About Us

Stuart has served as director of Gentiva (NASDAQ / Russell 1000 company) and as a director, chairman of the board of directors, and vice chairman and president of the Olsten Corporation (NYSE / Fortune 500 company). He also served on the board of Directors of Adecco and as the chairman of the operating board of MaggieMoos Int'l LLC. He was also on the Advisory Board of the Syracuse University School of Management. In 2017, Stuart acquired the software company Harqen where he spearheaded technology development that lead to the launch of Student Select.

Heather joined Student Select in January, 2018 and currently serves in the role of Senior Vice President. Prior to joining Student Select, Heather spent 25 years in recruiting, where she partnered with organizations in healthcare, hospitality, manufacturing, financial services, and education to create and execute effective recruitment strategies.

Micah has been working in design, development, and MarTech for over two decades, focusing on making a connection with current and potential customers.

Will oversees product development and technology operations. He has held senior leadership roles in IT operations, product management, and product marketing, and has extensive experience delivering cloud solutions to market. Prior to Student Select, Will served as a senior executive at Newtek Business Services Corp. (a NASDAQ company).

Thao brings to our team more than 5 years of experience developing data pipelines and machine learning applications. She holds a MSc in Computer Science and has published 7 papers in the fields of deep learning, image processing, gesture recognition, human-robot interaction, and virtual reality. Since joining Student Select, Thao has been architecting a more efficient data pipeline to drive the improvement of our state-of-the-art machine learning model.

Rachel got her PhD in Nuclear Physics and worked as a post-doc in Nuclear Engineering before joining Student Select as a Data Scientist. Now she hopes to use her knowledge of scientific experimentation and data analysis to understand and improve bias in the machine learning process.