industrial success of some paradigms.  Then if you do not have to imitate me to the limit, at least take the good of my perspective and do not stay still in a cycle which all renews for nothing change.

Sunday, August 7, 2022

Nobody applied to this call ! Reactions by Solomon Vimal ( How to Mobilize Top Tech Talent Towards Hydrology)

In a blog post, followed by a list-serv email, Prof. Rigon exclaimed,  “Digital Hydrologists from around the world unite! Nobody applied for this call”! His project focuses on building digital earth twins for the hydrologic cycle using advanced cyber infrastructure and software architecture solutions that are unusual in the field of hydrology in most hydrology groups around the world. He added, “Klemeš, V. (1986) reflected on dilettantism in Hydrology [... we cannot] manage complex interactions and feedback with poorly based informatics”. Prof. Rigon’s outcry indeed makes one think: “Ehi, out there, is anybody interested? Anybody interested in a PhD in this topic?”

It prompted me (Salomon Vimal, see below note by rr) to think -- what can be done to attract top informatics talent into hydrology?


Asterisks marks rr notes that you can find at the bottom.


Hydrology is a tiny field. We are a small sub-field of civil engineering. Among say 100 students who leave high school, conservatively, perhaps 1 in every 3-5 (maybe more!) years of graduation will reach the field of hydrology if lucky, and often by chance. This is an estimate on the basis that nobody in my circles from high school even knows what hydrology is. A subset of them may sign up to list-servs. A small subset (say 1/10) of professors would forward it to interested students in relevant MS programs. The incentives of a PhD salary in Italy, especially $ *, is relatively small compared to what most people with above average skills in tech industry get, so this filters a good portion of them out. Taken together with the fact that 95% of good software tech is developed by only a tiny fraction of the top percentile of the coders (more on this below), it is important to look for the tech talent with a different strategy to attract the cream-dela-creme. These call for a closer look at the tech talent pool and incentives to have them move to the small field **.


Let’s look at Stack Overflow’s (SO) skilled pool of talent. Let's assume SO is a good representative slice of the world's tech talent (which it indeed is). Some observations based on data on distribution of tech talent that can be drawn from Stack Overflow data queries at data.stackexchange.com. It may be helpful to look at how many people, with what skill level, contribution, and reputation are out there. There are 18M total SO users (see the query here). 95% of all activity is by 1M people with a 80 reputation. 80% of all activity is by 0.3M people with 850 reputation. 70% of all activity is by 100K people with 2K reputation. 50% of all activity is by 37K users with 7K reputation. The query example here can be modified to examine percentiles. But the point made here is simple. Most of the work comes from a very small fraction of programmers. For reference, I asked as well as answered 17 questions (a balanced karma) and only a few of my questions were actually appreciated and this puts my reputation score at ~880 (Aug, 2022) which accrued over 5 years or so, and I fall into the bucket of the top 0.3M users, i.e. top 1.6 percentile (by score) reputed users who make 80% of all contributions. My score is nothing compared to the top 50-100K users. While I generally feel comfortable to say that I am good with programming (with over 10 years of experience in Python), I certainly would not apply for the informatics job above, as I do not think I have sufficient skills to start contributing to the informatics/architectural aspect of the project without proper training in CS/IT. I would perhaps defer this position to someone with a score of >2-5K in SO or a degree in CS/IT. Using the query engine and the SQL language offered in Stack Data, one may try to find good metrics like rising stars on SO using one of the many threads on such metrics and pick the good ones to hire from such lists and write to them individually rather than wait for them to find the PhD job post***.


