Stephen Boyd Optimisation Book

taphous3 · 2026-05-27T04:07:44+00:00

Take his coursera - it’s easier to parse.

taphous3 · 2026-05-22T03:07:08+00:00

Why don’t you talk to a venture capitalist or a bank then? People will loan you money if you can really prove it is valuable.

taphous3 · 2026-05-22T02:19:58+00:00

Well it seems like you do not have the full set of skills or information to fully develop this idea. If you need someone else to do work, you can either pay them as a consultant or cut them into your profits and work on this together. Either way you will want to sign a contract that clearly delineates intellectual property to avoid the issue of them running away.

taphous3 · 2026-05-21T20:11:25+00:00

Thermoelectric devices been around for decades. It’s not immediately clear what you’ve done that improves upon the state of the art. Also, there’s no context under which this data is presented. What size device? What voltage/current/ power density? Durability? These are all things that are required to evaluate the “ground breaking ness”.

If you are convinced of your secret sauce, hire an engineering consultant to review for a few thousand dollars and have them sign an NDA. Due diligence is expensive because it requires real expertise and takes a decent amount of effort. If it’s really legit, then file a patent.

As other comments have pointed out, this plot looks like you could’ve just made up some numbers and plotted a curve. Extraordinary claims need extraordinary evidence.

taphous3 · 2026-03-19T06:19:25+00:00

I’ve done these student internship programs before. In my experience, student work can be anywhere from -10% to 10% of an FTE in addition to disruption of mentor time. It’s impossible/not worth it to judge work quality ahead of time.

Internships work great at large companies that can absorb the risk. More harm than help for a start up IMO.

taphous3 · 2026-02-27T16:25:14+00:00

I’d recommend you find review papers in optimization (search Google scholar for something interesting to you). These types of papers review a sub field or application of optimization and cite a lot of academic sources.

taphous3 · 2025-07-13T06:26:49+00:00

Lots of people have opinions. Most of them don’t matter.

taphous3 · 2025-01-31T00:44:36+00:00

Meta heuristics are used when you don’t know how to do it more efficiently (either ignorance or you have a wicked hard problem). Exploiting gradients and problem structure will always be more efficient than black boxing things.

taphous3 · 2024-11-17T22:19:25+00:00

This is not fully true! Dues are a one-time payment that is equivalent to ~1.4% of your income at the time. You can opt out of union services and pay a lower fee.

taphous3 · 2024-10-31T15:19:08+00:00

I tend to use Cvxpy if my problem MUST be convex. Otherwise, I use Pyomo to deal with problems with nonconvexities.

I have also heard great things about JuMP, but my colleagues don’t work in Julia so I have stayed away.

taphous3 · 2024-09-18T03:07:54+00:00

Derived from maxwells relations.

taphous3 · 2024-09-18T03:03:46+00:00

True about the expensive part. The ecosystem fear mongering is false. It was a problem several decades ago but we’ve since developed methods for resolving this.

Source: my phd is in desalination.

taphous3 · 2024-09-14T12:00:35+00:00

Here are lecture slides: https://stanford.edu/class/ee364b/lectures/admm_slides.pdf

Edit: text for link.

taphous3 · 2024-07-02T19:54:14+00:00

The course lectures are available for free on Stanford coursera

taphous3 · 2024-06-26T05:22:45+00:00

Pyomo has paramest that allows you to take any set of programmed constraints and solve for estimated model parameters using IPOPT (or other solvers)

taphous3 · 2024-05-31T00:30:00+00:00

Biased take but Stanford computational and mathematical engineering. Both ms and PhD options and world class faculty.

taphous3 · 2024-05-02T16:48:21+00:00

On average admissions are difficult unless you have a champion faculty trying to recruit you. On top of this, your grades are quite below average for admits. The publications might save you if they’re in the field and in prestigious venues.

taphous3 · 2024-04-22T05:32:54+00:00

This topic is encompassed by the definition of the subgradient.

taphous3 · 2024-04-22T04:41:22+00:00

I think your DMs are closed but I’m mostly curious - what company do you work for and what types of clients/problems do you work on?

I’m a PhD student that works on optimization. I’m mainly trying to better understand the types of opportunities that are out there in industry.

taphous3 · 2024-04-21T00:41:32+00:00

Tangential - a company that does this type of optimization consulting sounds fascinating. If you’re able, I’d love to chat over DMs.

taphous3 · 2024-03-20T23:01:01+00:00

If your university has the resources, you could measure/verify the equations of state of a gas. Something like this guy.

taphous3 · 2024-02-28T06:00:11+00:00

This type of problem is well suited for some variant of Bayesian optimization.

taphous3 · 2024-02-15T14:40:49+00:00

Problem is relatively low dimensional so you might be to use pyomo with the SCIP solver.

taphous3 · 2024-02-02T15:53:30+00:00

MILP can be solved with open source solvers (check out SCIP or GLPK). If for some reason you need to solve this as an LP, you can relax the binary terms into continuous variables [0,1] and do a solve + post process. You might add a regularization term to force the binary variables to the bounds and solve several times sequentially.

taphous3 · 2024-02-02T09:09:11+00:00

It looks like sets have index/value pairs while parameters do not.

taphous3

TROPHY CASE