UMass Amherst’s Hava Siegelmann Honored by U.S. Department of Defense
AMHERST — Nearly 100 colleagues recently joined an online celebration to honor Professor Hava Siegelmann of the UMass Amherst College of Information and Computer Sciences (CICS), as she received the rarely awarded Meritorious Public Service Medal from the Defense Advanced Research Projects Agency (DARPA) of the U.S. Department of Defense. It is the third-highest honor the Department of the Army can bestow on a private citizen.
“The distinctive accomplishments of Dr. Siegelmann reflect great credit upon herself, DARPA, and the Department of Defense,” reads the citation in part.
Added Siegelmann, “I didn’t know that anyone was noticing what I do. It was so touching, and a complete surprise. I feel honored to be contributing. I think UMass should get credit for supporting me to run a very advanced AI lab such that the government wanted to invite me, and for allowing me to join what is literally the world’s most advanced and sophisticated AI initiative.”
CICS Dean Laura Haas added that “I am extremely proud of Hava’s service to DARPA and the nation. Our college is dedicated to a vision of computing for the common good, and Hava’s work at DARPA has helped to advance AI for us all.”
Siegelmann went to DARPA as a program manager in July 2016, where her charge included “that the United States needs to stay on top in AI,” she recalled.
Her citation noted that “she created and managed some of DARPA’s largest and most advanced AI programs, including L2M — developing next-generation advanced AI systems capable of learning in real time and applying learning to environments and circumstances not specifically trained for.”
Siegelmann, whose career is characterized by thinking outside the box, created a different atmosphere for the L2M project than is usual at DARPA. With its support, she insisted that the large, diverse teams of scientists she chose from the nation’s top university and industry research organizations must actively collaborate. “Such a large leap in AI technology can only be achieved when we top researchers all put our strengths together and learn from each other,” she said.
The medal cites another major DARPA program Siegelmann created called GARD (Guaranteeing AI Robustness Against Deception), which aims to establish the theoretical machine-learning system vulnerabilities, characterize properties that will enhance system robustness, and encourage the creation of effective defenses. As systems become more advanced, these advancements open new avenues by which they can be attacked. GARD identifies often-obscure, technically complex vulnerabilities and builds new-generation defenses for them, she noted.
DARPA also points out that Siegelmann’s “exceptionally productive” term included developing a system that administers insulin plus dextrose to maintain glucose at safe levels for patients in critical care and those with diabetes; sensors to identify dangerous chemicals from a safe distance; collaborative, secure learning systems that allow group collaboration without revealing sensitive data; and methods to identify attacks by reverse engineering to secure the system and find the attacker.
“L2M has had major success in creating systems capable of learning and improving in real time,” Siegelmann said.