We may consider joint-specializations in PhD: In my previous company (RMS.com), flood models were built using GPU computing. Most of the hydrologists were unable to program with the GPU, but it was indeed developed in academia in a PhD work by someone at Penn State who had a PhD major in hydrology and minor in informatics — computational science, if I remember correctly. Most PhD programs do not offer such minor course work based specialization. Maybe universities can team up with the CS departments and offer a joint PhD in CS - this could be a solution to be attractive to a broader audience. I have no idea about the ground realities of bureaucracy that may impede such a solution, but I recall a double PhD in river science was offered at U. of Trento some years ago. ****


Let’s not forget the blackhole which attracts and retains top talent: Google alone has ~27K engineers (here, estimated for 2022) a good majority of whom are on SO, like the top user. The bulk of the good ones who do 50% of all activities are perhaps already taken by such Big Tech companies so PhD programs are not left with any good ones who have high reputation in SO. I know that Big Tech companies do have a similar approach to identifying top tech talent. If one prefers to do hiring in the more traditional way, one may write to CS department heads in some select universities in global cities that are in countries that would typically consider a move to Italy for PhD.


Consider the places where the bulk of tech talent comes from: The bulk of the top CS talent is arguably in US/China - clearly leaders in tech companies, products and talent - most of them perhaps won't move to Italy for PhD. This basically rules out many top university graduates. We are then left with some of the good institutes in other countries well-known for their contribution to global tech talent. India, for example, has a very strong IT workforce. But, it is better to focus on cities rather than countries in the case of CS expertise. In my experience cities that are Silicon Valley Like (SVL) in various countries might be good places to look. If I were to hire tech talent, I would simply look in the developing SVLs such as Tel Aviv, Bangalore and the NCR Region of India -- which certainly have a very strong talent pool in CS, perhaps not comparable to Bay Area or Shenzhen. I do not know the equivalent SVs of other countries but numerous articles like this one exist which enlist them. 


Finally, salaries: Horton wrote about a related issue in hydrologic research (Horton, 1937): "Men of highest degree of knowledge and experience in hydrologic matters are not likely to be employed by government salaries". The cream-dela-creme of the SVLs worldover will get salaries that will be well beyond the incentives of the PhD. In such a scenario, it may be sensible to adopt a different hiring approach and reach out to CS departments of universities strategically and identify candidates who have a demonstrable great level of skill in informatics which we are interested in and fully incentivize them to move to hydrology. For example CS graduates with say 3-5 years of experience from such SVLs may be interested in moving to Italy for the international experience and the good (alternate) life experience, even if the salary cannot per se incentivize a move. *****


It is indeed important for the field of hydrology to thrive with good software personnel who are also sought in all fields of science and all other domains of human pursuit. I hope we all agree this is a core problem with hiring good IT talent. Hydrologists need to hire top IT talent comparable with Big Tech companies to truly create good software as most of the good stuff comes from a small portion of skilled coders. It may be a good idea to give such hiring strategies a careful consideration. I hope my rambling is useful to hydrologists to reflect and find a good solution or hiring strategy.


Solomon Vimal


Solomon Vimal is an avid reader of the About Hydrology blog since 2011. He completed a PhD in hydrology in 2022 from University of California, Los Angeles on the topic, “Climate Change Impacts on Millions of Lakes”. He is now the founder and CEO of Geothara, a tech company currently incubated as a startup company at UCLA’s summer accelerator program and part of the 2022 cohort of the Runway Postdoc program at Cornell Tech in New York City. 


About Geothara: Geothara offers geographic change detection and visualization software to help its users explore the changing world using satellite images and a novel, up to 30% more accurate trend detection technique via a patent-pending technology that enables smarter location-specific decisions.


Comments by rr


* However, I would make not just a point of salary. The salary of a PhD student is not high but enough to live in Italy, if you are a young guy. Obviously you expect that the sacrifice bring some benefits. I cannot judge myself, but I believe that you can learn something from studying in Trento that you cannot learn elsewhere.


** small field (if we restrict our focus on digital hydrology) but important for life on Earth and for any community if we think that all is about water availability. After all everything which is alive requires water.

*** when we have our son, I felt somewhat inadequate to the role of father. Then I simply did (and I am doing) it. Never the fear should to succeed to stop you. Try ! PhD is a learning process.

**** That degree would be great to be set up but the start it is subject to the uncertainties and foresight of academic policies

***** unfortunately in Italy the salary is established once forever by the state (ok, maybe the single Universities could give some incentives). I will investigate what is possible.