MINERVA VOICES

Alumna Highlight: Rita Kurban

Introducing Rita Kurban, a Minerva graduate from the Class of 2020.
July 21, 2023

Can you describe the graduate program you are pursuing now?

I am currently pursuing a Master in Artificial Intelligence and Healthcare at University College London. I found out about the program last April and it was a really good fit because I have always been interested in biology. This is the first time they are running it, which is in some sense similar to Minerva, where I was part of Class of 2020, which was the second graduating class.

What is a big question, academically, that you are thinking a lot about in your studies and your research?

I am generating a synthetic version of a dataset for a healthcare company. They have a user base of 150,000 people who log their daily activity to the app to calculate their biological age acceleration, or how fast they are aging, and identify actions to prevent it. The goal is to share this data with other companies to boost healthcare research. However, sharing sensitive user information violates user privacy agreements. To address this issue, we want to generate a synthetic version of the dataset with a similar distribution while protecting user privacy. There is a tradeoff between user privacy and dataset accuracy that I need to address. The users' daily activity logging generates a time-series dataset. We not only need to measure the similarity between the distributions, but also consider the time component and how causal relationships evolve over time. For example, how walking 1000 steps today affects health a year later. This is an area of recent research, and I want to apply it to real-life datasets to evaluate its effectiveness and improve it further.

What part of your Minerva experience most significantly informed your current perspective on the world and the way you approach studying now?

If not for Minerva, I would not be in the field of machine learning or data science. Minerva was a formative experience for me—it helped me find who I am, who I want to be, what my dreams and goals are. It also equipped me with tools to contribute to biology and healthcare without being a medical doctor. I studied pharmacy for two years in Belarus, but I realized that face-to-face interaction with patients was not for me. Back home they say, only specific types of people become doctors because it is a lot of responsibility, and sometimes you need to be less sensitive. Minerva helped me find the right tools to fulfill my goals without pursuing the traditional route of becoming a doctor.

What are some learnings from your Minerva classes that you find yourself applying to your life or studies now?

I never expected it to happen, but I find myself thinking about Habits of Mind and Foundational Concepts (HCs) when I write reports or have conversations. For example, I might think about #SystemDynamics. These concepts are applicable to different areas of my life, especially when I want to persuade someone or impress people at a dinner party. I use these concepts often, and they are everywhere. It is funny because when I met some of my Minerva friends recently, we all said the same thing and laughed. We thought we would never use HCs after graduation, but in reality, our lives are just using these foundational concepts.

Minerva also prepared me in terms of more practical knowledge, like using several coding libraries, like PyTorch. I feel like I am better prepared than many people in my program. Many people come from multiple backgrounds, and usually these are people with some interest in biology. However, they do need to have computer science background. During my interview preparation, I was scared at first, but actually, I will say that I feel much more prepared than many other people from prestigious schools.

How does your Minerva education make you uniquely prepared for post-graduate life?

In terms of computer science preparation, there was not much focus on theoretical components like math, programming, or computer hardware at Minerva. However, by the time I graduated, I had worked on a wide range of projects through various internships, such as a bioinformatics lab in Korea, T-hub in India, and predicting deforestation in Argentina using satellite imagery. I had many projects in different circumstances and environments. Working in India is not the same as working in Argentina, South Korea, or Mexico. These experiences prepared me to work with different types of people and understand how teams work. Many of my friends from traditional schools probably only had one internship in a classical company with 15 other people. It is different to understand how to work as a real data scientist. By the time I graduated, I felt well-prepared.

Can you talk me through your Capstone project? In what ways do you think your Capstone work informs what you are doing now.

My Capstone project was focused on early breast cancer detection. I analyzed a dataset and predicted the likelihood of a female developing cancer in the coming years, focusing on prevention rather than cure. This approach has numerous benefits, including better prognosis, improved patient well-being, and reduced healthcare spending. Right now, I am doing something pretty similar in a sense that I have this healthcare data set, and I have a goal of how we can make use of it or make it better. I learned many of these tools and techniques at Minerva. I had one very nice tutorial on deep learning at Minerva, which got me into Artificial Intelligence. My experiences now are a direct result of what I was doing a few years ago at Minerva.

How did relationships with your Minerva professors help you to get into this program?

