residentialstudentstory

Antoni Czolgowski

Mariah Alvarado — Fri, 15 May 2026 17:07:08 +0000

Antoni Czolgowski Mariah Alvarado Fri, 05/15/2026 - 11:07

Meet Antoni:

From rural libraries to open-source AI research, Antoni Czolgowski's first year with the Master in Data Science program at the University of Colorado Boulder has been defined by one key phrase: Yes.

While completing his undergraduate degree in Quantitative Methods in Economics and Information Systems from the Warsaw School of Economics, Antoni joined Orange's data engineering team. In 2023, just shortly after ChatGPT launched, Antoni watched an entire organization's relationship with AI transform in real time.

Now at Boulder, his foundation became a launchpad: independent research, a supercomputing allocation, a published R library on CRAN, an ultramarathon and a hackathon win later, he's closing in on a degree that looks a lot like the versatile, technically deep career he set out to build.

You started at Warsaw School of Economics studying economics broadly — what pulled you toward the quantitative and data side of the field?

My interest started during undergrad, when I discovered big data technologies. It was interesting to think ‘how do we extract big data sets?’ but since then, everything has changed so fast. I have experienced the first two years of the AI revolution both as a student, and an employee within the data science field. Especially during my internship with Orange.

ChatGPT was released in November 2022, and when I joined the team in 2023, no one had heard of AI. I experienced the change first-hand when management first learned of AI-use and adapted their approach. I’ve seen a full span of approaches with AI – from limited use in the beginning, to a full adoption by the time I was preparing to leave.

I realized then that being up to date with new technologies, eager and bold, gave me an advantage. And I’m still like that. I’m optimistic about artificial intelligence. I've spent time with OpenClaw, an open-source framework for self-hosting personal AI agents on your own machine, to run that kind of infrastructure end-to-end. Now day-to-day the Claude ecosystem is enough: Claude Code in the terminal and the desktop app cover what I need.

Your research touches on something a lot of people in AI are starting to talk about now: cultural alignment. How did you first get interested in that area, and how did the project take shape?

My research originally began while building my thesis in my undergraduate degree. My research quickly became ambitious and I started working closely with Doctor Magdalena Smyk-Szymanska, who I had previously taken a class from. The work was about using econometric tools to measure real-world social patterns. At Warsaw I came at it from the econometric side. I had the statistical toolkit, and I went looking for problems where it could apply. The biggest shift since then is that I now start from the problem instead. Cultural alignment in LLMs is what I want to measure, and I pull in whatever tools actually fit, including LoRA fine-tuning, distributed inference, and methods I had to learn from scratch. That reframe is honestly the growth I'm most proud of in the past year.

The field of cultural alignment in the AI field is more and more important. I compare three open-source models, Gemma 3 (US), Bielik (Poland), and Qwen 3 (China), against real human responses from the World Values Survey, then apply LoRA fine-tuning to the demographic profiles where the models perform worst. Commercial models like ChatGPT, Gemini, and Claude dominate everyday use, but the open-source ones were a deliberate methodological choice: with access to the weights, you can measure bias and actually try to reduce it. Most of the workflow runs in R through PacketLLM, my own library, published on CRAN.

The idea came from my own experience as an early adopter. Treating LLMs as advisors, I noticed the answers didn't reflect the cultural context I was operating in, even after the model had collected a lot of information about me. So the questions followed naturally: do model creators implant their own worldview into the model? Is it the training data, or the lack of diversity in it? And which demographic groups do models understand the least?

So your research was already in motion before you arrived at Boulder. How did you find a way to continue it within the professional MS-DS program structure, where research is not traditionally required?

I reached out to one of my professors about my desire to continue my research, and was led to independent research. It was very natural. Independent Study at CU is essentially a one-on-one research arrangement: you pair with a faculty advisor, define a research question, and the work counts as graduate credit.

For me, this meant I could build my cultural alignment research directly into the MS-DS curriculum, which made it financially feasible to pursue in depth and spread the workload more evenly across the program.

I’m pleased to say the arrangement ultimately produced a paper accepted at OSSConf 2026 in Žilina, where I’ll be presenting my work!

