How Curiosity Lead’s My Venture into Data in Search of Patterns
My Humble Begining That Started The Journey
I’d like to take you on a journey into why I’ve chosen to dive deeper into the world of data. Imagine a world where every question, every problem, and every discovery is connected by an intricate web of unseen threads. This world is driven by curiosity — a force that has always propelled me forward. My journey began in the realm of physics at Institut Teknologi Bandung, a subject that I embraced with passion and dedication. But as I delved deeper, I discovered that physics was not merely a set of theories and equations; it was a key to unlocking some of the world’s most intriguing and often invisible problems.
You might wonder, “What’s the connection between physics, data, and global issues?” Let me take you on a path where these elements intersect in remarkable ways. As I immersed myself in the study of physics, I encountered a profound realization: the principles and analytical skills honed through physics could be harnessed to tackle real-world challenges. This was not just about abstract concepts but about applying rigorous methods to solve practical problems.
My passion truly ignited when I began working on projects that bridged the gap between theory and practice. I vividly remember the thrill of transforming raw, unstructured data into actionable insights. It was like deciphering a complex code, where every data point was a clue leading to a larger understanding. Whether it was analyzing climate patterns, optimizing industrial processes, or exploring new frontiers in technology, the process of making sense of data became a source of immense satisfaction.
But the journey didn’t stop there. I discovered that data could reveal patterns and connections that were previously hidden from view. It became a powerful tool for not only understanding the present but also predicting future trends and making informed decisions. The ability to translate complex data into meaningful solutions that could make a real impact on society was exhilarating.
This realization fueled my desire to deepen my expertise in data science. I saw data not just as numbers but as a narrative waiting to be uncovered. It was about using data to address pressing issues, whether it was improving public health, advancing sustainability efforts, or driving innovation in technology. The potential to create something valuable and impactful from seemingly disparate pieces of information became my driving force.
So, why data? Because it is the key to uncovering hidden truths, solving critical problems, and driving positive change. It’s a journey that combines my love for physics with a deep-seated curiosity to explore, analyze, and innovate. The pursuit of data science is not just a career path. It’s a passion that enables me to contribute to a better world by transforming raw information into powerful solutions.
How Robotics Increase My Curiosity and View To The World
Then there’s robotics — a chapter in my journey that has been nothing short of transformative. One of the most exhilarating milestones was my involvement with Dagozilla, an experience that has profoundly shaped my path. Being a part of Dagozilla ITB wasn’t just about joining a robotics team; it was about becoming part of a pioneering force in technology and innovation.
Imagine a world where machines are not just tools but collaborators in our daily lives. That’s the world we’re striving to create with Dagozilla. In this realm, I’ve had the incredible opportunity to work on mobile robots that are not only equipped with advanced mechanical systems but also imbued with machine learning algorithms that make them increasingly intelligent. It’s akin to teaching a machine to perceive, understand, and interact with its environment in ways that were once the stuff of science fiction.
Every line of code I write feels like a step toward solving a grand puzzle. It’s a puzzle where each piece — whether it’s a piece of software or hardware — contributes to a greater vision of smarter automation. The thrill of seeing a robot navigate autonomously or respond to its surroundings based on learned patterns is a testament to the incredible potential of robotics. For someone like me, who finds a unique form of expression in communicating with machines rather than people, this is a dream realized.
Dagozilla is more than just a robotics team; it’s a vibrant community where engineering prowess intersects with teamwork and strategic thinking. My journey with Dagozilla has been as much about technical advancement as it has been about personal growth. On the technical side, I delved deep into the nuances of fine-tuning mechanical systems and optimizing algorithms for autonomous navigation. It’s a meticulous process that demands precision and creativity, where each improvement enhances the robot’s capabilities and performance.
But beyond the technical aspects, my role in Dagozilla offered valuable lessons in leadership and collaboration. Working within a diverse team often means navigating the delicate balance between technical aspirations and the non-technical realities of project management. We frequently faced the challenge of aligning our technical goals with the broader objectives of the team. This experience taught me the importance of communication, the art of integrating various perspectives, and the power of cohesive teamwork in achieving success.
The interdisciplinary nature of Dagozilla revealed that innovation is not just about technical skills but also about fostering an environment where different ideas and expertise converge. It’s about creating a synergy where engineering, strategy, and collaboration come together to drive meaningful progress.
In essence, my time with Dagozilla has been a journey of discovery and inspiration. It’s where my passion for robotics and machine learning has found its true expression, and where the lessons learned extend far beyond the realm of technology. It’s a reminder that at the intersection of curiosity, technology, and collaboration lies the potential to shape a future that is both exciting and transformative.
How Projects Increase My Curiosity and Excitement
Beyond robotics and computer vision, my involvement in projects like volcano mapping using drones showed me the powerful ways physics and data science can be combined for research and real-world application. In collaboration with peers from ITB, we explored how aerial data collection could be used to predict and map hazardous volcanic regions. My role in designing and analyzing the data captured by the drones helped me sharpen my understanding of machine learning and data interpretation, solidifying my belief that physics can be a driving force behind technological innovations in disaster mitigation.
