Confessions of a researchaholic

April 30, 2016

Strength in numbers

Filed under: Real — liyiwei @ 12:12 pm
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In his PhD application, a student indicated that he is collaborating with a famous professor on a recent SIGGRAPH project.

I asked that professor about the student. He told me that the project has 20 students (most are not co-authors), and the particular student is probably not even a secondary helper.

In comparison, most of my projects so far involve 0 or 1 student, and none over 2 students.
🙂

April 20, 2016

User interface

Filed under: Real — liyiwei @ 8:45 pm
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When I was in grad school I thought UI is about tuning widgets and doing user studies (a lot of research did exactly that). I preferred working on algorithms because they seem more interesting and more fundamental.

Later on, I realized how wrong I was. User interface is crucial as long as humans remain biological and machines remain mechanical.
A good UI can save a not so good algorithm, but not vice versa.
And UI research can also be fun and fundamental.

April 17, 2016

Hiring mistakes

Filed under: Real — liyiwei @ 6:43 pm
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Hiring PhD students is even harder than hiring employees because younger folks have more potential to grow.
And unlike an industry researcher who can let interns come and go, a university professor sticks with the students.

Two prior PhD applicants to HKU whom I passed on have turned out with outstanding performance.

One of them is still collaborating with me, so I did not regret as much. Actually, if he had not gone to another school we would not have access to some crucial hardware environment for our project, and his adviser might not have warmed back to SIGGRAPH. So I probably still made the right call.
🙂

I clearly have a lot to learn, and will have hundreds of cases to practice every year.

April 12, 2016

Research coherence

Filed under: Real — liyiwei @ 7:31 pm
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One common advice on research is to have a coherent theme among our papers. I heard this from a bigwig around 2003 after getting my PhD.

This is one of these advices that I agree in principle but have violated in practice.
=D

Yes, coherence can help recognition from the community, especially when one enters a new field.

However, I am not sure if this should be intentionally aimed for. Unless you are extremely smart and versatile, you are likely end up doing related stuff without even trying.

There is this implicit force that drags us towards similar, and thus incremental, ideas. We should fight against this force, not follow it.
So, just do whatever you like. You will have more fun and more likely to produce novel stuff which, even if lacks coherence, beats being incremental.

April 9, 2016

How to design talk slides

Filed under: Real — liyiwei @ 11:57 pm
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Using slides is a popular way to give presentations. I am not sure if it is the best way, but things can go very badly if done in the wrong way.

Take a look at Jim Blinn’s post about giving presentations.
Below are some quick high level suggestions. (I plan to refine this post later.)

Aim for simplicity and minimalism.

The slides are for conveying information to your audience, not serving as memo for the speaker.

Use intuitive pictures, illustrations, and animations, instead of texts and (worse) equations.

If you find yourself worrying about typography, it is a sign of too much texts.
No sentence should run over one line.

Rid of visual clutters like bullet points.

Gratuitous colors and unnecessary font variations tend to confuse people.

March 24, 2016

Recording and sharing presentation

Filed under: Real — liyiwei @ 9:43 am
Tags: ,

Talks are usually easier to understand than the corresponding papers. To get accepted, papers need to be written in a way that look formal and rigorous, but not necessarily easy to understand. However, when authors present their (accepted) papers, they tend to cut the chase and talk straight.

In the past, people have to attend conferences for the talks.
Nowadays, everyone can easily share their talk slides online.
Better yet, record and share your presentations as videos (e.g. via PowerPoint). This can be done during practices or official presentation.
You do practice your talks, right? So why not record during your rehearsals, so that you can review now and share later.
Recording in official presentation might be trickier, e.g. the conference may prefer presenters using a shared machine and the recording might disrupt your presentation, but can be worth a try.

I have not done this for my own talks, but realized it can be a good idea after watching a few recorded talks online. I really appreciate the efforts from the authors, and plan to do so for my future talks.

March 11, 2016

Why it is fun to review journal papers

Filed under: Real — liyiwei @ 1:15 pm
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After kindly agreeing to review a journal revision for the N-th time, the guy commented that “it’s the gift that keeps on giving!” 🙂

Conversation with collaborator X prior to a SIGGRAPH rebuttal

Filed under: Real — liyiwei @ 1:11 pm
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X: I’m really eager to see what the SIGGRAPH reviewers have in store for us this time… The suspense is killing me. =o

Li-Yi: I just assume they will screw me, and I am never disappointed. 🙂

X: Yes, that’s what I do as well, but I’m always amazed about how they always find ways to complain about the stuff you don’t expect. 😮

Li-Yi: If I can expect what others will think, I will be like some sort of x-men or superman. 🙂

February 1, 2016

The cat experiment

Filed under: Real — liyiwei @ 11:07 am
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Once, when I was around 9 or 10, I was visiting my aunt’s place.

One of the cousins, X, and I were standing near the swimming pool. The family cat walked by. Cousin X and I got into the discussion about whether cats can swim. I have seen a few dogs and at least one horse swam, so I was pretty sure the answer is yes (cats seem more agile). Cousin X disagreed (he is older but not necessarily smarter), so we decided to have a bet.

Clearly, the only way to settle the bet is to experiment, so I grabbed the cat and threw it into the pool.
(That was before the age of YouTube and Google, BTW.)

What followed was amazing, and happened like within a few milliseconds. The cat sprang on the water surface like a trampoline, and immediate landed back near my feet. It was dripping, so it clearly fell into the water, but I had no idea how it managed to jump back. Meanwhile, our debate remained unsettled.

I am trying to come up with a very concrete way to tell a new PhD student how to decide whether someone is suitable for (scientific) research. So here is my try. Let me know if you have better ideas.

Do you like to ask questions that seem interesting at least to you (e.g. whether cats can swim)?

Do you enjoy finding the answers yourself through investigations and experiments (e.g. grab the cat and throw it into the pool, and observe what happens)?

Are you very comfortable with the consequences, regardless of the outcomes of the experiments (e.g. the cat neither swam nor sank and my aunt beat me up)?

Can you do this continuously as a career? Imagine it is Friday lunch time, and all the works you have done this week have turned out to be failures (e.g. no other ways you have tried can tell you whether cats can swim).
You have no idea what is going to happen this afternoon when you try your 101th experiment with that cat.

If you hesitate for any of these questions or you think I am crazy, you are probably not suitable for research. At least, you will not be happy or successful.

Talent and personality are important; you have to be sufficiently smart and tough for research. But passion is even more important; the only way to be truly happy and productive is to do what you really like.

January 29, 2016

School versus job performance

Filed under: Real — liyiwei @ 4:29 pm
Tags: , ,

How predictive is the school performance for the eventual job (and life) performance of an individual?

This is a very important question. The schools are supposed to educate what is actually useful. (But clearly that is not the case in practice.)

This is also a very broad question under perennial discussion.

In my personal experiences on the creative side of computer science (e.g. research and development for the cutting edge of graphics and HCI), there is a weak positive correlation between school and job performance (around 0.2 to 0.3 if I have to be numeric).
Good school performance reflects positive traits such as talent and work ethics, but also negative traits such as conformity, lack of creativity, and risk aversion.

This is why standard statistics, like grades, schools, and rankings, are not enough and sometimes even misleading. We have to look at more practical evidence, such as publications, projects, and recommendations.

This is also why recruiting top students and employees is very challenging. Top schools and companies do have advantages in attracting top talents, but we only get what we look for. Many of the best people I have worked so far had been bypassed by the traditional screening standards. Conversely, I have also seen many weak people in top institutions.

Maybe one day data analysis and machine learning will solve this problem.
Before that, I rely on the good old way of people reading.

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