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Hall of Fame

Hall of Fame - 2018

Todd Curtis

Todd overall score was the highest in entire class of over 150 students. He was very active in class (if no one knows, Ask Todd :-) plus he also placed high in top 10 of prediction challenge as well as highest in his section. Therefore he is also awarded with special grade of A+!

Here is what Todd says about himself

"My name is Todd Curtis and I am a Computer Science major. I have always enjoyed finding patterns and solving puzzles, so analyzing data and making predictions is right up my alley. I had some interest in the data science field before taking Data 101, but this class really showed me how much I truly enjoy the field. With that in mind, I am highly considering pursuing data science going forward. Analyzing the massive amounts of data available in the world today is a monumental task, but it is important to find ways to use the data that is out there in order to make smart decisions. I couldn't be more enthusiastic about the experience that Data 101 has been and highly recommend it to people of any major. Just understanding that not everything is what it first seems to be is such an important idea for everyone to learn in today's data driven world"

Michael Wang

Michael received second highest overall score in the class of over 150 students - nearly 95% of total score.

Here is what he says about himself

"Hello, my name is Michael and I'm a computer science major graduating in 2021. I find data interpretation to be interesting and I took this class because I wanted to get my hands dirty actually working with data. The prediction challenges were, well, challenging, but I left with a new tool R under my belt and learned more about probabilities. I think it's important to keep in mind not to blindly follow the "narrative" when the truth may lie in the numbers"

Sophie Barstein

Sophie is the WINNER of 2018 April Madness Prediction Challenge - in the convincing fashion - leading over the last several stages of five prediction challenges and achieving the smallest error from 140 competitors.

" Hello my name is Sophie and I am a psychology major and statistics minor. My Academic interests include cognitive science, business psychology, and data analysis. I took Data 101 because it seemed like a really interesting class and I wanted to learn more about the real world applications of data science. It ended up being one of my favorite classes I have ever taken at Rutgers and brought to light career possibilities for me that I haven’t thought about before."

Benjamin Guaragno

Ben won silver medal in our April Madness - prediction challenge 2018. Out of nearly 140 competitors over five different prediction challenges!

Here is what Ben writes about himself

"I am a Computer Science major, due to graduate in May 2021. I took Data 101 because I was interested in learning more about data science, as well as learning R. While I don’t plan to focus on data science in the future, I think the things I learned in this class, like visualizing data, logical fallacies, and when to be skeptical about conclusions, are valuable regardless of my career path"

Natalia Bryzhatenko

Natalia was 3rd in prediction challenge and also got 3rd highest score in class. Great performance!

Here is what Natalia wrote about herself:

I am originally from Ukraine, and this is my first year in Rutgers, while I plan to major in Computer Science. I think software engineering is a field when people can use their math and logic skills as well as creativity, that is why I chose it as my future career. Data101 turned out to be just the kind of class I like because students compete with each other solving prediction puzzles. These puzzles pushed me to study harder and gave a sense of proud for my work. Also, I think the ability of analyzing data and being somewhat skeptical towards all the information we receive daily is very important skill in modern world.

Hall of Fame - 2017

Andrew Li

Andrew won the bronze medal in April Madness Prediction competition, in photo finish where only one hundredth of a point sepearated the top 3. In addition he was one of the top 5 scorers in the class and gave amazing, spirited and full of humor presentation in front of the class.

ABOUT ANDREW:

"I am majoring in Computer Science with a minor in Statistics, due to graduate in May 2019. In Data 101, I was able to learn about the importance of Data, and how to properly utilize it. Even more importantly, through Professor Imielinski's teachings, I got to see how accessible this skill was using R. Between making visualizations, debating key issues with data, and of course, the class-wide competition, I found myself constantly improving my skills. I intend to hopefully utilize the skills I've taken from Data 101 as a professional Data Scientist in the future."

Yichen (Tony) Cao

Tony Cao, psychology major, won the April Madness Prediction Challenge in photo-finish over two computer scientists. This was the closest finish in the history. He recieved two Quinlans, for the best predictor of 2017 as well as (obviously) for the best non-cs predictor of 2017. Tony's overall score in class was in top 10 and he delivered some excellent presentations.

ABOUT TONY:

I am Yichen (Tony) Cao, a graduating senior majoring in psychology. As s student engaged in psychological research, I found that it is very important to be able to sort out in a reliable way what matters and what doesn’t. The Data 101 class provided me with the concepts and tools to find patterns and critical factors more easily and quickly. I have very little background in computer science, but I feel that I gained a great deal from the course. Knowing how to analyze data is equally important as knowing what code to use; having both enhenced my abilities
in many ways.

Michaela Murr

Michaela was abolutely top student in the class (highest total score) plus she placed second (silver medal) in April Madness Prediction Challenge for non-cs students and also TOP 7 in the overall prediction challenge competition. She was also one of the very best presenters! Excellent presentations and great speaking talent.

ABOUT MICHAELA:

I am a double major in math and economics, graduating in May 2018. I enjoy working with data to find patterns and creating presentations of my findings. I took Data 101 because I thought it would be fun and I wanted to develop my skills more in R and data analysis/visualization. I really appreciated this class because we were given a lot of leeway to do what we wanted with the assignments."

Brian Schillaci

Brian finished second in the prestigious Black Box tournament of champions and also in top 5 of the April Madness Challenge. In addition his overall score for the whole data 101 class was in top 3.