But what really fascinates me isn’t just the tech. It’s how data, when combined with physics, can solve complex human problems. I want to refine the tools I already have, data science, machine learning, and use them to answer bigger questions. I want to explore the depths of what’s possible when we combine analytical thinking with raw computational power.
In October 2022, I embarked on a fascinating project that merged two fields I am deeply passionate about: natural language processing (NLP) and machine learning (ML). The goal was to analyze the sentiments of ITB students expressed on the popular @ITBfess Twitter account. This project allowed me to dive into real-world data, uncover hidden patterns in the digital chatter of students, and see firsthand how these technologies can provide insights into public opinion.
The journey began with gathering the vast sea of tweets, most of which were spontaneous, emotional outbursts. Using Python as the foundation, I learned how to preprocess this data, turning raw text into meaningful information through techniques such as tokenization, stemming, and lemmatization. Each step in this process was like unlocking another piece of the puzzle, and I felt the excitement of being able to clean and shape messy data into something ready for analysis.
Through my involvement in various projects, I’ve gained a deeper understanding of this intersection between science and technology, learning not only how to build complex systems but also how to extract meaning from the vast amounts of data they generate. What I hope to gain from this course is more than just technical skills. I want to learn how to ask the right questions, to think critically about data in ways that can lead to breakthroughs in various fields, from geology to robotics to even social sciences. Through countless hours of testing and refining algorithms, I learned how critical precision is in both physics and machine learning. Small changes in parameters can lead to significant shifts in outcomes, a reality that mirrors many physical phenomena. This experience gave me a new perspective on the importance of experimentation and adaptability, as I often had to modify my approach when the initial results didn’t meet expectations. Imagine the power of understanding student sentiments on social media, like the project I did analyzing ITB students’ feelings on @ITBfess, and then applying that same knowledge to improve educational policies or community projects.
In October 2022, I embarked on a fascinating project that merged two fields I am deeply passionate about: natural language processing (NLP) and machine learning (ML). The goal was to analyze the sentiments of ITB students expressed on the popular @ITBfess Twitter account. This project allowed me to dive into real-world data, uncover hidden patterns in the digital chatter of students, and see firsthand how these technologies can provide insights into public opinion.
The journey began with gathering the vast sea of tweets, most of which were spontaneous, emotional outbursts. Using Python as the foundation, I learned how to preprocess this data, turning raw text into meaningful information through techniques such as tokenization, stemming, and lemmatization. Each step in this process was like unlocking another piece of the puzzle, and I felt the excitement of being able to clean and shape messy data into something ready for analysis.
What continues to motivate me is seeing the practical impact of the work I do. Each project shows me that the skills I’ve gained — whether in coding algorithms, designing hardware systems, or analyzing complex datasets — can create solutions that extend beyond the classroom. There’s a deep satisfaction in knowing that the fusion of physics, data science, and robotics can address real-world problems, whether it’s in automating exploration, improving safety measures, or developing technologies that push the boundaries of what we know.
Through these experiences, I’ve realized that what drives me most is the challenge of translating complex, abstract concepts into real-world solutions. The problems I tackle are rarely straightforward, but that’s precisely what makes them exciting. The iterative process of testing, failing, and refining ideas is an ongoing reminder of how learning never stops. Physics has trained me to think critically about the world, while machine learning has given me the tools to model and predict that world in ways I never thought possible.
What I Learned and What I Expect to Learn More
In a way, every project I’ve worked on, from predicting bank churn to analyzing school quotas in Bandung, has shown me that data has stories to tell. And I want to be the one to bring those stories to life, to solve problems that might seem trivial to others but hold immense potential to me. So why this course? It’s the next step in my evolution as a data scientist and physicist. I’m here to sharpen my skills, to become better at seeing the invisible connections, and ultimately, to solve problems that can make the world just a little bit better. And if that means spending more time with my favorite tools and of course, my trusty old laptop, then I’m all in.
Looking forward, my goal is to continue blending these disciplines, pushing the boundaries of what can be achieved through data and technology. I’m motivated by the endless possibilities of this field, knowing that each project, no matter how small, is a step toward understanding — and solving — some of the world’s most complex challenges.
Now, as I dive into the “Pemodelan, Generator Data, dan Analisisnya” course, I see a clear connection between my past work and the skills I aim to develop. This course will enhance my ability to design simple models and generate data, applying these concepts to more complex physical systems. The opportunity to explore both theoretical and practical applications of modeling excites me because it aligns with my long-term goal of leveraging computational techniques to solve real-world physics problems. Through this course, I hope to refine my ability to critically analyze physical systems, not just through abstract models but also by generating and interpreting data that reflect these systems. Moreover, the collaborative aspect of this course will help me grow as an individual and team-based problem solver, skills crucial for any aspiring scientist.
Ultimately, I am eager to apply the principles from this course to continue bridging the gap between theoretical modeling and real-world data analysis, a key skillset for any data scientist or physicist in today’s data-driven world.