You gained access to CU Boulder's Alpine supercomputing cluster through your independent study. For students who don't know that resource exists — what has it actually made possible for your work?

If you google, you can find many CU Boulder supercomputing opportunities, like Alpine. My basic access didn’t really provide much support, but having the independent study as an official course helped me gain access to more in-depth research support.

I can store my models on the supercomputer and run queries in parallel, resulting in faster outcomes. My queries can also run for 24 hours, compared to the one hour provided under the basic CU Student access.

I believe more MS-DS students could take advantage of Alpine, as it could allow them to complete in-depth review more quickly while also building their working knowledge of supercomputing.

That’s great to hear. Are there any more resources at CU Boulder that have shaped your work in ways you didn't anticipate when you arrived?

Yes! Before the school year started, our academic advisor Mariah sent us an email for an Interactive Case Competition. I organized a group of my classmates to compete in a competition to assess the needs of underrepresented communities as it regards broadband coverage, resulting in potential strategies to create additional access.

We became friends as we worked together, attempting to solve real problems with data, but for people. We currently have the best tools in human history at our disposal, and I believe with them we can make a real impact. I’ve always believed that my role as a data scientist can have a societal impact, but this competition further cemented that belief.

Our first semester’s courses proved useful -- especially our statistics and data structures courses. With that knowledge, we created comprehensive modeling using online public data to understand what drives the broadband coverage and where underrepresented communities reside in Colorado. We met with local broadband providers within Park County to understand their specific broadband constraints. We talked to community members in their local grocery stores and libraries, which also happen to operate as local community centers.

By collaborating with public libraries across underrepresented communities, computers could be equipped with tools to further community tool access and computer literacy. And as community members become more familiar with digital tools, they’re more likely to voice desires to gain their own broadband connections.

This all happened in the first semester. I was thinking, “Do I have time for this?” But I chose to say yes. I competed with the best schools across the US. I met some of my best friends. We even won a small award. It taught me not to say no. And it’s something I’ll bring with me even if I decide to pursue my PhD.

How have you gotten involved in the broader data science community at CU Boulder?

I've gotten involved through various competitions, like the Spectrum Broadband Interactive Case Competition, but also through the Data Science Student Association (DaSSA) and the startup scene on campus through Startups2�鶹��Ժ.

For the DaSSA hackathon this year, I reached out to a fellow student who'd presented strong work, asking if he wanted to team up. We invited some friends, built a team, and won. Our solution tackled advertising niche products on Reddit.

Startups2�鶹��Ժ has been just as formative. One conversation there turned into a data scientist offer at a Denver-area startup for summer 2026. I never sent a CV. Between the labs, the student associations, and the startup events, you could be at a DS-adjacent event every week here.

It sounds like year one has been a whirlwind! What does year two look like for you, Antoni?

Thanks to this masters degree, I feel strong on the technical side. I feel I can do a lot of things at once, especially with the help of AI agents, and now I’m eager to explore the hardware side.

This master’s program allows me to request electives that directly align with my own career goals, so I've requested an elective in robotics. The bigger goal is to grow into a versatile tech entrepreneur: someone who can always match the right tools to the idea in front of him. I feel strong on the software side. I want to feel the same way about hardware, and robotics is the first gap I'm closing.

Is there any advice you would give to someone who is where you were two years ago?

My advice would be to speak. Treat your two years as the only chance in your life to be in such a nice environment. Even if it doesn’t work out, asking is better than regretting. Everyone has ideas – but without communicating them, you can’t realize them.

Say yes. And more than saying yes, create the opportunity for yourself when you need to. Make your connection. The tools will show up.

When asked what drew Antoni to Boulder specifically, his answer was simple. The Denver International Airport (DIA). Having such straightforward navigation to his home country eventually sealed the deal. But airports don't write 60-page papers or hold a 4.0 – and that's what his first year here has actually been. He’s been dedicated to the professional masters grind, but isn’t afraid to be active in the local hiking and ultramarathon communities.

"The Pro Program made the academic grind possible. The Boulder environment made the first ultramarathon possible."

From the MS-DS program at CU Boulder, we hope to see Antoni summiting more mountains, breaking new personal marathon records, and advancing additional data science research in the years to come.

