Angelia Nedich has been solving puzzles for as long as she can remember. As a child, she played puzzle games with her parents. As she grew, her skills developed and her interest in solving problems remained strong. By the time she got to school, others began to notice. "I would have solutions before anybody could even think about it," says Angelia, thinking back, "Eventually I guess the professors started recognizing that I had something. They kept encouraging me and when they make you feel good about yourself, you just keep going."

Professors gave her books to study and urged her to compete and advance, and she kept doing what felt natural. She finished a bachelor's degree in mathematics from the University of Montenegro, Podgorica, in 1987, a master's in mathematics from the University of Belgrade, in Belgrade, Serbia, in 1990 and picked up a PhD in mathematics and mathematical physics from Moscow State University in Moscow, Russia in 1994. After that, she came to the US with her husband and had a son.

Soon, she started to look for a job that would help her take the next step toward the professional career in mathematics she'd always imagined for herself. But getting the type of position she wanted proved to be a new kind puzzle. "There was no way of getting to academia," says Angelia. Though she technically had a PhD, her work in Moscow hadn't required the breadth of coursework that would have been expected in the US. So she decided to head back to school and get a second doctorate, in the hope that it would help her compete in the tough academic job market. She applied to several schools and counted herself lucky when she was accepted to MIT, where she worked at LIDS under the supervision of Prof. Dimitri Bertsekas.

She was back on the path to academia, but life was busier and more demanding than before. "Part of me was never really a truly typical kind of student at LIDS, because I was a mother," says Angelia. On an average day, she'd push to finish as much work as she could during the traditional workday on campus, then head home to take care of her son and then, still later, put in a "third shift," during which she toiled away on coursework and research.

Despite the long hours, Angelia says she never considered giving up or turning to a different career. Being a scientist or professor in an academic, intellectual community was what she wanted to do and where she wanted to be, without a doubt.

She got a taste of that community while working at LIDS, alongside people who tackled difficult problems in control, communications, optimization, and signal processing. In her courses, she encountered classmates who had not only an abstract, theoretical understanding of problems, but also the intriguing ability to make guesses based on their knowledge of physical principles and deep familiarity with applications. They had a feel for the problems, while Angelia was predisposed to more of a pure, mathematical understanding.

"I had to stretch, because if I wanted to survive, it's not the math that matters. It's application domain," says Angelia, "That's the place to grow... You can learn the theory as much as you want but unless you find its use somewhere else, you will not be able to deeply appreciate its power and beauty." So she did extra reading and cultivated her ability to see the problems in the way her colleagues saw them.

LIDS is a lab full of people who are devoted to the study of practical, applied problems. During her time at the Lab, Angelia conducted thesis work that formed the basis for the project that has, to her surprise, sustained her interest for the last seven years; a project that started out as a general model and has since been used to study more application domains than she ever expected: multi-agent networked system optimization.

Though some of the related groundwork for the model was laid during her graduate work, Angelia didn't define the nature of the network model until the fall of 2006, when a friend and a colleague from MIT, LIDS Professor Asuman Ozdaglar, came to visit. Angelia had just left a four-year position in industry, and was now working as an assistant professor at the University of Illinois at Urbana-Champaign (UIUC), where she is still working today.

During the visit, the two collaborated on the model development of a distributed resource allocation in a multi-agent system. A multi-agent system is a decentralized network of agents or processing nodes. Each individual has limited information--it knows only about its nearby neighbors. But the network as a whole is charged with solving a larger network-wide problem. This, Angelia says, was a more complex version of work she had done as a part of her thesis. As she explored the model, she found that by changing the restrictions and characteristics of the nodes or the precise goals of the network the model could be used to examine a variety of problems. "The directions and applications of that model have far exceeded any expectations I may have had when this started," Angelia says.

She received an National Science Foundation Civil, Mechanical and Manufacturing Innovation Faculty Early Career Development grant to study the problem further, and she's been working in that area ever since. Though she's thought of moving on to the next problem more than once, Angelia says, students keep expressing interest in applying the multi-agent system optimization framework to one new application domain after another. Recently, graduate students have applied it to distributed regression and estimation, sensor networks, smart-grids, and machine learning.

Angelia is happy at UIUC. At the Department of Industrial and Enterprise Systems Engineering, she enjoys a collaborative, intellectual community that she describes as similar to LIDS. She's grown accustomed to the open skies and gently rolling land of Illinois, too. She likes the relative calm after Boston's frenetic pace, traffic-jams and hard-to-find parking – the price of daily life in the big city.

The days are still long, though. Now, in addition to juggling research and family, she travels to many conferences, teaches and makes herself available to students whenever possible. Her work still fills the nooks and crannies of life, on nights and weekends. But she doesn't mind much. It's still the only job she could ever imagine doing.