Technical solution or creative thinking? A Y-DATA graduate on why dealing with data can be so exciting
By: Lyoka Ledenyova
Tags: Cognitive Science, Data Scientist, Biology, Data Science, Neuroscience

Technical solution or creative thinking? A Y-DATA graduate on why dealing with data can be so exciting Lyoka Ledenyova Follow Dec 17 · 6 min read

Meet our hero of the day: Pini Koplovitch — a talented scientist that has recently graduated from our Y-DATA program. Pini’s first degree was centered on what the brain does and how it works, he studied both Cognitive Sciences and Biology at the Hebrew University of Jerusalem. After completing his BSc he proceeded directly to a PhD in Computational Neuroscience with an emphasis on the neuronal basis of neuropathic pain. In his study Pini was developing a genetically engineered biopump as a novel treatment for neuropathic pain, and the initial results of his research were found to be very promising. Unfortunately, during the proceeding phase he faced technical obstacles that did not allow more complex experiments and the continuation of the study. After careful consideration Pini has decided to leave the academic life, but not before receiving his MSc and publishing the PoC results in the leading journal in the field. During his study Pini has already started using clustering algorithms to semi-automatically analyze vast amounts of neuronal activity that helped him conduct much more experiments and increased the overall efficiency of the practical study.

“It’s important to be able to recognize when things are working and when they aren’t, to choose a correct path, as one will oftentimes find themselves on the crossroads in this regard, at least as far as research is concerned. It’s important to understand how things work internally on some level at least, the math and the statistics of it. A data scientist needs skills from both the practical and the research worlds. Many experiments can now be performed due to us having stronger tools in genetics, which allow us to take a closer look at the genes themselves. There are more advanced statistical methods of data science we can use to provide correct analysis. Data science does help a lot, but in the life science field people are still going to find themselves in need to conduct experiments, use live animals for them to see how one subject affects the others, etc. Both sides are going to be required moving further, and the best case scenario would be a scientist well versed in both the experimental and the analytical work.”

After leaving the Edmond & Lily Safra Center for Brain Sciences at the Hebrew University of Jerusalem Pini decided to focus on getting a firmer grasp of data science as a whole in order to positively impact people’s lives. He’s still eager to work in brain science or in the medical field to continue helping sick and diseased people.

“Data science is a tool, and I’m eager to use it in my professional work. I also just enjoy researching things, as I did with my PhD, even though I dropped it for many reasons. I used to work with animal research a lot, and I do want to experiment and discover things of course, but let someone else do the dissecting and I will focus on numbers. Finding solutions is something that excites me the most. I see data science as a tool to achieve said solutions. One can always use data science, but some problems don’t require fancy algorithms to get solved. Heavy machinery is not always the answer.”

Academic work taught Pini how to handle a lot of data, ask the right questions and find the relevant solutions to the problems at hand. He was twice on the Dean’s List, participated in “ETGAR” Honor’s Program and completed Y-DATA program with outstanding success and honors. The Y-DATA industry project he did together with Urska Jelercic for Healthy.io was chosen for distinction.

“When it comes to the Y-Data project, the main challenge we probably faced was working with the small and under-representative set of images the company provided us to work with. Instead of trying to squeeze better performance (and probably overfit) we decided to focus more on error analysis and to better understand which are the ‘hard’ images and what make them hard. This led to probably the main insight we delivered — which classes of images the company should focus when collecting more images. The second insight was that the architecture they encouraged us to work with is overkill for this problem (or at least for the current dataset) and much lighter architectures perform the same. The biggest excitement for me was the fact that we were solving a real life problem. Discussing things with other students and mentors during the project was inspiring, as every now and then I would get new insights or get introduced to new ways of thinking in regards to the problems we needed to solve.”

It seems like there is nothing that excites Pini more than understanding that his work can be beneficial for medical science in general and people’s lives in particular, and still he’s not limiting himself and is ready to test his “good student” skills in new fields as long as it involves solving problems and tackling new challenges. Despite lots of honors that Pini has, he looks extremely modest and undemanding. He knows his strong sides but doesn’t want to brag about it. It doesn’t take a long time though to understand that he’s a curious and intelligent hard worker who’s ready to dedicate all his free time to something he’s passionate about.

“Something to wake up in the morning for, something to be passionate about — is enough for me. A perfect day is the day when I am able to solve a big chunk of a problem at hand and to advance towards the end goal. As long as there is even a little progress, I feel satisfied. I am a curious person. Even the most mundane questions spark the will to research in me, this is what inspires me. I find interest in finding something new, something that no-one has ever done or seen before, and hopefully applying that something to solve a relevant issue. When the goal’s been reached there’s nothing interesting left. You don’t ever want to reach that end unless you can find something new to strive for.”

Pini gives the impression of being an independent scientific figure that can deal with everything on his own, but when the talk turns to career goals and job perspectives, he makes a surprising statement.

“One does need to socialize. One also needs to consult with colleagues, share insights, etc. In my PhD studies I had my own project, but I did have people I could consult with. I do want to work with people who tackle similar or related problems so that we can share insights and advice, better understand the tasks we are given and increase our efficiency. It’s important to work alongside people, not necessarily with them, to be able to do our job better. Two people cannot drive a car simultaneously, but the end goal is to reach the same destination with different cars with everyone pulling their weight.”

Pini believes that intuition comes with knowledge and experience and that to be a good data scientist one also requires creative thinking. Yet there doesn’t seem to be much in the world that couldn’t be explained from Pini’s rational point of view.

“I guess I am analytical because I actually know how the brain works. It removes most of the magic of how we see, think and understand, stultifies us questioning if our decisions have any meaning, or if we have free will at all. Alternatively, this knowledge poses new questions on its own accord, makes me think of how these things actually happen, how they work “under the hood”. We are physical entities in the end, and there is nothing metaphysical that can influence the physical. Even if we feel like we possess free will, there are physical processes that made us do whatever it is that we did. In parallel, we have got this notion that we decided to do something, but it only comes after the process of doing something has already begun. It’s not that there is a thought of initiating something and then the initiation of that something, but rather there’s doing something and the emerging feeling you get from some parallel channel that says “it’s me, I wanted to do it!”. Most people don’t like this way of thinking, though. I still enjoy thinking and believing that I do influence my own decisions. This is what keeps us moving in our day-to-day lives.”

Pini is open for job offers in data science positions. Feel free to reach out to him on his Linkedin.