HOFSTRA UNIVERSITY | DEPARTMENT OF COMPUTER SCIENCE
CHAIR’S NEWSLETTER • FALL 2026
Data Science at Hofstra: A Strong Start and a Proven Path Forward From freshman research in our new B.S. program to career launch through the M.S. in Data Science. The B.S. in Data Science and Machine Learning, launched in the 2025–2026 academic year, welcomed its first two majors, Dimitri Mignano and Hayden Budhan. After completing only one year in the program, both students are already demonstrating what we hoped the degree would make possible: a strong foundation in computing and data, early involvement in faculty-mentored research, and the confidence to apply that knowledge to real problems.
Preparing students to do more than use AI Artificial intelligence can generate code, analyze data, and automate tasks, but producing a solution is not the same as understanding whether it is correct—or knowing how to improve it. The program prepares students to understand what is happening underneath: algorithms, data, software, systems, mathematics, statistical reasoning, and problem solving. Students learn not merely to use today’s AI and data tools, but to evaluate them, build with them, and help create what comes next. That preparation aligns with a rapidly growing need. The U.S. Bureau of Labor Statistics projects employment of data scientists to grow 35% from 2025 to 2035, compared with 3% for all occupations, with about 24,800 openings projected each year. The opportunities extend across industries because data and machine learning are increasingly central to research, engineering, healthcare, business, cybersecurity, and intelligent systems.
Research beginning in the first year During their first semester, Dimitri and Hayden took CSC 108 Foundations of Data Science—their first course in the field—with Professor Angel Pineda. As freshmen, both also became involved in faculty-mentored research. Dimitri worked with Professor Marco Romanelli on performative prediction and optimization, strengthening his foundation in machine learning and preparing to approach complex real-world problems. Hayden worked with Professor Pineda on data science research involving the modeling of forced localization tasks using neural networks, extending what he was learning in CSC 108 beyond the classroom. This early access to research is a defining strength of the programs in the department: students do not have to wait until their junior or senior year to begin asking—and investigating—meaningful questions.
Already applying what they learned DIMITRI MIGNANO Dimitri is interested in applying computer science to robotics, automation, and aerospace. Building on his freshman research, he spent the summer interning at iRocket, where he helped develop the company’s automation process for solid rocket motor production—selecting equipment, planning for scale, and developing algorithms and new processes. He also presented the company’s technology to investors and contributed to fundraising efforts that raised more than $4.2 million. HAYDEN BUDHAN Building on CSC 015, CSC 108, and his freshman research experience, Hayden began contributing immediately as a Data Collection and Scraping Intern at Avatar Buddy, an AI-as-a-Service company. He built Python tools that collect brand-intelligence data from e-commerce sites, company websites, and news sources, feeding a pipeline that cleans, stores, and indexes data for AI-powered queries. His projects included a full Brand Scan scraper and a Grants.gov scraper that directly supported the company’s funding search.
Source: U.S. Bureau of Labor Statistics, Occupational Outlook Handbook, Data Scientists, 2025–2035 projections.
HOFSTRA UNIVERSITY | DEPARTMENT OF COMPUTER SCIENCE
Their accomplishments are impressive, but their significance goes beyond two individual success stories. They show how quickly students can move from foundational learning to research and industry when a program offers intellectual depth, close faculty mentorship, and authentic problems to solve. We are proud of Dimitri and Hayden —and excited to see where they, and the program, go next. GRADUATE PROGRAM SPOTLIGHT
The M.S. in Data Science: a proven pathway The department’s commitment to data science extends naturally to graduate study. The M.S. in Data Science offers advanced preparation for students who want to work thoughtfully and creatively with data, machine learning, and intelligent systems. It also gives students access to the close faculty engagement and professional experiences that distinguish computing education at Hofstra. THOMAS WALTER | FIRST M.S. IN DATA SCIENCE GRADUATE, December 2024
“The Data Science Master’s program was truly a transformative experience that helped me grow not only as a student but as a critical thinker.” Thomas valued the program’s intellectual breadth, the high level of engagement, and professors who encouraged students to draw on their technical and creative expertise.
Through Hofstra’s DeMatteis CO-OP program, Thomas completed a long-term internship at Altice, where he developed both technical and interpersonal skills. He coordinated action plans, presented to and worked with executives, and created products designed to benefit the company’s customers. The experience became a bridge from graduate study to professional practice: after earning his degree in December 2024, Thomas returned to Altice/Optimum as a full-time employee. Thomas’s experience is not unique: multiple graduates of the program have built successful careers in data science, while others have been accepted into Ph.D. programs in the field.
Extending the program’s reach Thomas’s experience shows what the M.S. program can offer: intellectual growth, sustained faculty support, meaningful professional experience, and a direct path into a data-centered career. The program is already a natural next step for Hofstra undergraduates and for students who build their preparation through the department’s postbaccalaureate certificate. Its promise, however, reaches further. There is an important opportunity to bring this experience to a broader community—including graduates of other institutions, working professionals, and career changers seeking rigorous preparation in a field that is reshaping every sector. A wider range of academic and professional backgrounds would enrich classroom discussion, strengthen the graduate cohort, deepen connections with employers, and extend Hofstra’s impact throughout the region. Together, the B.S. in Data Science and Machine Learning and the M.S. in Data Science create a powerful pathway —from a student’s first course and first research experience to advanced study, a CO-OP, and a successful career. The achievements of the programs’ first students and first graduate show that this pathway is working—and that it is ready to reach many more students.
Source: U.S. Bureau of Labor Statistics, Occupational Outlook Handbook, Data Scientists, 2025–2035 projections.