First of all, I want to thank Ben Nelson, because he actually referred me to my first job. And that is how I gained more experience.

Additionally, I received two reference letters from Professor Ribeiro and Professor Gahl. Professor Ribeiro is always excited to answer career-related questions or help write recommendation letters for me when I decided to pursue a Ph.D. program. She was very supportive toward me and is genuinely a caring person. I was very lucky to be in her Capstone class. Professor Gahl is from the Natural Sciences College, which was a nice combination of expertise to complement my computer sciences background. During my work-study with her, we worked on ecology projects where I contributed as a data analyst and created visualizations for papers. This experience introduced me to research, and Professor Gahl has been a great support, always available for calls and advice.

If you were inspired by Rita's story and are seeking a college experience that will teach you valuable pragmatic skills that will enable you to change the world, apply to join Minerva today.

Quick Facts

Name
Rita Kurban
Country
Belarus
Class
2020
Major
Computational Sciences & Social Sciences
Computer Science & Arts and Humanities
Business and Computational Sciences
Business and Social Sciences
Arts and Humanities
Business, Social Sciences
Business & Arts and Humanities
Computational Sciences
Natural Sciences, Computer Science
Computational Sciences
Arts & Humanities
Computational Sciences, Social Sciences
Computational Sciences
Computational Sciences
Natural Sciences, Social Sciences
Social Sciences, Natural Sciences
Data Science, Statistics
Computational Sciences
Business
Computational Sciences, Data Science
Social Sciences
Natural Sciences
Business, Natural Sciences
Business, Social Sciences
Computational Sciences
Arts & Humanities, Social Sciences
Social Sciences
Computational Sciences, Natural Sciences
Natural Sciences
Computational Sciences, Social Sciences
Business, Social Sciences
Computational Sciences
Natural Sciences, Social Sciences
Social Sciences
Arts & Humanities, Social Sciences
Arts & Humanities, Social Science
Social Sciences, Business
Arts & Humanities
Computational Sciences, Social Science
Natural Sciences, Computer Science
Computational Science, Statistic Natural Sciences
Business & Social Sciences
Computational Science, Social Sciences
Social Sciences and Business
Business
Arts and Humanities
Computational Sciences
Social Sciences
Social Sciences and Computational Sciences
Social Sciences & Computational Sciences
Social Sciences & Arts and Humanities
Computational Science
Minor
Computational Science & Business
Economics
Social Sciences
Concentration
Data Science & Economics
Machine Learning
Cells, Organisms, Data Science, Statistics
Arts & Literature and Historical Forces
Artificial Intelligence & Computer Science
Cells and Organisms, Mind and Emotion
Economics, Physics
Managing Operational Complexity and Strategic Finance
Global Development Studies and Brain, Cognition, and Behavior
Scalable Growth, Designing Societies
Business
Drug Discovery Research, Designing and Implementing Policies
Historical Forces, Cognition, Brain, and Behavior
Artificial Intelligence, Psychology
Designing Solutions, Data Science and Statistics
Data Science and Statistic, Theoretical Foundations of Natural Science
Strategic Finance, Politics, Government, and Society
Data Analysis, Cognition
Brand Management
Data Science and Statistics & Economics
Cognitive Science & Economics
Data Science and Statistics and Contemporary Knowledge Discovery
Internship
Higia Technologies
Project Development and Marketing Analyst Intern at VIVITA, a Mistletoe company
Business Development Intern, DoSomething.org
Business Analyst, Clean Energy Associates (CEA)

Conversation

Can you describe the graduate program you are pursuing now?

I am currently pursuing a Master in Artificial Intelligence and Healthcare at University College London. I found out about the program last April and it was a really good fit because I have always been interested in biology. This is the first time they are running it, which is in some sense similar to Minerva, where I was part of Class of 2020, which was the second graduating class.

What is a big question, academically, that you are thinking a lot about in your studies and your research?

