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Hall of Fame

Hall of Fame - 2025

Rayan Mahin

Rayan has won both Quinlan prediction challenge as well as Vapnik prediction challenge - become absolute king of prediction challenges. In fact his Quinlan prediction challenges win was the most decisive in the history of all 9 prediction challenges! Congratultions!

Here is what Rayan has to say about himself

"Hi everyone, I'm Rayan, a junior majoring in Business Analytics Information Technology (BAIT) with a possible minor in Data Science. I signed up for Data 101 hoping to broaden my foundations in Data Science, and this course has definitely exceeded my expectations. I particularly enjoyed the prediction challenges, which taught me that Data Science isn't just about building the most complex machine learning algorithm out there - but rather it's fundamentally centered on human intuition and problem-solving, a lesson I think is increasingly relevant in today's era of LLMs. Thanks Prof. Imielinski for the excellent course and good luck to all future students!"

Michael Hu

Michael placed in top 5 of prediction challenges and also acheived the highest overall score in the entire class of 250 students. Congratulations! This makes Michael Hu a top 1% student in the spring 2025 data 101 class

Here is what MIchael has to say about himself

Hi, my name is Michael, and I am currently a rising sophomore planning to major in Computer Science and Data Science. Throughout the class, I enjoyed exploring the various ways data can be used to uncover patterns and make predictions, and ultimately be used as a guide to formulate decisions. One of the most rewarding parts of Professor Imielinski's class is his prediction challenges, which pushed me to think creatively about the features beyond mere technical abilities. Looking ahead, the knowledge I gained from this class will continue to help me as I pursue data science.

Hall of Fame - 2024

Harshil Vejendla

Harshil Vejendla earned one of the highest scores in the entire class of Fall 2024 semester of data 101. He was also a co-winner of Vapnik prediction challenge as well as one of the best finishers in Quinlan Prediction Cup. Congratulations.

Here is what Harshil says about himself:

Hi everyone, my name is Harshil and I'm a freshman majoring in Computer Science and minoring in Data Science and Philosophy. I initially took this class as a way to see whether or not Data Science was of interest to me and I'm happy to say that this course far exceeded my expectations. Professor Imielinski's way of teaching is extremely valuable as he makes sure you understand the concepts as well as how to apply them in the prediction challenges. I believe the skills I've learned in this class will be very useful in the future, in almost any tech-related field

Harshil Vejendla is one of top 2% students in he class of more than 200 peers. Member of 2024 Fall semester Hall of fame of data 101.

Brian Wang

Brian Wang scored second overall in the FALL 2024 semester Quinlan competition in addition to the high overall score in the entire class. Congratulations.

Here is what Brian says about himself.

Hi everyone! I’m Brian, a sophomore majoring in Cell Biology and Neuroscience and considering a minor in Data Science. When I first signed up for this class, I wasn’t sure what to expect. But to my surprise, I found it both engaging and rewarding! This course not only strengthened my understanding of basic R and statistical concepts but also encouraged me to apply what I learned in real-world challenges using machine learning. I greatly increased my understanding of models like rpart, linear models, and especially random forest and how we could feature engineering and parameter tune for a better fit. I’m grateful for the experience and wish all future students the best of luck!

Brian Wang is data 101 Hall of Famer - in top 2% of the whole 200+ class!

Chris Chen

Chris Chen's performance in FALL 2024 semester data 101 prediction challenges has been spectacular! He won Quinlan Prediction Cup in dominating fashion. All his prediction models were free style - coded up by himself without any use of library functions such as rpart or random forrest. He is also a co-winner of Vapnik challenge. Congratulations!

Here is what Chris says about himself:

My name is Chris, and I am a sophomore double majoring in Computer Science and Statistics. Taking Data 101 deepened my understanding of data analysis, particularly through the prediction challenges. These challenges taught me that success in data analysis is not just about applying machine learning models but also about effective feature engineering and data visualization. I found the process of uncovering hidden patterns both exciting and rewarding. This course helped me develop critical thinking skills around data, which I look forward to applying in my future studies and career.

Chris Chen is data 101 Hall of Famer - in top 2% of the whole 200+ class!

Afnan Haider

Afnan Haider has been one of the masters of prediicion competitions - scoring 4th in overall for Quinlan Prediction Cup of FALL 2024 semester in addition to being one of just five co-winners of Vapnik challenge. Also - he answered correctly the most questions in class - contributing greatly to the concept of active class, thanks Afnan!

