Before I arrived, the UAE existed in my mind mostly as an image constructed by headlines and other people's accounts. I had opinions about it without having earned them. Going to NYU Abu Dhabi was, in part, an attempt to correct that. I wanted to be somewhere unfamiliar enough that I couldn't rely on what I thought I already knew.
What I didn't expect was how much that unfamiliarity would teach me about myself. When severe flooding hit the region, I found myself joining local relief efforts, and I remember feeling the weight of something I had only ever read about before. Climate change stopped being an abstract concern and became something I could see and respond to. The smaller adjustments of daily life abroad, navigating transit, handling bureaucracy in a foreign system, building a routine from scratch, added up in ways I'm still making sense of.
The friendships I formed there are some of the most meaningful I have. Living alongside people from so many different backgrounds shifted something in how I understand my own. I came back viewing my home country differently, not worse or better, just more clearly, the way you see a room differently after spending time outside of it.
My summer in Vietnam changed the way I think about sustainability and the kind of work it requires. At VinUni, I collaborated with Vietnamese students on a Digital Twin project focused on Hanoi’s urban infrastructure, where we built agent-based simulations to better understand traffic congestion, pollution, and energy efficiency. What began as a technical project quickly became something more grounded. The work was strongest when it reflected local perspective, not just the logic of the model.
Just as meaningful was the experience of working across cultural and language differences. There were moments when communication was difficult, and we had to rely on Google Translate, gestures, and visual demonstrations to move forward. Rather than making the collaboration weaker, those challenges made it more intentional. They taught me patience, adaptability, and the importance of meeting people halfway. I left Vietnam with a deeper appreciation for community-driven solutions and a clearer understanding that global sustainability efforts are only meaningful when they are shaped by the people most connected to them.
During my J-term in South Korea, I studied sustainability-first development and saw firsthand how culture, innovation, and community shape the country’s approach to progress. The program combined academic lessons with experiential learning, allowing me to connect big-picture sustainability concepts with real-world examples.
One highlight was meeting with the president of Dong Wha, where we learned about the creation of Whal Myung Su, a traditional drink rooted in wellness and cultural heritage. What stood out most was the company’s philanthropic mission, showing how business can prioritize giving back to the community while preserving tradition. We also visited incubator companies, where I learned about their unique missions, organizational structures, and the ways they foster collaborative work environments and strong communities.
Beyond these visits, I immersed myself in South Korea’s culture exploring vibrant neighborhoods of Seoul, sharing meals, and engaging with peers. This balance of academic exploration and cultural immersion gave me a broader perspective on sustainability, teaching me that meaningful progress depends not only on technical solutions but also on the values and relationships that guide them.
My experience at Stage Zero showed me a different side of engineering, one centered less on physical systems and more on the challenge of making information usable. As a Data Engineering Intern, I worked on building and improving data pipelines that could support the company’s broader mission of helping medical device leaders make faster, more informed decisions. The work required me to think carefully about how raw data is collected, cleaned, structured, and transformed before it can actually be useful.
What stayed with me most was how much impact exists in the work that happens behind the scenes. A strong model or product depends on the quality of the data beneath it, and I began to see data engineering as a form of infrastructure in its own right. My role pushed me to think about scale, organization, and reliability, but also about the purpose behind the system. In a space connected to medical devices and healthcare innovation, even technical decisions about pipelines and preprocessing carried a larger weight.
The experience also helped me grow more comfortable working through ambiguity. Much of the work involved figuring out how to handle new sources of information, how to make processes more efficient, and how to build something that others could rely on. I left Stage Zero with a stronger appreciation for the role data plays in shaping innovation and a clearer sense of how engineering, even when it is not immediately visible, can still contribute to meaningful progress.
My summer at Kinkisharyo gave me a much clearer sense of what engineering looks like when it is tied to systems people rely on every day. Working as a Field Engineer Intern on NJ Transit’s Hudson–Bergen Line, I helped diagnose propulsion, braking, power, and communications failures across more than fifty light-rail vehicles. Being that close to the operational side of transit made the work feel immediate. Problems were not abstract anymore. They affected reliability, service, and the daily movement of people across the line.
One of the most meaningful parts of the experience was learning how much good engineering depends on both technical skill and clear communication. Alongside troubleshooting active vehicle issues, I analyzed and mapped an obsolete electronic control system and turned that work into a step-by-step troubleshooting guide for technicians. That process showed me that engineering is not only about solving the problem in front of you, but also about leaving behind something useful for the next person. Preserving knowledge became just as important as applying it.
The internship gave me a deeper appreciation for the responsibility that comes with infrastructure work. Transit systems often fade into the background of daily life, but being part of the effort to keep them running made me see how much care and precision they require. I left Kinkisharyo with a stronger respect for field engineering and a better understanding of how technical problem-solving can have a direct and lasting impact on a community.
