Year in review: third year as a PhD student

As I mentioned before, it’s important to keep track of your successes and disapointments. Since I do have a list of sorts, I decided to share my summary of 2013 here.


2013 was definitely a year of journal papers. Or at least, of long overdue journal paper submissions. Here are the totals! I submitted four times in total (one paper twice, and two papers once). Two of these were rejections, one “revise and resubmit” and one still under review. So, 2014 probably will be a year of journal paper resubmissions.


Next to paper writing, there was also paper reviewing. In the beginning of last year, I was getting worried that I was not invited for reviews, but this worry turned out to be unfounded. I guess this goes together with submitting journal papers (and getting into the system) and meeting more people, who have more reviews than you, but are also more busy. I want to believe in review-karma: by writing good reviews, I hope to get good reviews. By good, I mean objective and constructive, not necessarily an “accept”.


2013 was also a year in which I tried to apply for scholarships to finance my conference visits and the trip to Tuebingen. For the second time (the first time being in 2012), I did not get the Anita Borg scholarship. I did get the ACM-W / Microsoft Research grant to go to a conference in China, which was awesome! The application that I spent quite a lot of time on, for the short-term fellowship from EMBO to go to Tuebingen, unfortunately got rejected (after I returned from Tuebingen already). However, I was able to get some financial support through my university, which was not a competitive application, but very helpful.

Research visit

And of course, 2013 was the year I went on a research visit, for which I have not (yet?) been able to write an overview. In short, the three months went by really fast and I had a great time. What everybody says about research visits is true. It is really helpful to experience a different place and get an idea of how people do research there. I think it’s a must for all PhD students, especially from smaller labs. It probably doesn’t even need to be a lab in a different country to get an impression of “how things are done” and to pick up useful research skills. I already have my next short visit planned, what about you? Did you / will you do a research visit during your PhD?

On recording your progress

It’s been almost a year since I started to blog alongside my PhD. I’m not sure whether I mentioned this a year ago, but my initial goal was to write something every week, which quickly deteriorated into writing something every month. With this post, I have been able to keep the latter promise up.

Although I had many moments of “oh, this is something I could write a post about!”, only few of them actually made their way from my thoughts into a digital version. The main reasons for this are, I think:

– too little practice: I really do find it difficult to write something that’s not directly about my research

– too little privacy: there are some issues I would not want to discuss online because my name is linked to my blog and I don’t want my opinions to always be “out there” somewhere. Many of the blogs I find very interesting (not just the ones that are linked on this page) are actually blogs that discuss such issues, and for 95%* these are anonymous.
* I initially wrote 95\% which amused me quite a lot.

– too little expertise: I like posts which contain advice on how to do something better, such as never worrying about poster transport again. The truth is, however, that there are not a lot of things I feel I’m more knowledgeable about than other researchers with blogs.

– too little information: I am, of course, knowledgeable about what I do on a daily basis (submitted this, got rejected for that). Of course, this is mostly relevant to me and not to readers in general. I am aware this is my blog and I can post whatever I like, but I am less motivated to spend time writing something that is not helpful to others. Also, I

What I recently realized is that I would have enjoyed to have more of these “progress” posts, just for myself. In my first attempt at blogging, I wrote about how I submitted my first paper and how a few months later, I got the email that started with, “We are pleased to inform you…”. Or about how I reviewed the paper for the first time, and it turned out to be horrible. It’s nice to remember how I felt then, what my goals were, and how I generally thought about research.

My advice (this is actually a helpful post!) if you are a PhD student: write your successes and disappointments down somewhere. Not necessarily in a blog. Maybe it’s even better if it’s not a blog, you might spend less time worrying about how to write it down, and who is going to read it. But sometime later, you will enjoy reading about these experiences, and what they tell you about your progress. Happy writing!

Year in review: second year as a PhD student

This post originally appeared on my previous blog.

After my one-year evaluation, the first thing I did was sign up for a course on presentation skills. To be honest, I hesitated a bit at first, but I started hearing quite a few good things about Art of Presenting Science, so I decided to see for myself what that was all about. I really, really loved it! I can’t really summarize my experiences in a few sentences, so perhaps I will dedicate a whole post to this.  I tried to put a few of the things I learned to the test when presenting my work at the meeting of the NVPHBV (Dutch Society for Pattern Recognition and Image Processing), and at the Benelearn conference in Gent, Belgium.

As for research, I was pursuing several directions that are relevant to Multiple Instance Learning, learning with dissimilarities, or both.  A few of these ideas resulted in submissions to conferences, while others were abandoned after a while. Perhaps “abandoned” is not the correct word to describe the situation, and “on the shelf” would be better.  The ideas are still very interesting, but at the time I did not have enough insight to turn them into something that could be published. I hope that I will have more luck with this in 2013 🙂

In the summer it was time to take a break from my own research, and learn a lot about what others are doing at the Machine Learning Summer School in Santa Cruz, California in the US. The summer school consisted of two weeks of lectures from people from academia and from industry. The proximity to Silicon Valley ensured a lot of interesting talks by Google, Facebook and other companies that have a lot of data and therefore do a lot of machine learning. Next to all the talks, it was a great experience to meet other researchers from all of the world and compare notes on everything from doing a PhD to making tacos. I hope we will meet again!


