Hall of Fame
Hall of Fame - 2021
Seok Yim won the Quinlan competition (prediction challenge) - tied with Bennett Garcia and had the highest score in class (tied with Nicole King)
“Hi, I am a Sophomore majoring in Computer Science who hopes to graduate in 2023. To be honest, I did not have that much prior interest in Data 101 and merely saw it as a way to satisfy one of the requirements for graduating. However, after taking this course, I realized how significant it is to properly understand data and also how easy it is to get fooled by data in the real world. The prediction challenges were fun and exciting, even though they took a lot of my time (They were totally worth my time!). Now that I’m done with Data 101, I feel so ready to act like a professional data analyst in front of my friends who haven’t taken this course yet. ”
Nicole King had the highest overall score in the class of 150 students - her work was simply outstanding - her TA commented that Nicole's presentations were like research reports.
Here is what Nicole said about herself and the class
"I am a Psychology major, Statistics minor, graduating in May of 2021. During my undergraduate career I worked as a research assistant in the Human Computational Cognition Lab under the direction of Dr. Pernille Hemmer and Dr. Julien Musolino. My honors thesis, advised by Dr. Pernille Hemmer, investigated prior knowledge in the form of scripted and unscripted events. My thesis was awarded the MarilynShaw Award for Research Promise and the Henry Rutgers Scholar Award. In Fall 2021, I will start classes at The Ohio State University in pursuit of a PhD in Psychology within the Cognitive Neuroscience track. I will be working in the Model-Based Cognitive Neuroscience Lab under the direction of Dr. Brandon Turner.
Data 101 was such an enjoyable class due to the hands-on approach to working with data. It introduced me to Kaggle and allowed me to further advance my R skills in such a way they will be advantageous to my future research career. The class not only engages those with experience in data science, but those with little data science experience. It has become one of my most memorable classes during my time at Rutgers and I am thankful to Dr. Imielinski for teaching it this semester"
Durva has written the best data driven blog (see 2021 blog entries), she also was one of the very top over all scorers in the class - with heavy load of 13 weekly assignments, final quiz and miderm.
"Hello everyone! I'm a rising senior majoring in Psychology and minoring in Economics. I am really interested in risk analysis, consumer behavior and business psychology, hence I am aiming to pursue a career in either one of these fields.
Before taking this class, the world of data science seemed daunting to me and consequently affected my ability to confidently derive conclusions about any data that I came across. Furthermore, my knowledge of R programming language was rather limited, hence the usage of R in this class has evidently shattered my mind blocks and made me more confident as an individual when it comes to data analysis. With that being said, I loved the fact that this class was more application based rather than rote learning, hence this class had connotations beyond academics for me. Lastly, I want to thank Professor Imielinski for his perspicacity while structuring this class and making it such an insightful course throughout the semester. I highly recommend this class to everyone at Rutgers!"
Bennett won (tied with Seok) the 2021 Quinlan competiton, the prediction challenge consisting of 4 problems. He has used neural network which was first time in the history of data 101 that someone used NN so succesfully.
Below, what Bennett said about himself
"Hi my name is Bennett Garcia and I'm a sophomore studying Computer Science and Math. I'm interested in Machine Learning and I plan on pursuing a career in research. I want to work on new reinforcement learning algorithms and develop practical uses for the field. I took Data 101 to further my knowledge on statistics and to practice applying Machine Learning to real problems. Before taking the class I had some experience with Machine Learning, but only on the implementation and Computer Science side. The prediction challenges were super fun and gave me a chance to try using Machine Learning in a more applicative way. I really enjoyed the class. It definitely gave me experience that will help me in my career"
Jeremy was one of the top competitors in prediction challenges. In particular his solution to one of the challenges (the Professor Moody grading challenge) was amazing! His overall score in class was at A+ level.
Here are few words from Jeremy:
Hello everyone! I am a Computer Science major planning to graduate in May 2023. I also hope to get the new undergraduate certificate in Data Science. This class was my first real experience working with data, and I loved every second of it! From coding and statistical analysis to prediction challenges with large datasets, every aspect of this course pushed me beyond what I thought I was capable of, and I could not be more grateful. I’m honored to have learned from such a great professor, and I know the lessons I’ve learned in this class will follow me in my future endeavors in data science.
Hall of Fame - 2019
Sarah is the reciepient of Quinlan 2019 award for winning the prediction challenge (5 weekly prediction problems - winner with largest aggregated accuracy wins). In addition she scored the top 3 overall score in the whole class.
Here is what Sarah says about herself and her goals
"I am a Statistics major and Psychology minor planning to graduate May2020. I hope to pursue a master’s degree in Biostatistics and a career
in data analysis. I was already interested in this subject before taking Data 101, but now I feel I have great hands on experiencanalyzing data (in R and in general). The Prediction Challenge wassuper fun and reassured me that I picked the right major. Overall, Iloved the class and I think it can be really useful for anyone
regardless of major, especially because almost all careers nowadaysrely on data in some way."
Sean has placed 4th in Prediction Challenge - he has also stunned the class with tremendous advance in Kaggle rankings in one of the challenges - moving almost 100 poistions up when kaggle calculated full test results. He has also been frequent presenter of excellent solutions to data puzzles and prediction challenges.
Here is what Sean has to say about himself and his goals:
"Hey everyone! My name is Sean Gilbert and I’m an Environmental and Business Economics major graduating in 2019. I took Data101 because I
had great experiences with online data boot camps, and wanted to take a formal class where I could expand my knowledge and compete in challenges. I am beginning my career as a data analyst and am excited to apply the skills I have learned in this course to real world problems. I could not recommend Data101 enough, as it teaches you to think critically, solve problems logically, and communicate clearly. It is one of the most valuable courses offered at Rutgers!"
Soham Shah got the highest overall score in the entire class. He also placed in top 6 of Prediction Challenge. This is what Soham says about himself and his goals
"I am currently a Junior at Rutgers, majoring in Genetics with a minor in Statistics and pursuing a certificate in computational genetics. I am particularly
interested in computational genetics and the application of statistical analyses in identifying patterns. I took Data 101 this semester because of my strong interest in statistics, and have really enjoyed how the April Madness prediction challenges combined statistics, logic, and creativity all into one fun class-wide competition.
Thanks to Dr Imielinski's class, I have gone from knowing nothing about R to developing a crucial foundation of its basics. I will be applying to medical schools this year, and in
the future, I plan to carry on my knowledge of data science to use a data-driven approach of research wherever I go"
Tanvi got the second highest overall score in class- in addition she placed in top 5 in prediction challenge - April prediction madness.
Here is what Tanvi says about herself:
Hi! My name is Tanvi Wagle and I am a Computer Science major. My goal in college is to explore as many fields of computer science as I can. Taking
Data 101 in the Spring of 2019 has allowed me to take a peek into the world of Data Science and further that goal. This class, especially the prediction challenges, has
fueled my intellectual curiosity and allowed me to develop more analytical thinking skills. The skills I developed from this class will certainly help me in deciding my career path.
Hall of Fame - 2018
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 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 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."
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 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 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.
"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."
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.
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 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.
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 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.
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 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.
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 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.
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 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 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 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.
"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 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.
"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"
2015 Hall of Fame
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.
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."