Post 3 – Interning at Image Insight Inc.

I set out into the summer with what I thought were some fairly broad and undefined learning goals: I wanted to gain experience doing machine learning, and I wanted to experience a professional environment, particularly a software development-oriented one.

Although the remote nature of my internship did not allow me to become as intimately acquainted with office life as I would have liked, I was still able to learn a lot about what day-to-day interactions are like, what working as a team in this kind of setting is like, and, most importantly, about machine learning. Being given the opportunity to push my own boundaries regarding this particular skill was really rewarding, as these are industry skills that will greatly benefit me going forward.

This internship provided clarity in terms of my career interests. I have been interested in software development for a while, and this was the perfect opportunity for me to see how my academic interests would transfer to the real world. I have learned how to interact with both peers and supervisors in a professional setting, which will greatly benefit me in the near future, as I progress along my professional journey.

To a student intern who was interested in obtaining a position with my host organization, I would advise them that even if things seem like they’re moving fast at first, it’s only a matter of time before your level of relative unfamiliarity wears off. Once I figured out my place and role on the team, I was able to quickly move forward with my personal project, which furthered my understanding of what I was supposed to do. 

To someone interested in a computer science internship, I would advise them to keep their head above the water. The field itself moves fast, and changes can be both imperceptible and sudden at the same time. There is enormous demand for computer science jobs and interns, so if you pay attention and are competent, plenty of incredible opportunities will come your way. 

This summer, I’m most proud of the contributions I’ve made at Image Insight. I had hoped to bring new insights and methods of analysis by reinventing their wheels, and I think I’ve done precisely that. One regret I have is that I was not able to fully finish one component of my assignment using machine learning, and had to implement a statistical approach to overcome this roadblock. Yet, by and large, this has been a summer of exploration and of learning. I’m very proud of my learning and contributions, and excited to take this experience with me moving forward.

Me working outside

Post 2 – Interning at Image Insight Inc.

Looking back at the first half of the summer, it’s crazy how fast time seems to fly. It seems like my internship started yesterday and feels like it has only been a week or two since I came home from school in mid-March. Yet, in the span of these few short months, I’ve learned a lot about working.

At first, I had mixed feelings about having a virtual internship. I wondered if it would be possible for me to get all my work done without constant live access to my supervisor. I asked myself if I would really be able to experience what work is like as a software engineer without the actual work environment and the human interactions around me?

As the summer progressed, I found myself answering these questions without the need for physical interaction. Don’t get me wrong. I would prefer the live interaction, but I was able to experience much of the day-to-day interaction of a cohesive team without actually being physically in-person, including large group calls, progress updates, and screen sharing code. Developing technology requires teamwork, and I have begun to learn how to collaborate virtually as a software engineer. Our work ends up being located in the cloud regardless of whether we gather in person or through Zoom.

Halfway through the summer I have also experienced significant differences between the work environment and academic life. At school, professors are generally much more prepared to handle mistakes one might encounter, having anticipated their occurrence and frame of reference. Furthermore, in the classes I’ve taken so far, the path set for us by the professor is also one they have experienced and determined.

In contrast, in the real-world there is no rubric that will give an exact output or desired set of parameters. Multiple times during my internship, when stranded with a foreign error message, I had to go diagnose the root of the problem myself by drudging through thousands of lines of documentation that my supervisor and I had’t written to find the root of a single problem. This is not exactly the work that is the most intriguing and inspiring to do, but it is required to achieve our goals. I have also experienced times during the first few weeks of my internship when problems were not as well defined. Grappling with these more vague problems has been an interesting challenge, and they have taught me to work through ambiguity.

I have built a lot of valuable skills this summer, most importantly a much deeper understanding of machine learning. Although I felt reasonably comfortable going into my summer role, this internship has both pushed me to learn much more and expand my boundaries beyond where I previously felt comfortable. Now, with a much higher level of understanding, I am beginning to see the forest through the trees. This skill will be immensely useful, as machine learning and artificial intelligence are growing fields, and my developing talent and experience will be in very high demand in the near future. 

Post 1 – Interning at Image Insight Inc.

This past fall semester, I took an Intro to Artificial Intelligence course which ignited my interest in AI and machine learning. One particular notion that fascinated me was the idea of how machine learning is an “enabling technology.” Just as the invention of programmable computers replaced the need to make a new circuit – drastically decreasing software development time – machine learning has this same potential to help software engineers do their jobs more efficiently. It was an exciting class, and after it ended I couldn’t wait to get my feet wet in the real-world.
This summer, my internship will give me the opportunity to apply many of the machine learning techniques that I have studied this past year. I’m interning for Image Insight Inc., a company whose mission is to provide low-cost radiation detection to the general public. Radiation is prevalent in many aspects of our lives at various levels, and high levels of radiation are dangerous and hazardous. The technology we’re developing can aid users at a multitude of levels, including the military, first responders, and people who receive radioactive treatments.
While many advancements have been made, there are still some problems that need refining in order for this technology to be utilized at its highest potential. For example, different cameras detect varying levels of radiation, and consistently standardizing what a normal level of background radiation looks like is difficult even between identical cameras.
This summer, I will use a machine learning approach to solve this problem as well as several issues from the nature of radioactive randomness. Solving these problems will allow for smoother transitions from device to device. In 2015, there were reportedly over 24,000 different types of
android phones on the market so it’s not realistic to individually tailor a solution for every single kind of phone on the market. Instead, new approaches and fresh techniques may be just what we need to broaden the scope of this technology to make it more accessible in the market.
This summer, I’m excited to have my first professional experience in a software development and machine learning setting. I hope to make a valuable contribution based on what I’ve learned in class, and see how it applies to Image Insight’s needs. I’m also looking forward to learning how to navigate a professional environment, even if I have to do it over conference call. Originally, the internship was planned to be onsite, and due to COVID-19 I will be working remotely. Luckily, I’ve already met the rest of my team and have begun working with them. I look forward to learning a lot and am very excited about what the rest of the summer has to offer.