Author: Yu Gu

Last Quarter Moon

by Yu Gu, posted in Astronomy, Uncategorized

This is an 9-panel mosaic of the last quarter moon. The seeing was excellent at the beginning and it deteriorates a bit towards the end. My C11 also has some field curvature and collimation imperfection. But I think the end result looks quite good. I also added a Mars image from the same night (~8hours earlier) for comparison of their visual sizes.

See a much larger version of this photo on my Astrobin page.

Or click here for a full resolution (about 300 meters per pixel) version (make sure to zoom in!).

Starting a Deep Sky Gallery

by Yu Gu, posted in Astronomy, Uncategorized

After NEOWISE, I  am getting more interested in learning deep sky astrophotography.

With a recently acquired Astrophysics 92mm F6.65 Stowaway and a 0.8x field reducer/corrector, I really don’t have excuses.

Here are the first two images taken from my light-polluted backyard that I am quite happy about: M27, Dumbbell planetary nebula, and M13, the Hercules globular cluster.

The camera used was an unmodified Sony A7RII, no filter, 100 x 30s exposures at ISO 800 (to avoid the star-eating problem…).

Comet NEOWISE

by Yu Gu, posted in Astronomy, Uncategorized

In almost 45 orbits around the sun, I have only gotten to see a handful of comets.

Halley’s Comet’s return in 1986 was the single event that ignited my interest in astronomy. I was 11 back then. All of a sudden, everyone in school was talking about Halley. All the kids wanted to see it, and I wanted to see it too! The “instrument” I had at the time was a pair of toy 2X binoculars. I begged my parents to buy me a real telescope, but they could not afford one. One day, my dad borrowed a telescope just to check it out, but it was too expensive. It was about 50 Yuan (or 10 USD), roughly my parents’ salaries for a month.  I used my 2X binoculars to scan the sky every evening and I did not find anything. Nobody I knew seemed to have seen Halley, except for some rumors floating around. But we were just kids. We knew that if we take care of ourselves, we may get to see it in year 2061!

The interest in astronomy and telescopes stuck with me ever since. Years later, I have gotten to know several people sharing the same story: Halley helped them to discover the passion that they didn’t know existed, despite that they never got to see it.

Fast forward four years (1990), I was in high school. My dad’s best friend gave him a pair of 10×50 binoculars, after he visited America. I started to scan the night sky from my balcony anytime I can. One night, I came across a fuzzy cotton ball near zenith, which seemed strange. The next night, it was still there, but moved a little. Maybe I found a comet? I wrote a letter to Beijing planetarium about this finding. To my surprise, I received a reply a few weeks later. What I saw was a comet discovered by Levy (a famous comet hunter) a couple months earlier. That was enough excitement to keep me up at night! I became more diligent at scanning for comets; but with no success.

Five years later (1995), I was a college student in Shanghai. School load and light pollution had made astronomy a distant memory. That was until Hale–Bopp showed up, one of the great comets of the 20th century. It was supposed to be not only visible, but also spectacular to the naked eyes! But not for people in Shanghai. If you have sharp eyesight and patience, you maybe able to find 5-10 stars in the Shanghai night sky in those days. I had a homemade 3cm scope with me and I found Hale–Bopp from the top of a tall school building: a faint glow in the orange sky!

Another four years had passed before I arrived in the US (1999). One day, about one year later, I realized that I could actually afford a decent telescope, with my humble graduate research assistantship. I went all crazy on telescopes and planetary imaging. I have seen a couple comets over the years but nothing too exciting. Oh, I also saw the 2009 Wesley Jupiter impact event. Not sure if it was caused by a comet, but close enough to the famous comet Shoemaker–Levy 9 impacts that I missed.

Now, year 2020, comet NEOWISE is here to visit the sun. My son is now at the age when I was helplessly hunting for Halley in the sky and my daughter is only 2-years behind.  The whole family got up early one day to see NEOWISE rising before the sun. Now the comet is in the night sky, we can observe it from the comfort of our front porch. I have never taken a photo of a comet before NEOWISE so it’s an excellent opportunity to practice!

An NSF REU Proposal on Human-Swarm Interaction

by Yu Gu, posted in Research, Robotics, Students, Uncategorized

I am sharing a REU (Research Experience for Undergraduates) proposal. When I first started writing this proposal, along with my colleagues Dr. Gross and Dr. Klink, we had no idea where to start. I searched the internet and found a couple sample REU proposals. Several friends also kindly shared their successful proposals. Now, it’s my turn to give back!