Are you an MS-DS student? Email datascience@colorado.edu for a special student resource created specifically by Antoni and learn how to take advantage of CU Boulder's Alpine Supercomputer resource.

Meet Antoni: a second-year MS in Data Science student at CU Boulder, originally from Poland. His work spans AI cultural alignment research, open-source tooling, and community-driven data projects. He is a published R library author, OSSConf 2026 presenter, and DaSSA hackathon winner.

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Yashwant Gandham

Nikitha Konanki Rajeswara Rao — Tue, 28 Apr 2026 16:41:09 +0000

Yashwant Gandham Nikitha Konank… Tue, 04/28/2026 - 10:41

Meet Yashwant:

Before joining the MS in Data Science program at University of Colorado Boulder, Yashwant followed an exploratory path shaped by a background in Electrical Engineering, early research lab experience, and even securing a role in the tech industry—only to realize that a traditional 9-to-5 in electronics wasn’t the right fit.

Instead, they were led to Data Science as a flexible, high-impact skill set for decision-making and innovation. Drawn to CU Boulder’s unique combination of strong academics, hands-on opportunities, and entrepreneurial ecosystem, they’ve since taken full advantage of the program—working across research labs, engaging with startup initiatives, and now serving as a Founding Engineer at a pre-revenue AI startup in the entertainment space—demonstrating how the MS-DS experience can empower students to explore broadly, build technical depth, and translate that into real-world outcomes.

Could you tell us about your educational and work experience background before you enrolled in this program?

Before I joined this program, I wasn’t particularly interested in the traditional 9-to-5 job. Instead, I was eager to explore various opportunities. For instance, I worked at a research lab to gain insights into the research world. Interestingly, I even interviewed for positions at major tech companies. Surprisingly, I secured a job, but I realized that electronics wasn’t my passion. I had only accepted the interview because I had spent four years studying Electrical Engineering. While I understand that a short period of time may not provide a comprehensive understanding of a field’s impact, I believed that trying different things quickly was the best approach. That’s exactly what I did until I realized that I should explore different areas of interest.

What initially drew you to this program?

To be honest, I was a bit uncertain when I chose Data Science. I was at a stage where I was trying different things in my life, and Data Science seemed like something that could significantly impact decision-making. So, I decided to pursue this course. A major factor in my decision to come to CU’s Data Science program was the university’s architecture. Education quality is important, but for me, I wanted to study in a well-designed university, and CU felt like the place where I wanted to be.

What are your favorite parts of the program?

My favorite part is the numerous opportunities I’ve had to explore and work on. I’ve worked in multiple research labs, and over the summer, I collaborated with CU startup initiatives to launch my own startup. I’ve met some incredible people and professors who have all helped me reach the point where I can’t thank them enough. Now, I’m a Founding Engineer at a pre-revenue startup, and I’m working hard to make it a success. All of this wouldn’t have been possible without the exposure to excellent courses, professors, and CU resources.

What do you hope to do with your MS-DS degree? Would you recommend this program to others? Why or why not?

Well, I would like to use it to demonstrate my credibility for upcoming journeys. Who knows, I might return to CU sometime later to pursue a PhD. It’s not something I’m planning to do anytime soon, but it’s something I would really want to do.

Of course, I enjoy the course. I would highly recommend the University of Colorado in general. I genuinely love my university and all the opportunities I’ve explored. There’s still much more to discover; if only I had more time.

What do you wish you’d known before starting the MS-DS, and what's one tip you have for students who are starting this program?

I wish I had known my career path before embarking on my MSDS journey. Throughout my time at CU, I’ve discovered my passions and interests, although they don’t entirely align with data science. However, I’ve managed to incorporate the data science skills I’ve acquired into my daily responsibilities.

I would say be grateful. Don’t just take help from others; also return it to those in need. This is very important in today’s highly competitive world. Without helping each other, no one can reach their desired goals.

Is there a specific project you have worked on that stands out to you?

Yes, I’m actively working on my startup, which is an AI infrastructure company in the entertainment industry. We’ve made significant progress and are almost ready to secure funding and officially launch. The work I’ve been doing on this is incredibly important to me. I dream about it, think about it while eating, playing, and even while sleeping, because I’ve been working on it for a very long time now.

