MIT Collaborators Win 2026 Hertz Foundation Fellowship | MIT News
The Hertz Foundation announced that it has awarded 2026 fellowships to three current MIT students and a graduate student. They are: Annika Marschner, Alvin Q. Meng, Zachary S. Siegel, and Matthew Wanta.
The prestigious science and technology award provides each recipient with five years of financial support – a grant and full tuition – giving them an extraordinary measure of independence to pursue challenging research in their graduate work.
“What impresses me the most about this group is their fearlessness in taking on new challenges and pushing the boundaries of science,” said Philip Welkhoff, Hertz Fellow and director of the malaria program at the Gates Foundation, which participated in the selection. “Each has shown incredible creativity, grit, and vision, and I can’t wait to see what each person accomplishes with the freedom to innovate that the Hertz Fellowship provides.”
In addition to funding, fellows receive lifetime access to Hertz Foundation programs including events, mentoring, and networking opportunities, along with more than 1,300 other fellows who have been named since the fellowship was founded in 1963. The connections created between these people have sparked the initiation of cooperation, research, and trade in different fields of technology, science, and engineering. Hertz Fellows have contributed to breakthroughs in areas such as advanced medical treatment, global defense networks, and the James Webb Space Telescope.
This year’s MIT-affiliated recipients are among a total of 19 Hertz Foundation Fellows selected from across the United States.
Annika Marschner ’26 is majoring in mechanical engineering and will begin his PhD at MIT in the fall. His undergraduate research focused on the development of novel technologies for both biointerfacing and bio-inspired systems, including a benchtop stereoscope-compatible incubator and extrusion-based desktop bioprinter for MIT’s Raman Lab, a light-based filament bioprinting system for ETH Zürich’s Tissubrication engineering systems and robotic hardware design for MIT’s Biomimetic Robotics Lab. Marschner’s undergraduate thesis focused on improving the speed and range of motion in bio-inspired robotic limbs. As a graduate student, he plans to continue his work in both hardware and control system design in biologically relevant settings, particularly in the areas of medical assistive technology and surgical robotics.
Alvin Q. Meng is a doctoral student in inorganic chemistry focusing on understanding the fundamental interactions underlying chemical structure and reactivity. He is currently studying iron-sulfur complexes under the supervision of Professor Daniel LM Suess. Born in Tianjin, China, Meng immigrated to the United States at the age of 10. He received degrees in chemistry and mathematics from the University of Virginia, where he worked in the research group of Professor W. Dean Harman. His research involved the synthesis and isolation of dihapto-coordinated tungsten complexes of cyclopentadiene, focusing on a class of rare binuclear species that contain a carbon-carbon bond connecting two metal-bound five-membered rings.
Zachary S. Siegel is an electrical engineering and computer science graduate student pursuing a PhD in Computer Science and Artificial Intelligence Laboratory, where he works at the intersection of robotics, cognitive science, and artificial intelligence. He graduated summa cum laude from Princeton University with a BSE in computer science and a minor in philosophy, receiving honors including Tau Beta Pi, Sigma Xi and the Outstanding Computer Science Independent Work Award. His senior thesis, advised by Tom Griffiths and Jacob Andreas, investigated how people achieve the goals of others in open, real-world environments. Siegel demonstrated how Bayesian inference works as an accurate model for predicting people’s intentions by comparing incomplete observations to a learned library of probabilistic systems that are estimated by their prior probabilities. His doctoral research goal is to build machines that learn and think more like humans – systems that can learn from limited data and adapt to new situations by combining robotic programming and Bayesian inference. Siegel is particularly interested in assimilation: the human ability to synthesize known skills in new ways to solve problems that could not have been seen before without further demonstration. At MIT, he was mentored by Leslie P. Kaelbling, Tomás Lozano-Pérez, and Joshua B. Tenenbaum.
Matthew Wanta is an incoming doctoral student who will begin a research career at MIT in the fall. He is a Class of 2026 graduate of the United States Military Academy at West Point with a bachelor’s degree in computer science and mathematics, both with honors. His work focuses on machine learning for autonomous systems, combining probabilistic modeling and computer vision in cooperative drone search and crowd control frameworks. In collaboration with the DEVCOM Armaments Center, Wanta has developed computer vision models to detect potential defects in weaponry, enabling rapid, non-disruptive quality control in defense production. His work with the US Special Operations Command and Army C5ISR organizations focused on automated aerial search and sensing, where he built simulation architectures for potential target location and multi-agent communications. Wanta served as company commander of Bravo Company, 2nd Regiment; president of Upsilon Pi Epsilon; and vice president of Phi Kappa Phi. He is an Astronaut Scholar and a graduate of Sapper School, and is commissioned as an Army officer in the Cyber Corps.
