When you work in the digital sphere, it is easy to become disconnected. A year ago, clinical professor and former Wall Street data analyst Frank Parisi, alongside other Pace faculty, conceptualized a space where individuals with an interest in data science and machine learning could connect. “We wanted to make a central repository for all kinds of data, where we have the computational power to do interesting things, work together and collaborate across the University and, in the long-term, with outside partners for research.” Now, the space has been set up, the machines moved in, and Pace’s Computational Intelligence Lab is open for business.
Computational intelligence refers to the machine learning and data analysis abilities of a computer—it’s what allows us to collect data, speak to Siri, and play the newest video games. Having a physical lab with quality equipment and dedicated software means that students and faculty engaged in deeper analysis will not have to rely on remote Google servers to get their work done.
“This will be a proper space for computational intelligence specifically, from Artificial Intelligence, pattern recognition and machine learning.”
The lab isn’t just powered by machines, but also by passionate students. Multiple student employees are hard at work developing content for other students to exercise their technical skills while getting hands-on help from their peers.
Austin Blaise ’22 is a graduate computer science student who finds so much value in such a space that he volunteered to help set up the lab. He hopes for it to become a vibrant hub for students interested in data science, saying, “This lab allows you to learn the basics to create your own artificial intelligence model, and also have an environment wherein you have similar-minded students working on similar technologies.”
“This lab allows you to learn the basics to create your own artificial intelligence model."
Jon Lee, a clinical professor, was one of the architects of the Lab and he believes it will be unique in what it offers. “There are other Ƶ hubs that exist for design, digital forensics, cybersecurity,” he says. “This will be a proper space for computational intelligence specifically, from Artificial Intelligence, pattern recognition and machine learning.”
More importantly, perhaps, is its function as a place for students and faculty with similar interests to gather and connect. According to Lee, this lab is “one more way to get Seidenberg students engaged, active, and doing amazing things on campus, especially those who are feeling disconnected after COVID-19.”
Want to see the Computational Intelligence Lab or learn how you can get involved? Reach out to Frank Parisi at fparisi@pace.edu or Yegin Genc at ygenc@pace.edu.
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