CBSExecEd ROL Lab

University Facilitating Fund Awarded

Dr. Nakamura has been selected as the awardee for George Washington University Facilitating Fund to support her research on the reflection on adult brain.

The 7th International Conference on Business and Social Science (ICBASS 2019)

On the 28th of March, Yoshie Tomozumi spoke at the Educational Session of the ICBASS Conference in Kyoto, Japan on Adult Learning in Time of Crisis. Thanks for all those who came out!

Researcher Intro Series: Parul Kaushik

My past research assignments include studying ‘Lies & Detection of Lies’ at Columbia University and I continue to use facial coding system and neuro-linguistic psychology of lying in my ongoing assignments.  My research assignment at United Nations Development Program on behaviour assessments was a national initiative for public service officials with a view to strengthen leadership in…

Rehan Rehman

What is your data analytics experience at the lab?

As a research assistant in the Return on Learning Laboratory, I am interested in examining how the fields of neuroscience and business intersect with each other, particularly with respect to how mindsets affect learning within organizations. Recently, I have also developed an interest in the neuroscience of leadership, decision making and cognitive biases. Ultimately, I aim to develop strategies that would equip learners with the tools to maximize their return on learning within an organizational framework.

What about data analytics most impassions you?

The brain is a complex organ and understanding its structure and function requires sophisticated technology. Only until recently have we been able to develop such tools to answer multifaceted questions about the brain. Answering these complex questions about the brain and understanding how resulting insights about this organ can be put to practical use in the areas of education and business is what I am passionate about. There is still a lot that needs to be explored and done regarding the brain, and it is this very prospect that fascinates me, as a student, as a teacher and as a researcher.

What is the biggest challenge you face in data analytics?

Huiying Zhang

What is your data analytics experience at the lab?

I am a new graduate research assistant at the Return on Learning Lab and joined the data analytics team in December 2017. My day-to-day tasks include finishing up cleaning data gathered in the past and looking into our data from Pardot.

What about data analytics most impassions you?

Han Sun

What is your data analytics experience at the lab?

It is such an honor of working with brilliant friends. I am primarily focusing on improving the objective-based recommendation system and analyzing online user behavior for growth hack. Based on the previous version of recommendation system, I am looking for more powerful machine learning algorithms and natural language tool kits.

What about data analytics most impassions you?

My passion for data analytics stems from the effect of my analysis, which can do or change something. When I was a kid, I dreamed about being a detective like Holmes or Quain. Now, data analytics allows me to be the detective, instead focusing on data. I love to dive deep into an algorithm and perform deep learning and/or reinforcement learning. Ultimately, I’d like to create an AI based on big data. 

What is the biggest challenge you face in data analytics?

TaeYoung Choi

What is your data analytics experience at the lab?

I will be analyzing online data that stores user behavior on the web in order to gain insights and possibly improve their experience.

What about data analytics most impassions you?

As a student with a statistics background who has faith in the power of data, I have studied how to optimize various systems through algorithms, and data science has triggered my curiosity.

What is the biggest challenge you face in data analytics?

Yiqi Wang

As a graduate research assistant with ExecEd’s Data Science team, I am primarily focusing on improving the recommendation system and analyzing online user behavior for growth hack. I am trying to improve the efficiency and accuracy of the current recommendation algorithm through natural language processing and machine learning techniques.

Solving real-world problems by way of scientific data analytics is the most exciting thing to me. Due to the increasing data size, many statistical theorems can be applied to help people see insights on the data and leverage this analysis to improve human beings’ lives.

Hassan Mortagy

I have been working with Yoshie as a research assistant since the start of the summer. I was very excited to get onboard and do pricing analytics work, which has not been done before here at executive education, and is also a field that I enjoy very much. Here at the lab I have been working on all things revenue and cost, through various aspects of pricing that range from price optimization to modelling the program choices of our customers

I am most passionate about price optimization, finding an optimal price point for product is a notion that just really appeals to me. In addition, I am also very passionate about the intersection of machine learning and business analytics with pricing. This is the area where I use statistical models to estimate our customers’ behavioral response to pricing, such as in the estimation of price-response functions and fitting choice models.

Hi, this is Mengxiong Li. It’s my great honor to work with Yoshie and other team mates. My major job in this lab is to clean the data set and build the Recommendation System. The data set available for us is very messy, and there are also a lot of empty or useless records in the data set. Therefore, cleaning the data set is a very time-consuming process. During the data cleaning, our team use some predictive model to fill in the missing records. For the Recommendation System, it is one of the major projects in our team. We hope that by using this recommendation system, we can recommend some courses for the individuals who input some information to our system. Since the available data set is very limited, right now we only build a draft Recommendation System. However, there are lots of room for this system to be improved.

Data analytics is one of the hottest topic in the industry. As a statistics student, data analytics is always the field that I am very interested in. I believe that with the development of Machine Learning, Deep Learning and other advanced statistical techniques, the function of data analytics will be even broader.

While the data analytics is very interesting, I also face many challenges when dealing with the data analytics. One of the biggest challenges is the limitation of the data set. Even though we have many great ideas or statistical algorithms, we are always limited by the availability of the data set. What’s more, since we are facing the raw data set, it takes a lot of time to clean the data set.

Kapil Sharma

As a Graduate Research Assistant here at the ExecEd’s Data Science team, I’ve been working on building the predictive model and recommendation system to improve conversions from inquiries to enrollments. I also manage the blog and social media posts for RoL Lab at ExecEd. This is a great place to learn and experience hands-on implementation of advanced statistical methods using real world data.

I am passionate about building products and processes that continuously leverage the power of data to better themselves. Most tech product development today is focused on user experience & optimizing the use of software architecture while completely overlooking the insights that could be generated from user data. I want to build products that generate and act upon these insights leading to potential avenues of revenue growth or increased user satisfaction.

The biggest challenge that I face in data analytics is figuring out the quality of data and identifying the key parameters that need to be included in the model. Especially, when you have data pouring in from various sources, it is important to make sure that certain parameters do not get over-represented. Often times, a good understanding of the business/operations process that generates the data set helps in tackling this problem.

Aidan Rivera

Apart from handling the website and social media sides of the lab; I focus mainly on compiling data to use from ExecEd’s Canvas site and social media outlets.

I am most passionate about seeing the product of what we do. Working with a tangible source of data and working on the algorithms which format that information into usable data makes me appreciate seeing a nice graph or curve from the messy reality in the end.

Ryo Kono

I have conducted research for and supported many quantitative and qualitative analytics projects over the years, including determining competitive social media efficacy, conducting social network analyses from survey data, and creating a comprehensive regression model to forecast enrollment patterns on both a micro and macro level.

Apart from teasing out the key insights from a large data set that initially might seem random and chaotic, I am most passionate about figuring out how to tell a compelling story from the data because it challenges me every time and forces me to think outside the box.