I am generating a synthetic version of a dataset for a healthcare company. They have a user base of 150,000 people who log their daily activity to the app to calculate their biological age acceleration, or how fast they are aging, and identify actions to prevent it. The goal is to share this data with other companies to boost healthcare research. However, sharing sensitive user information violates user privacy agreements. To address this issue, we want to generate a synthetic version of the dataset with a similar distribution while protecting user privacy. There is a tradeoff between user privacy and dataset accuracy that I need to address. The users' daily activity logging generates a time-series dataset. We not only need to measure the similarity between the distributions, but also consider the time component and how causal relationships evolve over time. For example, how walking 1000 steps today affects health a year later. This is an area of recent research, and I want to apply it to real-life datasets to evaluate its effectiveness and improve it further.

What part of your Minerva experience most significantly informed your current perspective on the world and the way you approach studying now?

If not for Minerva, I would not be in the field of machine learning or data science. Minerva was a formative experience for me—it helped me find who I am, who I want to be, what my dreams and goals are. It also equipped me with tools to contribute to biology and healthcare without being a medical doctor. I studied pharmacy for two years in Belarus, but I realized that face-to-face interaction with patients was not for me. Back home they say, only specific types of people become doctors because it is a lot of responsibility, and sometimes you need to be less sensitive. Minerva helped me find the right tools to fulfill my goals without pursuing the traditional route of becoming a doctor.

What are some learnings from your Minerva classes that you find yourself applying to your life or studies now?

I never expected it to happen, but I find myself thinking about Habits of Mind and Foundational Concepts (HCs) when I write reports or have conversations. For example, I might think about #SystemDynamics. These concepts are applicable to different areas of my life, especially when I want to persuade someone or impress people at a dinner party. I use these concepts often, and they are everywhere. It is funny because when I met some of my Minerva friends recently, we all said the same thing and laughed. We thought we would never use HCs after graduation, but in reality, our lives are just using these foundational concepts.

Minerva also prepared me in terms of more practical knowledge, like using several coding libraries, like PyTorch. I feel like I am better prepared than many people in my program. Many people come from multiple backgrounds, and usually these are people with some interest in biology. However, they do need to have computer science background. During my interview preparation, I was scared at first, but actually, I will say that I feel much more prepared than many other people from prestigious schools.

How does your Minerva education make you uniquely prepared for post-graduate life?

In terms of computer science preparation, there was not much focus on theoretical components like math, programming, or computer hardware at Minerva. However, by the time I graduated, I had worked on a wide range of projects through various internships, such as a bioinformatics lab in Korea, T-hub in India, and predicting deforestation in Argentina using satellite imagery. I had many projects in different circumstances and environments. Working in India is not the same as working in Argentina, South Korea, or Mexico. These experiences prepared me to work with different types of people and understand how teams work. Many of my friends from traditional schools probably only had one internship in a classical company with 15 other people. It is different to understand how to work as a real data scientist. By the time I graduated, I felt well-prepared.

Can you talk me through your Capstone project? In what ways do you think your Capstone work informs what you are doing now.

My Capstone project was focused on early breast cancer detection. I analyzed a dataset and predicted the likelihood of a female developing cancer in the coming years, focusing on prevention rather than cure. This approach has numerous benefits, including better prognosis, improved patient well-being, and reduced healthcare spending. Right now, I am doing something pretty similar in a sense that I have this healthcare data set, and I have a goal of how we can make use of it or make it better. I learned many of these tools and techniques at Minerva. I had one very nice tutorial on deep learning at Minerva, which got me into Artificial Intelligence. My experiences now are a direct result of what I was doing a few years ago at Minerva.

How did relationships with your Minerva professors help you to get into this program?

First of all, I want to thank Ben Nelson, because he actually referred me to my first job. And that is how I gained more experience.

Additionally, I received two reference letters from Professor Ribeiro and Professor Gahl. Professor Ribeiro is always excited to answer career-related questions or help write recommendation letters for me when I decided to pursue a Ph.D. program. She was very supportive toward me and is genuinely a caring person. I was very lucky to be in her Capstone class. Professor Gahl is from the Natural Sciences College, which was a nice combination of expertise to complement my computer sciences background. During my work-study with her, we worked on ecology projects where I contributed as a data analyst and created visualizations for papers. This experience introduced me to research, and Professor Gahl has been a great support, always available for calls and advice.

If you were inspired by Rita's story and are seeking a college experience that will teach you valuable pragmatic skills that will enable you to change the world, apply to join Minerva today.