The project is about human-swarm interaction: how can one person effectively manage a 50-robot swarm in achieving a high-level goal? In the project, the undergraduate students need to design the robots, the test environment, a simulator, human-machine interfaces, along with swarm control algorithms. They would also perform a variety of experiments to demonstrate these capabilities.

During the first year (2019) program, eight undergraduate students from around the country worked together with several WVU students for 10 weeks. They designed and built 50 robots (!) and developed the basic swarm control software. Here is a video:

Here is a paper written by the students. One major difference between our REU Site and most other REU programs is that all students were working together on a same project. They had to work as a team (I called them a swarm…) to achieve the overall project goal.

This year (2020), however, we had to cancel the program due to COVID. We will be back in motion again next year!

The proposal received a C (Competitive) from the NSF review panel. The individual reviewer ratings were VG/G, VG, VG, VG/G (VG – very good, G – good). In general, the reviewers were excited about the project research ideas, but had concerns about our detailed program designs. Of course, we were very inexperienced in this area at the time.

Attachment: REU Proposal

The CV that Gets You the Faculty Interviews

by Yu Gu, posted in Faculty, Job, Robotics, Students, Uncategorized

If you are a Ph.D. student or a post-doc, you probably have thought about the prospect of becoming a professor at some point, even though this option may not be high on your list. If you only thought about getting a faculty position shortly before applying, you probably won’t get an interview; because it takes planning and time to build up a CV that is competitive for the faculty job market. When is the best time to start planning your academic CV? During your undergraduate years. Ok, if you missed that, and I don’t think I know anyone who didn’t, the earlier the better. I only started caring about my CV three years after my Ph.D., and I had to pay for that …

A strong CV is simply the most important part of your faculty job application package, and sometimes, it may be the only thing that a search committee member reads.

Sun Tzu once said: “If you know the enemy and know yourself, you need not fear the result of a hundred battles.”

There would probably be more than 100 battles for a faculty-job applicant. Let’s first think about your opponents: the search committee members. We are talking about a bunch of professors who may or may not be in your field. They have all failed numerous times in the past but those memories have faded. They are now trying to get through busy daily schedules and fulfill the service duty with the minimum time/energy costs. Reading tens, if not hundreds, of applications is just not that fun for them anymore. To prevent these people from making arbitrary decisions there is likely some kind of forms that the search committee members must fill. These are probably pre-determined performance metrics that evaluate your record or potential on teaching, research, and service. What does all this mean? It means your CV needs to be simple (easy to find relevant information) and well rounded. You shouldn’t be lagging your competitors in any of the major categories (e.g., publication, teaching, funding, and service). An easy way to find out the going credentials is to check out the CVs of newly hired faculty members in your field; they are not hard to find on the internet. Scoring a zero in any of these categories is not going to look good for you.

You might wonder how would you get teaching and funding experiences when you are still a graduate student? You can if you try hard enough. For example, you can offer to teach or co-teach a class; you can submit fellowship proposals; and you can attend teaching and grant writing workshops. A reasonable search committee would consider your available opportunities as a student, but you must demonstrate that you are proactive and have the potential. This would also help you later during the interview process.

Would this be enough? Not yet. Having all the boxes checked may get you a decent first impression. It may also take away some of the arguments for someone on the committee to strongly against you. What you really need now is a few strong supporters on the committee. In other words, you must impress them.

What makes your CV look impressive? Here is my rule of thumb: the most impressive things are the ones many people have tried but could not get. If you have done something unique but no one on the search committee has thought about trying, then sadly, it’s likely to go unnoticed. What are some examples of impressive things? publications in highly selective journals/conferences, best paper awards, prestigious fellowships/grants, a new theory, solving a known hard problem, …. Of course, you need to be good, work hard, and have abundance of luck, to get even one of these. Many people focus energy on achieving the seemingly least uncertain goal: increase the number of high-quality publications. However, if you have special talents, you may find a different path to success.

I want to quickly bring up the discussion of quality vs quantity here. I have seen CVs with over 100 papers not being appreciated by the search committee. A CV with just 1-2 good papers (unless they are on Nature or Science…) may also not be convincing enough. What if this person was just lucky or was working in a very small niche area? In robotics, for a freshly graduated Ph.D., I think 2-3 first-authored top journal papers and 2-3 first-authored top conference papers, plus a similar number of non-first-authored high-quality papers would make your CV look quite impressive. It’s certainly not easily achievable within the Ph.D. period. Adding more low-quality papers to the mix would only serve to reduce the perceived quality of your CV.