As if that wasn’t enough traveling, I received the decisions on two papers that were submitted a few months ago. Both were accepted as poster presentations: “Does one rotten apple spoil the whole barrel” at the International Conference on Pattern Recognition (ICPR), and “Class-Dependent Bag Dissimilarities for Multiple Instance Learning” at the Structural, Syntactic and Statistical Pattern Recognition (S+SSPR) workshop.  S+SSPR was held in Hiroshima, and ICPR was held in Tsukuba, close to Tokyo. With an extra day to recover from jetlag and a few days (because three weeks in the US aren’t cheap) for sightseeing, this meant a two-week trip to Japan. One of my posters in action:


I enjoyed both conferences although they were completely different from each other. S+SSPR was very small, which allowed informal discussions more often and attending a lot of the talks. I also noticed the same type of close community (but with a different subset of researchers) that I saw at Multiple Classifier Systems a year earlier. ICPR was very big, which was a new experience for me. The program booklet was as large as the proceedings of some conferences! Therefore it was quite difficult to choose which talks to attend. I found out that often, my first impression (such as “this is relevant to my research” or “I won’t understand this at all”) was wrong.  In fact, I was pleasantly surprised by a few talks about unrelated topics, but given by a great presenter. There is still a lot to learn for me there.

Although I thought I could deal with time differences pretty well, I did have a few sleepless nights in Japan. On one of these nights, I had an idea about the relationship of my own work to a quite successful MIL classifier. Who wouldn’t get inspired if you are surrounded by wonderful things like this:




Instead of scribbling the idea down with a few words, arrows etc, which is what I usually do, I actually started writing the paper. I didn’t get very far while I was in Japan, but I did discuss the idea and let it develop. After the decision to made to submit a paper to Multiple Classifier Systems 2013 (I admit, I loved MCS 2011 so much I just couldn’t resist), the whole process of writing and submitting the paper cost me about a month. Perhaps that might be long for some people, but for me it was definitely a record. I’m also very happy with the process, so perhaps I will try this more often (starting to write a paper as soon as the idea is there).


Year in review: first year as a PhD student and before

This post was originally appeared on my previous blog.

Before I write an overview of 2012, I thought it would be nice to write about some highlights of the previous year.

I graduated in November 2010 with a thesis titled “Random Subspace Method for One-Class Classifiers“. This is me with my diploma:


After going on vacation and celebrating the start of 2011, my first official working day was on the 3rd of January 2011. Now my job was to work on a different pattern recognition topic: Dissimilarity-based Multiple Instance Learning. 

However, for a while I still continued working on my MSc subject in order to write a paper for Multiple Classifier Systems 2011. The paper “Pruned Random Subspace Method for One-Class Classifiers” (as you can guess, the regular method was not good enough) was accepted for presentation!

In June we went to Naples, Italy for the MCS 2011 conference. Here is an impression of me presenting:


Here is an impression of the conference lunch:


Besides the great food, wine and weather I really really enjoyed the conference. I finally got to meet the people behind all the papers I have been citing and I got a feel for the type of community that all these people formed. After the conference, we had a few days to see more of Naples, the Vesuvius volcano and the ruins of Pompei.

As my next project, I helped with a journal paper that a colleague of mine was writing, “Bridging Feature and Structure Representations in Graph Matching”. Without getting into too many details, we wanted to classify objects that are represented as attributed graphs, while varying the importance of the attributes (features) or the actual graph structure. We investigated two ways to do this: using a graph edit distance and using graph kernels, which was my part. Besides learning a lot about graph kernels, I really enjoyed this project because of the regular meetings and discussions and my responsibility to the other people involved.

In September, it was time to go to Italy again, now for the Similarity-based Pattern Recognition Workshop (SIMBAD) 2011 in Venice. My supervisor presented the paper “Bag Dissimilarities for Multiple Instance Learning”, which is also what most of my current work is about. Unfortunately, I was very ill during the conference, so I didn’t have such a good conference and sightseeing experience as in Naples.

Next to research, some of my time was spent on education. I followed courses on topics related to image processing and bioinformatics, and also did the online Machine Learning course, which was very helpful. I also got to experience education from a different side a little bit while assisting in Pattern Recognition courses for PhD students and for people from industry.

In the end of the year, I had my go/no-go presentation and I received a go, together with a lot of helpful advice on how to improve my work. The main points were to become more comfortable with mathematics, be more precise in why I’m pursuing a certain direction in research, and to improve my presentation skills.

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