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Mrunal Bhosale

Nikitha Konanki Rajeswara Rao — Tue, 31 Mar 2026 16:55:31 +0000

Mrunal Bhosale Nikitha Konank… Tue, 03/31/2026 - 10:55

Meet Mrunal:

With a foundation in Mechanical Engineering and professional experience as a Data & Business Analyst, plus hands-on work with the Automotive Research Association of India, Mrunal entered the MS in Data Science program at University of Colorado Boulder to deepen their ability to turn complex, noisy data into meaningful insights.

Drawn by the program’s intersection of statistics, machine learning, and emerging agentic AI, they’ve expanded a core strength in pattern recognition into a versatile, cross-industry skill set—applicable from healthcare to automotive—highlighting how CU Boulder’s MS-DS equips students from diverse backgrounds to build impactful, data-driven careers.

Can you tell us about your educational and work experience background before you enrolled in this program?

I’ve completed my undergrad in Mechanical Engineering as well as worked as a Data & Business Analyst for a year before I enrolled for this program. I’ve also collaborated on multiple projects at an internship at ARAI (Automotive Research Association of India).

What made you want to study Data Science at CU?

The cross path of statistics + machine engineering and the chance to study emerging agentic AI in depth drew me to this program.

One of my strengths has always been to notice patterns and shape noisy stories into something meaningful.

This program elevates that exact strength.

What do you wish you’d known before starting the MS-DS? What do you wish you’d known before starting the MS-DS?

I wish I’d known how versatile the knowledge of this program is. It can be applied in all fields right from healthcare to automotive!

Would you recommend this program to others? Any tips for anyone starting out?

Yes! I’d definitely recommend this program to the others. Data science is an emerging and ever growing field. The importance of this field in each sector is extremely valuable.

Data science is one of a kind program where, no matter which study background you come from, it’ll help you analyse and work towards a unique blend of your past experiences and applied knowledge that you love!

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Dnyanada Bhosale

Nikitha Konanki Rajeswara Rao — Tue, 27 Jan 2026 17:44:03 +0000

Dnyanada Bhosale Nikitha Konank… Tue, 01/27/2026 - 10:44

Hi Dnyanada! Thanks for sharing your story. What was your educational and work experience background before you enrolled in the MS-DS program?

Hello! I'm Dnyanada Bhosale, a passionate and driven first-year Master of Science in Data Science (MS DS) student at the University of Colorado Boulder. I proudly serve as the Marketing Chair for the Data Science Student Association (DaSSA) at CU Boulder. I completed my undergraduate studies in Electronics and Telecommunications engineering. I was working on a Generative Adversarial Networks project [before joining].

How are you involved now in the MS-DS program?

I proudly serve as the Marketing Chair for the Data Science Student Association (DaSSA) at CU Boulder. One thing I love about DaSSA is that it makes sure MS-DS students get opportunities for professional development while making it fun and enjoyable. The events conducted by DaSSA are very good.

Very cool! what initially drew you to this program?

My academic journey is focused on mastering the tools and techniques of data science, with a keen interest in specializing in data analytics. I'm dedicated to leveraging data-driven insights to solve real-world problems, particularly within the fast-evolving tech landscape. MS-DS has a blend of faculty from Computer Science, Applied Science, Statistics, and Information Science. It closely aligns with the job role I would want to pursue in future. [The] curriculum offers a balance between academics and real life applications.

Would you recommend this program to others? What tips would you give to someone applying to the program?

Yes , definitely! The residential program provides many career opportunities and jobs for students. I would advise them to be confident and invest their time in pursuing master's at CU!

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Sai Nandini Tata

Nikitha Konanki Rajeswara Rao — Tue, 27 Jan 2026 16:59:46 +0000

Sai Nandini Tata Nikitha Konank… Tue, 01/27/2026 - 09:59

Thanks for interviewing with us, Sai! Can you tell us about your educational and work experience background before you enrolled in this program?