OK, say you have gotten a decent impression for your application package and the committee will meet next Wednesday to decide on a list of candidates to be interviewed. By the time the committee meets, the contents in many applications may have gotten mixed up in their heads, because they all look so much alike… The only chance you have is if you got something stands out, pointed out by one of your advocates on the committee. Other members would quickly flip to that page on your CV. If they also agree and cannot remember anything bad to say about you, then congratulations, most likely you would get an interview.

So, let me summarize it: create a CV that maximize the “expected” number of supporters (e.g., having something impressive) and minimize the number of naysayers (e.g., being well-rounded).

How to get there? This is the part about “knowing yourself.” Discover your true passions and strengths and come up with a plan for yourself. Well, …, that’s easy to say than done. Without known better, one way that worked well for me was to start by making myself look bad: creating the Google Scholar profile and making it public; posting the CV online; asking myself awkward questions like what are my top 3 contributions to the field? I found things usually get better after I learned to not avoid myself.

Attachment: my CV back in 2008, over 3 years after my Ph.D., which, unsurprisingly, did not get me anywhere.

Shake Your Camera to Take Sharper Photos

by Yu Gu, posted in Future, Ideas, Uncategorized

Computational photography is changing the way how photos are taken. More and more cell phones are using computation to offset the small lenses allowed on the phones and the progress has been amazing. What I am still waiting on is a way to allow shaky cameras to take sharper photos. Arguably, a shaky camera can provide more information of a scene than a steady camera. It seems like our brain-eye (and inertial?) system can process it, which gives us a stable (and sharp!) perception of the world while moving. Since most phone users are not so good at holding their cameras steady, why not taking advantage of the shaking? Even better would be allowing a shaky telescope to provide a sharper view of the planets! Has this been done before? Can someone point me to a product or a paper using this approach?

So, What Do We Do with It?

by Yu Gu, posted in Astronomy, Photography, Research, Robotics, Uncategorized

I am more of a telescope collector than a sky watcher. I have about a dozen telescopes of different designs: achromatic, apochromatic, doublet refractors, triplets, Newtonians, Maksutov-Cassegrain, Maksutov Newtonian, H-alpha solar scope, Dobsonian mounts, German equatorial mounts, roof prism binoculars, porro prism binoculars… you name it. I know way more about telescope designs than constellations of the sky or features on Mars. Most of my telescopes spend years collecting photons in a very dark place: my closet.

I am more of a camera lover than a photophile. I have several cameras from the film era to the mirrorless age. I have a couple dozen lenses with focal lengths ranging from 14mm-500mm, not counting telescopes.

I have learned to accept this. There is nothing wrong with being obsessed with equipment, I told myself, the hobby is supposed to be fun!

I also like robots. My lab, IRL, has about two dozen robots, plus a 50-robot swarm. The UAV lab I worked in before had about a dozen UAVs. Most (but not all) of these robots and UAVs were custom developed. I, as someone who always like toys, had a hand in the design of most of these systems.

So now, what happens when we have all the hardware we ever wanted? Of course, we can only get close, but not there. There is a pretty big difference between “wants” and “needs”, and we often rationalize “wants” as “needs”. As engineers and perfectionists, seeing small issues with the current setup makes us feel itching. We are constantly dreaming up next design iterations. We are telling ourselves better robots will make our research better.

Is that true? Do we really need more/better robots to do better research? Maybe to some degree. If we don’t have the appropriate tools, we can’t do certain experiments. If we don’t have high quality equipment, some work may be very hard to do (e.g., mapping without 3D Lidar or robotic pollination without a precision manipulator). I think another important reason for having the best robots, like having the best telescopes/cameras, is that we have no one else but ourselves to blame for the underperformance…

So, let me ask again, what happens when we have all the hardware we ever wanted? What do we do with it? The answer is simple: let’s focus on research. Instead of rushing to start on the next generation design and letting the existing robots collect dusts, let’s make them do things nobody else can dream of or believe!

What Makes a Good Grand Challenge?

by Yu Gu, posted in Ideas, Robotics, Uncategorized

I am a big fan of Grand Challenges.

