Synthesizers: The Science and History of Technology in Music

 Matthew Hale, Verrazzano Class of 2026, completed a major in Music Technology and a minor in Dramatic Arts

My work with Prof. Carlos Delgado focused on what goes into creating a functioning synthesizer and a sequencer. At the start of this project, Prof. Delgado had me read up on the extensive history of technological innovation in the field of music. Over the course of this study, I gained a better understanding of the steps taken to create what we use in today’s music, from the earliest instances of electricity in music to the technology found in the music of David Bowie and Pink Floyd. Through hands-on work, I learned the different components of a synthesizer. As the building process of the synthesizer went on, the more I learned, starting with the oscillators that create the waveforms, then the filters that carve away at the waveforms to shape your sounds, then the amplifiers that shape the volume throughout the sound,  and finally the Low Frequency Oscillators that shape the sound further with frequencies that are lower than the range of human hearing. The sequencer works hand-in-hand with the synthesizer, creating patterns using a string of notes that sends data to the synthesizer.

I knew I wanted to do my capstone project about music technology. However, I didn’t realize I wanted to focus on synthesizers and sequencers until I started working with Max/MSP in Prof. Isidore Ramkissoon’s class. The following semester, I started Prof. Carlos Delgado’s class, where the area of focus is entirely up to me. He mentioned programming my own synthesizer, and I was hooked immediately. Because I am currently enrolled in my mentor’s class, the workflow was a little unorthodox. I was expecting to need to dedicate time outside my classes to work on this project, but I was able to complete a good majority of it during my class time. Programming the synthesizer definitely had its difficult moments. Specifically, working with many tiny, intricate parts led to several issues that required extensive trial and error to resolve. Remembering what each component does was also a bit tricky, given all the moving parts. One aspect that surprised me, however, was the research on history. I was not expecting to find traces of electronic music dating back to the mid-18th century. Moving on from this project, I would like to further experiment with updating my synthesizer, adding new components, and experimenting with ones already in it. I would also like to delve deeper into early-20th-century innovations because they seemed the most experimental and “out there.” From this experience, I have gained a newfound appreciation for electronic music and a better understanding of the programs I have been working with on my own time.

Resisting Erasure: Queer Women and the Historical Record

Isabella Roseo, Verrazzano Class of 2027, completing major in History (7-12)

I have always loved history, and I am majoring in History Education 7-12, so naturally I gravitated towards researching history. However, I wanted to stray from the "Great Man" view of history that is all too common. It's about time we focus more on women's history and more obscurely queer women's history. I was motivated simply through the knowledge that I was using my platform to bring visibility to a topic that is dear to me and too often overlooked.

This project examines why the lives and relationships of queer women in the nineteenth-century United States and England are so difficult to find in historical records. At first glance, their absence might suggest that such women were rare or invisible in their own time. However, my research argues that queer women did exist in significant ways, and that their apparent absence is the result of how history has been recorded, interpreted, and sometimes deliberately altered.

The main objective of this research is to understand how this invisibility was created. Rather than treating the lack of explicit evidence as proof that queer women were not present, I focused on the social and cultural forces that shaped what was documented. I examined personal letters, diaries, and long-term relationships between women that were recorded but later described as “romantic friendships" instead of being considered potentially queer.

One of the key findings is that nineteenth-century society had strict expectations about gender and sexuality, which made it difficult to openly identify or label same-sex relationships. As a result, many women formed deep emotional and sometimes lifelong partnerships that were socially acceptable, as long as they were framed in non-sexual terms. Historians later reinforced this framing by interpreting these relationships as purely platonic, even when the evidence suggests a more complex emotional or romantic bond.

Another important conclusion is that the erasure of queer women's history was not accidental. Over time, institutions such as publishers, historians, and even families contributed to reshaping the historical record. Letters were sometimes edited before publication, and language that suggested romantic or intimate connections between women was softened or removed. This process limited the evidence available to future historians and helped create the impression that queer women were largely absent from the past.

