Drake Adams worked virtually with
OneRadio out of Seattle, Wash., to help automate the startup procedures of their high dynamic range receiver and its applications.
Tristan Brigham used Python-based machine learning algorithms to design circuits for testing quantum error correction on within the
AAIM Lab while also utilizing his newfound artificial intelligence skills to create projects using cutting-edge computer vision, text recognition, and error detection strategies. Furthermore, Tristan used his programming skills in Rust and C to continue development of the
NYU Secure System Laboratory's Lind framework while preparing the project for its final testing phases which he will initiate in his capstone.
Zoe Demers worked with an
MIT microeconomics research team to analyze how new e-commerce platforms, such as AirBnb and Zillow, have affected the trajectory of the U.S. real estate market.
Logan Gamlin worked this summer to analyze known transiting exoplanets and TESS candidate exoplanets using AstroImageJ in collaboration with Ms. Warner at the
University of Maryland.
Ellie Hanson worked at
Nuance Communications, testing virtual assistants and other voice recognition software in the medical industry with Java, Silk Central, and Agile methodology.
Ciaran Henry worked with Professor Nir Krakauer at the
City College of New York to model climate trends in the Northeastern area with RStudio, using data from the Integrated Surface Database.
Charlotte Kinlin worked in the
Applied Biomechanics Lab at the University of Colorado, Boulder, where she studied the effects of running specific prosthetic stiffness on the metabolic cost and symmetry of female athletes with a trans-tibial amputation.
Caroline Light worked at
Georgetown University studying the mechanisms of a targeted protein-protein interaction inhibition-based cancer therapy developed for Ewing Sarcoma.
Jenna Malone spent her summer working with
OMEGA Venture Partners and the
Center for Collective Intelligence at MIT. At OMEGA, she analyzed early growth AI companies as potential investment opportunities. At MIT, she researched "Superintelligence," or the theory that human-computer groups are more efficient than either group alone.
Avery Minter worked at the
NASA Jet Propulsion Laboratory and detected the magnetospheres of super-earths through electron-cyclotron maser emission from super-earths in python. Additionally, she worked at
UMASS Amherst and used galactic morphological classifications to analyze galactic data in python.
Kyle Pellerin worked at the
IDEAS lab at Northwestern this summer, where he collaborated a team focused on creating more energy efficient HVAC systems using deep reinforcement learning coupled with other machine learning strategies.
David Yan worked at
MathEarth, Inc. at Acton, Mass. to develop an in-pipe leakage detection robot system in collaboration with the Mechatronics Lab at MIT, he also helped with the implementation of a pressure GIS leakage detection system in LinGang, Shanghai.