I was super motivated when reading about John Harrison, a self-taught engineer (carpenter) in the 18th century, who won the longitude reward through decades of perfecting clockmaking skills.  I also watched several DARPA Challenges with great interests. I have participated in, for three years, NASA’s Centennial Challenge on Sample Return Robot. Those three years left me with countless memorable moments to be enjoyed for the rest of my life.

What I like most about Grand Challenges is that they give people excitement and hope. Grand Challenges allow someone, who otherwise would not be known by people, such as John Harrison and Charles Lindbergh, to shine through their courage, dedication, and talent. They also can accelerate technology development, by bringing together a broader range of conventional and unconventional innovators and solutions.

However, many Grand Challenges failed to achieve these effects, for a variety of reasons. Here are a few factors I think maybe worth considering when designing a new Challenge.

  1. It needs to be relevant. If a Challenge addresses one of humanity’s most urgent needs, more people would likely to follow and participate.
  2. It must be a Challenge. A Grand Challenge needs to be hard. It should be a jump from any of our known abilities. It may sound impossible at first, but It’s so cool that it makes people imagine. The Challenge shall also not be too big a jump, otherwise everyone would fail (which is an acceptable but not desirable outcome).
  3. The Challenge description must be clear, rigorous, and stable. Like any games, there should be no ambiguity and room for interpretation. The actual tests must also precisely match the description. Unfortunately, quite often, the organizers did not fully think through all the issues at the beginning. They would come up with a set of rules that cause confusions (and potentially unfairness) and then they dumb down the challenge after most participants failed (this happens more often than you may want to believe!).
  4. Human factors must be kept at a minimum. One of the Grand Challenge’s greatest strengths is that it gives everyone a fair chance. You do not have to be a world renown thinker/scientist/engineer, you do not have to be rich, you do not even need to have a stable job; as long as you have a good idea, the skills, and the will (easy to say than done), you have your fair chance of winning. The success of a Grand Challenge should be defined by beating the problem, not anyone or anything else. If we allowed humans (e.g., the Challenge organizers) to pick winners based on their pre-conceived ways of solving the problem, John Harrison would had no chance against big name astronomers at the time (note: the Longitude Board, including Newton’s preference on finding an astronomy-based solution did cause hardship to Harrison for many years…). Let the results speak for themselves!
  5. Teams shall come up with their own resources, at least initially. This one may sound strange to you. Would it not be rewarding people with deeper pockets and leave the poor guys out of the fight? It might, but let’s consider the alternatives for a moment. What if the organizer picks a few promising teams, give each of them a few $M, so they don’t have to be sidetracked by fund raising and other resource constraints?  The question would then be: based on what criteria? prestige? track-record? how likely a team’s idea may work? If you read the history of Grand Challenges, you would know that none of these are reliable indicators of success. What this funding approach does is effective disincentivize the selected teams to push envelopes hard (they already have the cake; the final Challenge prize is just the icing) and block out all other competitors. In my opinion, just like any startups, each team needs to fight for its own survival the entire time. If you think you have a good idea, try to convince someone to fund you, or join another team with adequate resources. I think the phased approach being used by NASA Centennial Challenges is very good. Let teams compete for some initial phases (e.g., a simplified Challenge with a low-entry barrier) on their own dime, provide teams some funds once passed the initial phase. This record of success also helps teams to raise more funds from other sources.
  6. Give it a longer time frame. Most government funding mechanism have a short time horizon, but that is not necessarily good for getting the best outcomes. If a problem is of such importance to the society (e.g., determining longitude), why not keep the challenge alive for decades until it’s solved (luckily, it was!)? Short term focus leads to more applied solutions, discourages risky/crazy ideas, and more likely leads to the picking of lower-hanging fruits. Grand challenges for picking lower-hanging fruits? Does not sound good!
  7. Follow up after the challenge. Don’t let the whole thing ends the moment a victory is declared. Each participant probably has developed something unique/valuable; creating mechanisms (with funding) to support them working together for a little while may spark more innovations.

Of course, we all live within the real-world constraints. I will continue to be excited whenever a new Challenge is announced!

My Anti-CV

by Yu Gu, posted in Job, Uncategorized

I have been wanting to do this for several years: create an anti-CV that documents the major academic/career failures that I had. I used to have a folder for rejection letters, but it soon ran out of space, and I stopped collecting them a long time ago…

Time to find a different way to remember my failures! So here it is, an incomplete version of my anti-CV. I will keep it updated from now on.