The KATIB project focused on understanding how assistive feedback could shape the way people learn handwriting. Using a handwriting platform with magnetic and visual guidance through an XY-stage and touchscreen, the goal was to compare how participants performed when they were being guided versus when they had to rely more on memory. At its core, the project was about learning, motor control, and how assistive systems can better support people through that process.
My role was leading and designing the EEG experiments for 50 participants. I also built the framework used to analyze handwriting accuracy by normalizing and interpolating the trajectories across the different feedback conditions. What I contributed was both the structure of the experiment and the analysis behind it, helping turn participant responses into something measurable and meaningful.
The Mental Health and Vibrations project explored whether a wearable tactile vest could help reduce short-term anxiety. The system combined vibration-based feedback with PPG and GSR sensors so we could study both the experience itself and the body’s physiological response. The project was centered on the idea that wearable technology could support mental well-being in a way that felt noninvasive and practical.
My contribution was helping integrate the tactile vest with the sensors, running the human-subject testing, and analyzing the results. Through that process, I helped show evidence that the system could reduce short-term anxiety. I also co-authored the conference paper that came out of the work, which made the experience feel even more meaningful because it showed that the project had value beyond the lab.
The neural decoding project focused on improving the preprocessing of noisy medical audio so it could be used more effectively for downstream analysis and communication-related research. The larger goal was to make these signals more usable, especially in contexts where traditional speech systems fall short. It sat at the intersection of signal processing, machine learning, and accessibility, which is a space that already meant a lot to me.
My role was developing a preprocessing pipeline that cleaned the audio data by automating voice activity detection, speaker identification, and transcription. A big part of my contribution was making the data more reliable before it ever reached the next stage of analysis. That experience showed me how much impact can come from improving the foundation of a system, especially when the broader purpose is tied to communication and giving people more ways to be heard.
Sixth Sense is an assistive technology project focused on helping visually impaired individuals better understand and navigate their surroundings. The system uses cameras, gesture recognition, object detection, OCR, and audio feedback to turn visual information into something more accessible in real time. What made the project especially meaningful was that it was trying to function in real environments, not just controlled ones.
My contribution was working on the computer vision and interaction side of the system, especially around gesture-based triggering, OCR, object detection, and audio feedback. I helped build toward a system that could identify surroundings and communicate useful information back to the user in a way that felt practical and immediate. What I liked most about the project was that it brought together a lot of different technical pieces, but always in service of a very human goal: helping someone move through the world with more independence.
At the NYU Tandon hAQathon, I took on a lead role in developing Quasar, a Quantum Convolutional Neural Network designed to classify recyclables into five categories. Working with my team, I used quantum computing, Python, Pennylane, and TensorFlow to explore how quantum machine learning could be applied to a real sustainability problem. What drew me to the project was not just the technical challenge, but the chance to work at the edge of something new while still keeping it tied to a practical goal.
What made the experience meaningful was seeing that the project was not only interesting in theory. When we compared our QCNN to a classical CNN under the same parameters, we saw improvements in accuracy, training time, testing time, and model size. That made the work feel bigger than a competition project. It showed me how emerging technologies can be used in ways that are both innovative and grounded, especially when they are aimed at problems like sustainability and resource use.
At NYU Hack Dibner, I led Team AKPN in designing a tool that could attach to library chairs and use vibrating sensors to remind students to stand up, stretch, and take breaks during long study sessions. The project came from a simple observation: students often stay seated for hours at a time, even when they know it is not good for them. We wanted to create something small and practical that could gently interrupt that pattern and encourage healthier habits.
What I liked about the project was that it focused on a problem people often overlook because it feels so normal. Long hours of sitting, fatigue, and burnout are built into student life in ways that are easy to accept without questioning. This tool was our attempt to make well-being part of the study environment itself. Leading the project taught me a lot about building around everyday behavior and showed me that even simple engineering ideas can have real value when they respond to how people actually live and work.
ChironVR was built around a question that felt both technical and bigger than the hardware itself: if haptic feedback matters in surgical training, how much of that value can still be preserved when cost is treated as a real design constraint. Most high-fidelity haptic systems are expensive enough that many training programs cannot realistically access them, which means the issue is not only about performance, but about who gets the opportunity to train with touch at all. The goal of the project was to design a low-cost VR haptic glove that could still create meaningful tactile feedback, even if it did not match the fidelity of commercial systems.
What made the project meaningful to me was that it turned affordability into the center of the engineering problem rather than something to think about afterward. Using consumer-grade components, servo-driven force feedback, potentiometers, and an ESP32, we built and refined the glove through multiple prototype iterations, always returning to the same question of whether the feedback was coherent enough to actually change the training experience. In the end, the project showed that lower-cost design does not have to mean no value. Even under strong cost limits, the glove was able to preserve enough haptic feedback to make interaction feel more grounded and deliberate, which is what made the work feel important beyond the device itself.