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Philly honors experts in robotics, genetics, evolution

The 2017 John Scott Awards are going to Ruzena Bajcsy, Warren Ewens, and Masatoshi Nei.

Philadelphia’s annual John Scott awards in science and medicine are going to Ruzena Bajcsy for her work in robotics; Warren Ewens for his research on population genetics; and Masatoshi Nei for his work on evolutionary theory.
Philadelphia’s annual John Scott awards in science and medicine are going to Ruzena Bajcsy for her work in robotics; Warren Ewens for his research on population genetics; and Masatoshi Nei for his work on evolutionary theory.Read moreCourtesy of the Board of City Trusts

With driverless cars fast approaching the market and camera-equipped robots now available as toys, the phenomenon of computers that "see" may seem like everyday technology.

Ruzena Bajcsy helped launch the field before digital cameras even existed.

The founder of the University of Pennsylvania's acclaimed robotics lab is among the three winners of Philadelphia's annual John Scott Awards in science and medicine, to be given in a ceremony Friday at the American Philosophical Society.

The other winners are Warren Ewens, a Penn emeritus professor of biology who pioneered the use of statistics in the field of population genetics, and Masatoshi Nei, a Temple University biology professor who is acclaimed for applying molecular biology to the study of evolution.

The Scott awards are bestowed each year by the Board of Directors of City Trusts, a group that administers more than 100 charitable trusts for which Philadelphia is named as trustee. The winners, each of whom receives $10,000, are chosen based on recommendations from a panel of scientists. Scott was a Scottish chemist and pharmacist who endowed the award in honor of Benjamin Franklin, directing that the prizes be given to "ingenious men or women who make useful inventions."

In 1822, the first year the awards were given, recipients were honored for such practical creations as a garden weeder and a "screw-cock hydrant." Later honorees of note included architect and inventor Buckminster Fuller and radio pioneer Guglielmo Marconi.

Bajcsy was among the first to tackle the problem of teaching computers to perceive three dimensions from a two-dimensional image, starting in the 1970s. Digital cameras had not yet been invented, so she and her colleagues had to build their own "digitizer" to convert images from traditional photographic film, she recalled in an interview for a robotics oral history project sponsored by Indiana University. Her early research paved the way for medical imaging such as MRIs.

Born in Bratislava, in what was then Czechoslovakia, Bajcsy earned an undergraduate degree in electrical engineering in 1957 and soon was working on the country's first computer — a machine that came from the Soviet Union. She earned a Ph.D. in engineering in 1967, then went to Stanford University for a second one in computer science, in 1972.  She came to Penn in 1979, where she founded the GRASP robotics lab, applying theories from mathematics and biology to her work, and now is at the University of California, Berkeley.

"In science, you don't limit yourself to just one trick in the book, to one specific field," she said in a news release from the awards committee.

Ewens, the Penn biologist, developed a statistical technique in 1972 to gauge the frequency of genetic variants across an entire population. More than four decades later, the method is now such a fixture that a Rutgers University statistician wrote a whole paper about it, titled the "The Ubiquitous Ewens Sampling Formula."

Born and educated in Australia, Ewens now teaches statistics at Penn's Wharton School.

Nei, who spent more than 25 years at Pennsylvania State University before coming to Temple, also studied population genetics but is best known for his work in the field of evolution.

A past winner of the prestigious Kyoto Prize in science, Nei's research involved analyzing the "distance" between genes in different organisms to determine how long ago they diverged on the evolutionary tree of life.