Here is what Afnan says about himself:

Hey everyone, I'm Afnan, a freshman majoring in Computer Science with a strong interest in Quantitative Finance. Coming into Data 101, I had zero data science experience (in fact, I used to think R and Rust were the same thing!). All I knew was that "Big Data" was taking over the world. However, this class has helped me not only understand the fundamentals of data science, but to also apply the new skills I've learned in the prediction challenges.

I wholeheartedly agree with Professor Imielinski’s philosophy that textbooks and exams are "outdated". His teaching style made the class both informative and engaging, keeping us on our toes. I highly recommend Data 101 to anyone considering it—it’s an eye-opening course.

And here's a little secret: always sit in the front and participate actively. Don’t stress if you don’t get every answer right (I definitely didn’t!), but it’ll keep you engaged and help you learn.

Afnan Haider is data 101 Hall of Famer - in top 2% of the whole 200+ class!

Alona Dhal

Alona Dahl has earned 3rd place in Quinlan Prediction Cup of FALL 2024 Semester data 101 competition in addition to being one of the top overall scorers. Congratulations!

Here is what Alona says about herself:

Hello! My name is Alona Dhal and I am a freshman intending to major in Economics and Data Science. I initially took this course to learn more about R, especially because it's a powerful coding language that has reached all fields of study. But after taking Data 101, I discovered that I've always been interested in the real-world application of knowledge, not limited to coding languages and statistics. Through both the creative homework assignments and the competitive yet fun prediction challenges, Professor Imieliński's dedication and strong interest in Data Science are evident, truly making this course an exciting experience. I can't wait to apply what I've learned in Data 101 in the future!

Alona Dahl is data 101 Hall of Famer - in top 2% of the whole class of more than 200 students.

Het Patel

Het Patel had one of the very top scores in the entire class of Fall 2024 and in addiition he was among top 6 students in Quinlan Prediction Cup. Congratulations!

Here is what Het says about himself:

Hi everyone! My name is Het Patel and I am a rising junior double majoring in Computer Science and Data Science. I initially planned on double majoring with Economics instead of Data Science. But after taking this course and seeing the recent growing trends of data science, I realized data science is a field worth pursuing. I gained more interest through completing the prediction challenges as I got to learn more about powerful tools such as rpart() and lm(). Taking this course has been one of the best decisions I think I made and I highly suggest anyone with a small interest in the field of data science to take this course as you will get to learn much more. My GitHub (Hetp29) contains the work I've done in this course which includes the prediction challenges and assignments.Thank you Professor Imielinski for this amazing class and I believe nobody could have taught this better than you!

Het Patel is a member of selective Hall of Fame for 2024 Fall semester data 101 class - just six students out of over 200 peers.

Rebecca Philip

SPRING 2024 Class: Rebecca has acheived the highest overall score in the entire class of Spring 2024. This is quite an honor and achievement. Congratulations!

Here is what Rebecca says about herself:

"Hi everyone, my name is Rebecca! I'm a double major in Business Analytics & Information Technology (BAIT), and Data Science. I knew that data analytics was a field that I wanted to pursue, but this class really elevated that passion for me. The best attributes of this class were how engaging and thought-provoking all of the topics were, and all credit goes to Dr. Imielinski for that; it's abundantly clear how passionate he is about this field! The prediction challenges were a great way to get hands-on experience with coding and finding patterns, and the Data in Society assignment was really interesting (especially the Climate Change Court of Data!) You'll definitely get a lot out of this course and be able to more critically analyze all of the data around you; best of luck!

Thanks once again for this opportunity, and for everything that you did in the class! I normally have a little difficulty focusing on lectures, but your clear excitement about the subject matter, as well as how the information was presented, was thoroughly engaging! Both you and the TAs were extremely helpful and willing to explain concepts, and I'm grateful for the positive experience I had in your class. I hope to keep in touch; have a great summer break!"

QiGui Weng

QiGui iWeng is the winner of this 2024 Spring semester Quinlan prediction cup. Thus, he has won the Quinlan award and gold medal. In addition, QiGui is also one of the top 10 overall scorers in the data 101 class.