Language also plays a significant role in this issue. Terms like "lesbian" or "queer" were not widely used in the same way during the nineteenth century, making it difficult to directly identify these relationships using modern categories. This creates a challenge for historians, who must interpret historical evidence without forcing present-day labels onto the past, while still recognizing patterns of same-sex intimacy and connection.

Ultimately, this project concludes that the invisibility of queer women in nineteenth-century history is not due to a lack of existence, but to long-standing processes of reinterpretation, omission, and silence. By revisiting historical sources with a more critical perspective, it is possible to recover aspects of these hidden lives and better understand the diversity of past relationships.

This research is important because it challenges the idea that queer identities did not exist in earlier periods. By uncovering the ways queer women's lives were documented and later obscured, this project contributes to a more accurate and inclusive understanding of history.

I expected a capstone to be very tedious. In reality, at some points, it was very tedious. However, all the hard work and time spent is worth it in the end. For the first time in my college experience I really felt like I was getting the most out of higher education and applying it to something that really mattered.

The most challenging part of the research was having to stay focused during long hours of reading through sources and writing. The easiest part was presenting at the Undergraduate Research Conference. I was surprised by the more administrative aspects of the process. I feel like I have filled out so many forms and emails throughout this experience.

I would like to expand on my research by looking for examples of queer women's history beyond the Western world. My biggest take away from this experience is that research can be very enjoyable, and it certainly generates a feeling of deep academic pride and fulfillment. 

Determining the Feasibility and Environmental Benefits of Implementing PV Systems to the CSI Campus

 

Emilia Turek, Verrazzano Class of 2026, completed a major in Environmental Science

My capstone project analyzed the benefits of implementing solar energy canopies to the CSI campus. I wanted to learn more about renewable energy and how CSI could benefit if it was implemented on campus.

To do this research, I digitized the parking lots of CSI on ArcGIS Pro to get the area of each row of the parking lots and getting the area of each lot. I then calculated the number of panels that could fit on each parking lot row, the cost of implementation, and the energy that could be generated annually.

From this project, I learned that implementing solar energy is a complex and costly process. Although it is beneficial and the costs will be recouped over time, it is important to research the most efficient ways this can be done to best help the environment while also limiting costs. As part of this project, different programs that could aid CSI with this were considered that would help limit costs. I learned that there are different programs that are specific to helping higher education institutions with decreasing their carbon footprint.

 This project can be developed further by considering different sources of renewable energy that can be implemented on the campus, such as wind energy. In addition, other solar energy companies can be researched, or other assumptions can be made to ensure the most efficient method is used. I found a standard size for solar panels and costs per panel to create calculations on the costs of this, the number of panels that could fit in each row, and the amount of energy that could be produced. These calculations were then used to find the recoup time when CSI would eventually get their return on investment. However, other data can be found and utilized to determine the recoup time.

Future work could also find how much funding this project could receive and use this in calculating the recoup time. I have also learned how to digitize on ArcGIS Pro with maximum accuracy. I precisely mapped out each row to the parking lots by hand using a computer mouse to get as accurate data as possible. It is important for this to be done carefully with as little human error as possible. It was challenging to map out the parking lots as accurately as possible. However, it was easy to do the calculations to find the amount of energy that could be produced.

Overall, from this capstone project, I learned about the many ways CSI would benefit from solar energy on campus. I researched initiatives that other institutions are doing to decrease their carbon footprint, and learned more skills when using ArcGIS Pro.

The Effects of Existential Concerns on Subtle Manifestations, Prejudice, and Political Preference

 Raneem Baalbaki, Verrazzano Class of 2026, completed a major in psychology with a minor in critical criminology and social justice

I joined Florette Cohen's lab two years ago because I found her research on Terror Management Theory intriguing. The theory is the idea that when we as humans are reminded about our own mortality, it causes us psychological anxiety leading us to cope with our world views and values.

