The Hertz Foundation announced that it has awarded 2026 scholarships to three current MIT students and an incoming Ph.D. These are: Annika Marschner, Alvin Q. Meng, Zachary S. Siegel, and Matthew Wanta.
This prestigious science and technology award provides each recipient with five years of financial support – a stipend and the equivalent of full tuition – giving them extraordinary freedom to conduct groundbreaking research as part of their master’s thesis.
“What particularly impresses me about this cohort is their fearlessness in taking on new challenges and pushing the boundaries of science,” says Philip Welkhoff, a Hertz fellow and director of the Gates Foundation’s malaria program, who co-led the selection process. “Each has demonstrated tremendous creativity, commitment and vision, and I can’t wait to see what each of them will accomplish 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, and since the fellowship’s creation in 1963, more than 1,300 fellows have been named. The connections made between these individuals have spawned joint start-ups, research and commercialization in a range of technology, science and engineering fields. Hertz Fellows have contributed to groundbreaking discoveries in fields such as advanced medical therapies, 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 majored in mechanical engineering and will begin her PhD at MIT in the fall. Her undergraduate research focused on the development of novel technologies for both biointerfaces and bioinspired systems, including a custom stereoscope-compatible desktop incubator and extrusion-based desktop bioprinter for the MIT Raman Laboratory, a fiber optic bioprinting system for the ETH Zurich Tissue Engineering and Biofabrication Laboratory, and large-scale hardware designs for robotic systems in the Robotics Laboratory Biomimetic MIT. Marschner’s bachelor’s thesis focused on improving the speed and dexterity of animated limb movements in biologically inspired robots. As a student, she plans to continue working on the design of equipment and control systems in biologically relevant environments, particularly in the areas of assistive medical technologies and surgical robotics.
Alvin Q. Meng is a PhD candidate in inorganic chemistry, focusing on understanding the fundamental interactions underlying chemical structure and reactivity. Currently, he is researching iron-sulfur clusters under the supervision of prof Daniel L.M. Suess. Born in Tianjin, China, Meng immigrated to the United States at the age of 10. He received bachelor’s degrees in chemistry and mathematics from the University of Virginia, where he worked in the research group of Professor W. Dean Harman. His research included the synthesis and characterization of dihapto-coordinated tungsten cyclopentadiene complexes, focusing on a class of unusual binuclear species containing a carbon-carbon bond connecting two five-membered metal-bonded rings.
Zachary S. Siegel is a graduate of electrical engineering and computer science, completing doctoral studies in the field of: Laboratory of Computer Science and Artificial Intelligence, 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 Award for Outstanding Independent Work in Computer Science. His major thesis, supervised by Tom Griffiths and Jacob Andreas, examined how people infer the goals of others in open-ended, real-world environments. Siegel demonstrated how Bayesian inference serves as an true model for predicting people’s goals by comparing partial observations with a learned library of possible plans weighted by their prior probabilities. The goal of his doctoral research is to build machines that learn and reason more like humans – systems that can learn from circumscribed data and generalize to novel situations by combining robot planning and Bayesian inference. Siegel is particularly interested in combinatorial generalization: the human ability to compose known skills in novel ways to solve previously unseen problems without additional demonstrations. At MIT he is advised by, among others: Leslie P. Kaelbling, Tomás Lozano-Pérez, and Joshua B. Tenenbaum.
Mateusz Wanta is an incoming graduate student who will begin operations research at MIT in the fall. He is a 2026 graduate of the United States Military Academy at West Point with a bachelor’s degree in computer science and mathematical sciences, both with honors. His work focused on machine learning for autonomous systems, integrating probabilistic modeling and computer vision in collaborative drone search and swarm control. In cooperation with the DEVCOM Armament Center, Wanta has developed computer vision models for detecting energy defects in artillery ammunition, enabling quick and non-invasive quality control in defense production. His work with the U.S. Special Operations Command and Army C5ISR organizations focused on autonomous aerial search and detection, where he built simulation architectures for probabilistic target location and multi-agent coordination. Wanta served as a company commander in Bravo Company, 2nd Regiment; president of Upsilon Pi Epsilon; and vice president of Phi Kappa Phi. He is a graduate of the Astronaut and Sapper School, as well as an army officer in the Cybercorps.