Here is QiGui in his own words:

Hi everyone! I’m QiGui Weng and I am a sophomore majoring in computer science and possibly minoring in Data Science. I came to this class expecting it to be difficult and tedious after hearing lots of rantings from previous students who had taken this class. However, I found the class to be really enjoyable as Professor Imielinski kept the class entertained with his humor. His clear explanation and the textbook that he created made it easier to understand statistical topics that are taught in his class. While the course covered the fundamentals of R code and analytical thinking, I believe it is best for one to learn by challenging themself, applying what they learn and use it in the prediction challenges. Thank you to Professor Imielinski for instructing the course and hope the best to everyone who’s taking it!

Navid Jery Pulikkottil

Navid Jery Pulikkottil is one of the top 5 overall scorers in the entire data 101 class of over 200 students. In addition Navid, has tied for the "podium" (third) in overall ranking for prediction challenges.

Here is what he says about himself:

Hi, my name is Navid and I’m a freshman planning to double major in Computer Science and Data Science. Before coming to Rutgers, I had initially only planned on majoring in CS with a possible minor in economics or mathematics. But after taking Data 101, I now know that data science is a field I definitely want to delve deeper into. Prior to taking this course, I had minimal knowledge of data science as I didn’t even know what R was. Now, even after only learning the basics, I know what a powerful tool R can be. I also especially liked participating in the prediction challenges because even though they were difficult, it was rewarding to see my accuracy go up as I tried my best to figure out the hidden pattern. Thank you Professor Imielinski for this amazing class!

Nideesh Kumar

Nideesh Kumar has achieved one of the top overall scores in the entire class in addition to placing in top 10 of the overall leaderboard of prediction challenges. In addition, Nideesh has won one of the challenges.

Here is what Nideesh says about himself:

"Hey! I'm Nideesh and I'm a rising sophomore graduating in 2026 with a focus on Computer Science and Data Science. I expected Data 101 to be an intro to the field of data analysis and exploration but I learned a lot more about the field through the prediction challenges. I HIGHLY recommend you participate in the prediction challenges as you gain TONS of experience which will help you grow your data science skills tremendously. I really enjoyed Professor Imielinski’s class and hope you will gain as much from it as I did"

Jay Rana

Jay has achieved second highest overall score in the our data 101 class of over 200 students and in addtion has succesfully competed in prediction challenges series which this year consisted of 5 challenges. He placed in top 5 there as well.

Here is what Jay says about himsef:

"Hello, my name is Jay and I am pursuing majors in Computer Science and Data Science with possibly a minor in Cognitive Science. Data 101 has taught me the basics of R programming as well as the practical applications of data analysis. Also, participating in the prediction challenges throughout the semester has helped me understand the importance of eyeballing and subsetting to find specific patterns that are not easily detected even through rpart() or lm(). Finding hidden patterns in the data sets was a fun experience and I recommend participating in at least some of the challenges if you have the time. I hope what I've learned in this course will help me with future computer or data science courses at Rutgers and my future career goals"

Hall of Fame - 2023

Taneesh Amin

Taneesh Amin is one of top 5 scorers in the whole class. In addition he has won prediction challenge 2, with spectacular accuracy which provided dramatic ending on the Kaggle night!

Here is what Taneesh says about himself:

My name is Taneesh Amin and I am a Freshman (sophomore by the time you see this) graduating in 2026 with a major in Computer Science and the newly announced Data Science Major. Data101 was one of the more intellectually inspiring classes I have taken so far as a student. It really increased my love for Data Science, and I am so glad I am able to gain skills to pursue a career in it. If anyone had any interest in data science I would definitely recommend this course. If you are interested in seeing my continued data journey, I will be sharing it on my github (Taneesh04) and my Instagram (taneesh.am) where I analyze various patterns, mostly in sports using skills that have been taught to me in this class.

Tanish is the member of svery selective Hall of Fame of data 101 - top 2% of all students.

Rey Riordan

Rey has acheived top result (#1) in overall score in entire class (over 100%, maxing also extra credits!). Plus he placed top 5 overall in Quinlan competition for best overall prediction.

Here is what Rey says about himself and he even has something to share!