When deciding what I wanted to research for my honors/capstone project, I knew I wanted to focus on aggression, as I am studying to become a forensic psychologist. I wanted to understand how far people were willing to go to perform aggressive acts under the right conditions, such as a person in power asking them to. Aggression has always interested me because the act itself is a choice and I’ve wanted to understand why some people choose aggression while others don’t. With the help of Dr. Cohen, we were able to create an experiment that tested Terror Management Theory as well as aggression in participants to develop my thesis.

I expected this project to involve hard work and extensive research; however, I never expected to thoroughly enjoy the process and have fun with it. It was definitely challenging at times, but I learned so many valuable skills and discovered how to overcome challenges in research.

My research has many aspects that could be further expanded in the future, such as why Terror Management Theory seems to be losing its effect and why non-voters scored higher on aggression than voters, and I'm excited for the opportunity to expand on these ideas.

One of the main things I took from this experience is that while research is a long and difficult process, I am capable of doing it. Not only am I capable, but I genuinely enjoy it and will continue to love this work.

ReZon: A Context-Aware Personal AI Assistant Desktop Overlay by Ahmad Basyouni

 Ahmad Basyouni, Verrazzano Class of 2026, completed a major in Engineering Science

My capstone is called ReZon, a personal AI assistant that runs as a small see-through window on top of everything else on your screen. The idea is pretty simple. Instead of leaving your work, opening a chat tab, copy-pasting your code or your chart, and asking a question somewhere else, the assistant comes to you. You press one hotkey and it can see what's on your screen, figure out what app you're in, and either give you a quick answer or do something for you.

It has three modes. Trader Mode watches TradingView and warns me when I switch between stocks, reminding me of rules I set for myself, so I don't make impulsive trades. Coding Mode takes a screenshot of whatever code I'm looking at, reads it, and gives me a short summary, a possible bug, and a fix. Productivity Mode can create calendar events, send iMessages, raise GitHub issues, and make Notion tasks, but only after I click an Approve button. It never does anything on its own.

The whole thing runs on my laptop. The language model (Qwen 2.5 7B) is loaded locally through Ollama, so nothing I'm reading, writing, or trading ever leaves my computer. The system boots up with one command in about 11 seconds, and I check it before every demo with a script that runs 33 tests against all three modes.

My main conclusion was that the AI part was almost never what made things hard. Once the model was warmed up, it gave me good answers in under two seconds. What actually broke the system was the surrounding plumbing. A hardcoded calendar name that didn't exist on my Mac. A screenshot that accidentally captured the assistant's own UI. A retry loop that gave up too early after 61 tries. None of those bugs were about intelligence. They were about details. For an assistant that lives on your screen, the smart part is necessary, but the small interface decisions are what make it feel reliable.

I picked this research area because I was annoyed at myself. I'd be paper trading on TradingView and catch myself about to click Buy on something I already told myself I wouldn't trade, just because the button was sitting right there. And while coding I'd tab over to ChatGPT, paste a function, ask a question, then come back and lose my place. Both problems are the same problem. My apps don't know about my plan, so they let me forget about it. I wanted to build the thing I wished existed for me.

I expected the project to mostly be about AI. Picking the right model, prompting it cleverly. It really wasn't. The hard parts were tiny details. Getting an Electron window to actually float above Fullscreen Chrome on Mac took way more research than I expected. Making sure the screenshot didn't capture my own overlay took an entire afternoon of debugging. AppleScript for Calendar and iMessage was simple to write, but macOS permissions fight you the first few times you run it.

What was easier than I expected was the language model itself. Qwen 2.5 7B running locally was fast enough and accurate enough that I never felt limited by it. What surprised me most was how much one tiny fix mattered. I added a hardcoded fast path that fires a guaranteed sub-second toast on every ticker change, totally separate from the slower AI path. That one design choice is probably what kept my live demo from breaking on stage.

If I keep going on this, the next step is Windows support, because every friend I showed it to asked for it. After that I want to add long-term memory using a vector database, so the assistant remembers preferences across months instead of just sessions.

The biggest thing I'm taking away is that building something for yourself first is a really good way to stay motivated for a whole semester. I learned more from debugging this one project than I did in most of my classes.