I have a bachelor’s degree in Electronics, but during the lockdown, I explored my interest in Machine Learning. I worked on several side projects, did a few remote internships, and that experience made me want to study this field further and understand the math behind it.

What initially drew you to this program?

When I was exploring different universities, CU Boulder’s curriculum stood out to me. One morning, I looked at the faculty list and noticed that Professors James Martin and Ramin Ayanzadeh were part of the program. That really inspired me. I wanted to be part of the same university as them. It felt like the right place to learn and grow.

Every Masters degree is a little different. How does the MS-DS program fit into your life?

The MS-DS program fits perfectly because it starts with the basics and then dives into the important topics needed in data science. It helped me brush up on my fundamentals while also teaching me how to understand what goes on behind the algorithms.

What are your favorite parts of the program?

Definitely the people and the projects! I’ve really enjoyed working with my peers, brainstorming ideas, and building things together. The campus is also beautiful, which makes the whole experience even better.

Is there anything you wish you’d known before starting the MS-DS?

I wish I had figured out time management a little earlier. It took me about a semester to get back into the rhythm of university life, but once I did, things started flowing smoothly.

What do you hope to do with your MS-DS degree?

I hope to apply the skills I’ve learned to meaningful projects and build strong connections through the CU community. This program is helping me lay the foundation for a great career in data science.

Would you recommend this program to others? Why or why not?

Of course! I absolutely loved it and would encourage more people to join and become part of the CU Data Buffs community. It’s an amazing place to learn and grow.

Thanks, Sai! Lastly, what’s one tip you have for students who are starting this program?

Have fun! Take part in events, network with others, learn from people around you, and pay attention in class. Trust me, half your work will already be done.

Interested in starting your own journey? Explore the Residential Masters in Data Science.

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Kalp Mukund Mepani

Arushi Jha — Tue, 27 May 2025 17:47:42 +0000

Kalp Mukund Mepani Arushi Jha Tue, 05/27/2025 - 11:47

Can you tell us about your educational and work experience background before you enrolled in this program?

Before this program, I completed my bachelors in the field of Computer Science and Engineering and was part of a research internship at SUNY Binghamton followed by a corporate internship at State Street Corporation in the field of Artificial Intelligence

What initially drew you to this program?

My interest in Data Science grew mainly in 3rd year of my bachelors degree where I got to know how you can use machines to make them intelligent and predict our future and it would always excite me. The program outline along with the campus beauty was something that literally dragged me to CU Boulder!

Can you tell us how the MS-DS program fits into your life?

It fits perfectly! As I mentioned DS is something I want to pursue in my career and a lot of new opportunities are now open, now that I have successfully completed my Masters in Data Science. I feel that I am doing something which interests me, which excites me and so this masters fit perfectly with it. Along the way, I have also encountered a rollercoaster of experiences, facing moments of challenge and difficulty that have tested my resilience. However, these moments have taught me invaluable life lessons, pushing me to come back stronger and more determined than ever before.

What are your favorite parts of the program?

Met amazing people and worked on amazing projects such as finetuning our own LLM, using some of the awesome AI techniques and knowing more about AI in detail. The program also helped me create some useful projects and added some useful experiences and I got to know more about what I want to do after my masters, particularly in DS.

What do you hope to do with your MS-DS degree?

I want to explore more in the field of GenAI and LLMs and want to professionally contribute in this field. So, I want to use my degree along with the skills and knowledge that I have gained in the past years towards that. Additionally, I also want to use my data science skills in order to contribute towards the World where I can use the data to depict a meaningful story!

Would you recommend this program to others? Why or why not?

Yes, I would definitely recommend this program. I believe it will be like a rollercoaster, where you will be at your lowest and your highest and it will teach you a lot of things apart from some real life experiences in the field of Data Science

What is one tip you have for students who are starting this program?

Try gaining more experiences under your faculty and if possible working on real-World issues into your projects. Lastly, just make sure to enjoy every bit of this program, while you can!

Is there a specific project you have worked on that stands out to you?

I feel fine tuning our own LLM that I did with my team is something unique and was really interesting. Along with that working on extracting sentiments and emotions using audio and video as well as working and designing analysis for animal shelters was something I think shaped me in a better way.

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