Hi, I'm a freshman pursuing majors in computer science and cognitive science as well as a minor in either mathematics or data science. I took this course to take my first steps into the field of data analysis, but I would like to stress to any incoming Data 101 students that this course is not about learning the gritty details of coding in R. Professor Imielinski focuses more on data science conceptually as being a way to think and analyze the world around us, which I think is much more useful! As a thanks for reading this far, here is a link to my notes that helped me do well in the class:

https://docs.google.com/document/d/1MWXHpWIHFV_aoixn6-qkW2PguYojeAai64d1...

And as a final note, if your R code isn't working you probably either made a typo or missed a comma. Good luck to everyone!

MAYEESHA MALIHA

Mayeesha has been on of the top 5 students in the class of 200 and also outstanding prediction challenges competitior (in the first two prediction challenges)

Here is what she says about herself and the class

Hi everyone, I’m Mayeesha! I am majoring in Cell Biology and Neuroscience and minoring in Psychology. I took Data 101 during my last semester as a graduating senior while trying to explore different career paths. I cannot stress enough how much this class has taught me about thinking analytically about the information presented to me. From realizing the role of bias in skewing samples and results to subsetting the data to find meaningful patterns, this class has shown me the importance of being critical about what I read and see on a daily basis. Despite my lack of coding experience, Professor Imielinski has been so encouraging and kind in office hours while showing me how to use R, which I feel much more comfortable with now! I look forward to using the data analysis skills I have gained in my future career and would recommend this course to anyone looking to gain a more keen understanding of how to analyze and present findings in a way that is meaningful to the audience at hand.

MELANIE TAN

Melanie has achieved 2nd highest score in the class (also, like Rey, above 100 with extra credits). She also placed in top 5 of leaderboard for prediciton challenges

Here is what Melanie says about herself.

Hello! I’m a freshman majoring in mathematics and computer science. I took this class because I was interested in exploring data science and am currently considering it as a future career. I had a lot of fun figuring out the patterns in the prediction challenges and I’m thankful to Professor Imielinski for giving me the opportunity to learn and practice R! The skills I’ve learned in this class helped me to get a research position for the summer and I’m excited to apply my statistical analysis and R skills to data in the real world :)

Howard Luo

Howard is the winner of 2023 Quinlan competition!

He got the highest combine accuracy from all competitions and won the trophe this year! In addition he placed in top 3 out of 200 students in overall score in the class. He also saved me a few times discovering early on some crippling mistakes like publishing values of prediction variable (the one which is supposed to be missing!)

Here is what Howards says about himself:

Hey there! I'm a sophomore in the class of 2025, majoring in computer science, mathematics, and possibly the newly introduced data science major. I had originally intended to devote myself entirely to artificial intelligence, but I enjoy the statistical elements of CS that this class contains. This course far exceeded my expectations and serves as an excellent foundation for data science purposes. This course teaches many fundamental basics in R for practical applications, which makes it suitable for students across a wide range of majors. I would like to thank Professor Imieliński especially, as I would most likely not be continuing data science if not for him. Thank You!

Hall of Fame - 2022

Joyce Huang

Joyce earned the highest score of over 99% in the entire class of 290 students. In addition to this she secured podium finish (top 3) in prediction challenges.

Here is a message from Joyce:

Hello everyone! I'm a freshman in the class of 2025. I'm majoring in Biomedical Engineering and minoring in Data Science. I took an online course on Data Analysis in junior year of high school and found it quite enjoyable, which is why I decided to minor in Data Science. I especially enjoyed the data puzzles that we did in class. Some of the patterns in the datasets were really interesting and I had a lot of fun finding them. Thank you Professor Imielinski for the fun class!

Jeeva Ramasamy

Jeeva is the winner of 2022 Prediction Challenge!. Jeeva won in unparalleled style winning the first two competitions on predicting categorical data as well as coming very very close second in the numerical data prediction challenge (it was really a "camera finish"). In addition Jeeva was one of the very top overall scorers in the class with around 98% of the total score.

Here are a couple of words from Jeeva:

Hello everyone! My name is Jeeva Ramasamy and I am a freshman majoring in Computer Science with a minor in Data Science. I am passionate about Data Science, Statistics, and Machine Learning. Although I was interested in this field before class, I had never performed data analysis or tried any machine learning algorithms. This class has been an amazing opportunity for me to learn about the fundamentals of Data Science. I especially enjoyed the weekly prediction challenges where we apply our learning to gain insight from datasets. I would like to thank Professor Imielinski for making every class and assignment exciting. This course is beneficial to students in any field as understanding data is very important in today's world.