About Brian:

My name is Brian Schillaci and I am a Computer Science major going into my junior year at Rutgers. I took Data 101 during the spring of 2017 and learned a ton. This class showed me how important data is becoming in the world. Our ability to interpret and use data is more important than ever in helping us to be smarter global citizens in a world of confusing statistics about politics, climate change, and more. I learned a lot about data analysis, machine learning, and problem solving in this class while also having a lot of fun, especially in the data prediction challenges. I have no doubt that I will be able to use the skills I developed in this class in a future career and life in general.

Steve Valle

Steve is silver medalist of the April Madness Prediction Challenge coming very close to win it. He has also proposed some very creative solutions to prediction challenges - always thinking out of the box. Steve also finished in top 10 scorers for the entire class.

About Steve:

Hello, my name is Steven Valle. I'm majoring in Computer Science, hoping to later double major in Mechanical Engineering somewhere down the line as well. I hope to develop my own products to market to people, and acquire the skills necessary to understand what consumers demand in a changing world. I especially enjoyed Data 101 for it's strong emphasis on both handling given datasets and freely choosing your own datasets to work with and present in your own way, giving a mix of assigned responsibility and proactive responsibility. I think being able to model projections of any sort is a very important skill to have, and I hope to master this to better master the fields I intend to go into.

Daniel Fraser

Daniel won the prestigious Black Box tournament of champions and placed in top 5 of April Madness Prediction Challenge in addition to top 10 scores overall in the class.

About Daniel:

I am currently a junior, and I am majoring in computer science. I enjoy finding problems and creating algorithms to solve them. I took data 101 in spring 2017 because I never took a data analysis class before. This class got me interested in machine learning and after taking this course, I decided to teach myself more about machine learning and started playing around with many of R’s machine learning libraries.

2016 Hall of Fame

Chirangi Prettypaul

Chirangi won our first Prediction Challenge 2016 (gold medal) by providing simple (minimum description principle!) solutions which did really well on testing data. Isn't it the whole point? Yes and he got it.

He also did very solid statistical analysus comparing Steph Curry and Kevin Durant before were teammates (this was part of Data&Society Court of Data, and the title was "who is better player, Curry or Durant?"

Here is what Chirangi says about himself:

"I am a computer science major, graduating in January 2018. I took Data 101 my sophomore year in Spring of 2016 because I wanted to learn more about how I can apply my background to data analysis. I have used the tools introduced to me by Dr. Imielinski for a variety of applications, mostly for fantasy sports analysis in basketball and football."

Abdulrahman Althobaiti

Abdulrahman is silver medalist of our 2016 Prediction Cup and one of the top puzzle solvers over the whole semester. Enough to said, that he presented the record 5 times during class - coming up with exciting solutions and many times exposing Professor's data trickery!

Here is what he writes about himself:

My name is Abdulrahman Althobaiti, and I am part of the KGSP program of King Abdullah University of Science and Technology, KAUST. I have taken Data 101 at Rutgers during the Spring of 2016. In this course, I have developed a great interest in: data science, machine learning, and visualization, which allowed me to participate in a research of Aerospace Engineering and Mechanical Engineering at UT Austin. After a successful experience at UT Austin, a professor at UCI, University of California Irvine, invited me to join his team in the development of Brain Signals Modeling, Analysis, and Visualization. Thanks to Dr.Imielinski, Data 101 provided me with the tools necessary for a data scientist.

Boyang Fu

Boyang was one of the very top students in data 101 class and medalist of the Prediction April Madness Competition. His solutions to data puzzles were always among the best and he was enthusiastic and active participant and presenter in the Court of Data and Data & Society debates.

About Boyang
"I am a transfer international student and junior at Rutgers. I am interested in majoring in Computer Science. I like solving puzzles and actively participating in debates. I plan to work in the field of Artificial Intelligence in the future."

Zoran Gajic

Zoran got the highest score in class - just nailed all the data challenges as well as exams etc. Despite of Professor's attempts to
embed some false patterns in the data, Zoran never fell for any traps and exposed Professor's trickery clearly and without any doubts. Great contributor to class discussions and medalist in Prediction April Madness Tournament.

About Zoran:
"I am currently a junior in the SAS honors program Majoring in Molecular Biology and Biochemistry with a Minor in Computer Science, focusing on analysis of large scale biological data such as genome, transcriptome and proteome sequencing, for the purpose of creating novel ways to understand disease states such as cancer. My goal is to do an MD PhD joint degree specializing in computational biology for the PhD portion and using that degree to help advance the field of oncology"

Zoran Gajic

2015 Hall of Fame

Wenxin Zhu

Wenxin was the best student of the 2015 edition (first) of data101 class. Not only she get the highest score but also her group has been medalist of the Prediction April Madness Challenge (where you compete to provide best predictions for several different data sets). She and her group have also been presenter of many ingenious solutions to Data Puzzles during the semester.

About Winxen
I’m currently a senior at Rutgers, double majoring in Cell Biology and Neuroscience and Psychology. I hope to become a doctor and I am planning on applying to medical school this coming year. I took Data 101 my sophomore year because I had a background in statistics and I was curious about this class after my friends signed up for it. I ended up enjoying it much more than I thought and it opened my eyes to other fields of study."