Institutional News

Data Science at Bennington: First Timers Unite

Bennington’s Women in Data Science Datathon introduced students to computer science and datathons to expand experience, create community, and build excitement for their upcoming virtual conference.

Join Bennington’s chapter of Women in Data Science on March 8 for the Women in Data Science Conference, and see all upcoming WiDS events.

At noon on Saturday, February 25, students gathered in the Commons Atrium to learn more about how they can use data science to solve one of the world's biggest challenges: climate change. It was Bennington College’s first Women in Data Science (WiDS) Datathon and the first in a series of two events organized with the aim to welcome more women to computer science fields. 

Most of the 20 participants were Bennington College students, but a few came from Williams College to participate in the event. Elani Reyes ’25was “very nervous.” She has taken mostly cultural studies and language courses until this term. She enrolled in her first computer class, Data Structure and Software, after she was assigned to work on a website during her Field Work Term experience.  

“I would have done a much better job, in my opinion, if I had more knowledge on data structuring and had a little more foundation in computer science,” Reyes said. She was relieved that the event was open to beginners. 

Angela Gui ’24 is a Computer Science/Art History/Art Studio major at Williams College. She attended with her instructor and two fellow students. None of them had ever been to a datathon before. 

“I just thought it would be cool to come out and meet more people and also because it is organized by Women in Data Science, which is definitely an underrepresented community,” Gui said. 

She was also interested in the topic of this datathon: extreme weather forecasting. “I have taken some environmental sciences classes, so I thought it would be really cool to integrate what I have learned in class with this opportunity.” 

After a welcome, introductions, and a short data science video, the audience received beginner-friendly information about the field of computer science, including data science and artificial intelligence. They heard about how people with knowledge and experience in these fields can make progress against climate change and other challenging problems. 

Finally, they divided into teams of four, got an introduction to the Kaggle open source programming platform, and practiced writing Python programming. A few hours into the event, they were ready to familiarize themselves with a data set and discover the first steps in programming a machine learning model to predict severe weather events and improve current physics-based models. According to the event format, half of all teams' members needed to be female identifying people

Image conference attendees in a room
Event organizer Niki Karanikola presents at the opening of the Women in Data Science Datathon on Saturday, February 25.
Image of man sitting in chair
Rohail Altaf ’17 is a senior software engineer and served as one of the mentors of the event.
Image of woman standing with microphone
Sinha Binte Babul ’25 stood to answer a question during the opening of the Women in Data Science Datathon on Saturday, February 25.

Developing Bennington WiDS

Bennington College’s chapter of WiDS was initiated by Niki Karanikola ’23 in the Fall of 2022. The chapter has grown to include a handful of students serving in a variety of roles. In addition to Karanikola and Faculty Sponsor Meltem Ballan, the group includes Tinashe Chiura ’23, event social media and communications; Mohammad Tanvir Anjum ’25, co-ambassador; Sinha Binte Babul ’25, video editor; Kasha Butterfield ’26; assistant video editor; Alejandra Vouga ’26, logistics; Miranda Aguero Gonzalez ’25, logistics; and Uyen Huynh ’24, logistics. Together they planned the Datathon and the upcoming virtual WiDS conference on March 8. 

“I know that we are way more privileged and have way different rights compared to females before us, but there’s still a lot of work to be done,” said Karanikola. “And I think when you are in a community, it is easier to stick to it and not get discouraged.”

As students worked throughout the early afternoon, mentors—including Ballan, Karanikola, Python Programmer Rohail Altaf ’17, and Ons Ali ’25—were on hand to help both beginners and intermediate students. It was a collaborative, rather than competitive environment, designed to make everyone feel comfortable asking questions. Each team also had access to a notebook with resources  directed to their level of experience. 

Karanikola’s aim in facilitating the Datathon was to gather women together and expose them to hands-on data science work. “It is hard to understand something without trying it,” she said. She was not necessarily expecting any of the teams to arrive at the final answer. “Because even just understanding the data takes a lot of time,” Karanikola explained. “But, I hope it was challenging and accessible and allowed some new people to become familiar with data science concepts.”

Reyes indicated after the event that the event was challenging and informative. “There was a lot of learning,” she said. She appreciated Karanikola being available to answer questions. 

“I think the event was organized really well,” said Gui. “It was a low stress but definitely an informative introduction to datathon events.” 

“I came away feeling very impressed by the quality of the experience,” said Babul, a WiDS Bennington member who is studying Computer Science, Data Science, and Animation and who contributed video promotion for the event. “Everyone felt very supported despite their diverse academic background.”

Coming Soon: Women in Data Science Conference

Karanikola and WiDS co-member Anjum are also ambassadors to the upcoming Women in Data Science conference. From this role, they are working with fellow Bennington WiDS chapter mates to provide an opportunity to attend parts of the Stanford Women in Data Science Conference via simulcast. 

The event is scheduled from 11 am–4:30 pm Wednesday, March 8 in CAPA Symposium. The program includes women from industry-leading companies like Microsoft and those conducting groundbreaking data science research with an aim to shed light on various societal and academic challenges. 

Speakers include Maria Elena Monzani, Lead Scientist, ​SLAC National Accelerator Lab; Gabriela de Queiroz, Cloud Advocate, Microsoft; Desi Small-Rodriquez, Assistant Professor of Sociology and American Indian Studies, at University of California, Los Angeles; and Marisa Torres, Bioinformatics Lead, Lawrence Livermore National Lab, among others.

Talk titles include, “Embrace the Journey: Learnings and Inspiration from a Non-Linear Path into Data Science,” “Killing Diseases with Really Big Computers: Building Analysis Tools to Solve Disease,” and the keynote “A Sparkle in the Dark: The Outlandish Quest for Dark Matter.” Students Mileati Melese and Stephanie Perez will share their work on Algorithmic Fairness in Health Care, along with Sherri Rose. The line up also includes a series of fireside chat videos with women computer scientists the chapter created. 

The program reveals the interdisciplinary nature of Computer Science. “It’s way more interconnected and accessible than most people think,” Karanikola said. “It is a tool, and the point is to solve problems. You can use the tool in any field that you want. That is great for students to learn, because we are living in an era where technology is all around us.”
 

Women in Data Science poster

Conference attendees from the College and the public can come and go as their schedule allows. While, according to WiDS operating principles, all of the speakers will be female or female identifying, people of all genders are welcome to attend. Those interested are invited to view the agenda and register in advance at the Bennington event’s Eventbrite

Learn more about Bennington College’s chapter of Women in Data Science in this interview by Halley Le ’25 or by visiting the Women in Data Science website, LinkedIn, Facebook, or Instagram.