Eva Zhang

There are many achievements of Eva in 2022 data 101 class. First of all she was the only student who got perfect score in the final quiz (in the class of nearly 300 students!). Secondly she was top 10 competitor in the April madness - our prediction challenges. Finally she scored over 98% of the overall class score!

Here are few words from Eva:

Hello! I’m a freshman (‘25) majoring in Business Analytics and Information Technology (BAIT) and double majoring in Computer Science. I took this course because I wanted to learn the basics of R and data science. I also heard really great things about this class. I really enjoyed the puzzles we did for homework, and overall, I’d definitely say they were worth the time and effort. I highly recommend this course to anyone who is interested in data science, wants to learn a bit of programming for statistics, or just wants to learn more about interpreting numbers!

Jiaxu Hu

Jiaxu has placed as on of the top 5 competitors in prediction challenges. He has also achieved one of the top overall scores in the class with over 97% of points. In addition, he pretty much answered almost all the questions during lectures! great class participation, Jiaxu!

Here are few words from Jiaxu himself:

"Hi, I am an ordinary Junior Mathematics major student. I took Data 101 for SAS Core Curriculum Our Common Future(CC-O). And I expect it will be a tedious course. However, we have some interesting homework every week that imply us how we can utilize the skills we learned this week. I also learn a lot in recitation by following the example code of TA to rough review about function of codes. I like the prediction challenge for the last several weeks, and I suggest it will be better if everyone has about 3-4 chances to hand in the code. Also the online textbook is really convenient to use and provides a lot of examples for every chapter. Tomasz is very kind that helps me a lot in office hours. All in all, this course inspires and encourages me to study data science. I suggest all students who are interested in math or computer science should try it."

George Basta

George has placed 2nd overall in Prediction challenges (out of over 250 students). In addition he has received one of the few best scores in class overall with over 96% of credit.

Here are a few words from George himself:

Hi all! I'm currently a sophomore with plans to get a B.S. in math. Initially, I didn't want to take this class because I've had a bumpy relationship with coding, but once I got the hang of it, the coding in this course was actually pretty manageable! It also helped that I had some prior experience dealing with data from Kaggle, but the synthetic data sets in this course have been a lot more interesting to play around with. I have learned a lot about data science, but even more about what I don't know in this massive field.Big thanks to Professor Imielinski for the way he taught this class; it has definitely made me want to consider more data science and statistics classes in the future (just wish that data science major would come out sooner)."

Ella Walmsley

Ella has won 2022 Datablog of the year (from 250+ submitted blogs). Not only she did perfect statistical analysis but she collected her data herself as survey of 200+ Rutgers students (published also on rediit). Ellla also did great in class with over 92% of total score.

Ella's inspiring presentation is class was enthusiastically received by her classmates and the professor!

Here are few words from Ella herself:

Hello everyone! My name is Ella Walmsley and I am double majoring in Plant Science/Agriculture and Food Systems and minoring in Data Science. I hope to pursue a masters in data science upon graduation. I have done coding and data analysis with R for research projects before, but this was my first real academic experience regarding data science, and I absolutely loved it! I feel honored to have had such an amazing professor and such wonderful and supportive classmates. I look forward to using what I have learned here in my research, career, and beyond. Thank you!"

Dhiren Patel

Dhiren placed in top 5 overall (our of 290 students) in Prediction Challenges (3 prediction problems where students competed using Kaggle). In addition he was one of the top students in class - with over 95% of the score!.

FROM Dhiren:

Hey! I'm Dhiren. I'm planning on majoring in Finance and Computer Science with a minor in Food Science. I took Data 101 Spring 2022 with Professor Imielinski in the hopes of becoming comfortable with manipulating and analyzing data as an aspiring Financial Analyst. I'm happy to say that this course and Professor Imielinski met and exceeded my expectations for what I hoped to gain at the start. Not only have I developed an interest in the search for patterns and characteristics hidden in unassuming sets of information, but Professor Imielinski's incredible passion, humor, and interest in data science have inspired me to seek a career where I can be as happy as him with what I do

Hall of Fame - 2021

Seok Yim

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

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 Kakade

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.

From Durva:

"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!"

Bennet Garcia

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 Prasad

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 Abu-Shanab

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 Gilbert

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

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 Wagle

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 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."