My goal has always been to receive no less than 10 rejections a year.

Updated June 2024: Anti-CV

Presenting Your “Whole Package” During Faculty Interviews

by Yu Gu, posted in Job, Students, Uncategorized

It looks easy. All you have to do is to pretend as someone who is better than yourself for half an hour (on the phone/Skype/Zoom), and then a day (on campus), to get that dream faulty job offer.

I tried that a few times as a candidate but was not very successful. I didn’t know what the problems were until years later after serving as the chair or a member on several faculty search committees.

Faculty interview is like speed dating. By the time you made to the interview, we (the search committee) have been impressed by your achievements (on paper), but we haven’t got to know you as a person. We are afraid of picking someone that we may regret and be stuck with for years… That scary thought motivates us to do a careful job.

So what do we care about? First and foremost, we like to know if you are a person we want to work with as a colleague. Are you an open and frank person? Would you see our institution as your future home? Are you the type that can make the people around you better? Do you hold a balanced view of different matters?

Second, we try to predict if you would become a star (not just meeting the tenure requirements) with our yet-to-be-proven fortune telling skills. Do you have a solid grasp of the fundamentals in your area? Are you passionate about something? Can you think critically and independently? Are you aware of ongoing trends in research and in the society? Are you an ambitious person with big dreams and a strong vision? Can you communicate well with different audience, make sound arguments, and be persuasive? Can you be an effective teacher? Can you handle pressure, stress, and setbacks?

Finally, we also want to know if your success would matter to other people. Are you bringing complementary skills (teaching, research) to the institution? Are you a team player? Are you more interested in yourself, the community, or the society? Can you lead a team to build something bigger than us individuals can do?

In a nutshell, we are looking for someone who is way closer to perfection than ourselves …

Of course, we don’t know how to evaluate all that… In robotics terms, we are facing a decision making under uncertainty problem, an active perception problem, and a bounded rationality problem (e.g., making decisions with incomplete information and limited time). Each of us on the committee tries to observe and to probe you with questions. We fall victims to our cognitive biases, jump into conclusions with insufficient data, while trying hard not to fill the missing pieces with stereotypes, imagination, and random thoughts/mood of the day.

So how to survive this complicated, stressful, inherently stochastic, and often biased process? There are a lot you can do before coming to an interview. Preparation and experience help. Iterate on the answers to common questions leads to better, more focused answers. Known what may come helps you to prepare and know when to relax.

However, a skillful search committee can/may see through some of the facade. There are things that can be couched by a good advisor in a matter of hours (e.g., which funding programs to target), but we are not hiring your advisor. Interview experience can be learned (someone had many interviews in the past is not necessarily preferred to someone on the first trip). Always done you homework is a good quality; but is only one of many that we are looking for. Worked on a cool project, like a NASA mission, only means you were on a large team. There are also things that any intelligent person can learn on the job later, without much risks.

What we really want to get to know better is you. We try to focus on things that would take real effort and experience to understand. For example, someone who has never taught a class before would likely not understand the true challenges in teaching and learning. Someone who only did what the advisor told him/her to do may not have deep insights on what is the next step, the step after that, and why. You are unlikely to be a good leader without appreciating the meaning of compromise and sacrifice. Your strong desire to help the community needs to be backed up with a purpose and a track record. You may pretend well for a minute, but if you didn’t have the real experience, this may not survive a few rounds of probing.

Faculty candidates often don’t know why they failed (or succeeded). Almost no search committee can provide frank and detailed feedback due to a variety of reasons. We won’t/can’t tell you that you’ve been acting like a teenage; your accent was not a problem; that name dropping/talking down other researchers did not serve your interest; your honesty and willingness to expose your vulnerability was appreciated; you didn’t seem to be prepared to write a proposal/teach a class/run a lab; etc. I have seen candidates apparently interviewed at many different places didn’t quite understand why they haven’t landed a job. I was in that boat for a few years as well.

So, pretending to be a better, more desirable version of yourself during the interview may not work out. I think a better strategy is to act like that version now, to identify and build up these experiences, and to collect honest feedback. It is never too late for doing that. After you have started on this path, you can follow what many people suggested to do during interviews: “just be yourself”. You no longer have to pretend to be someone better; you are a better faculty candidate.