Bringing AI Home: Meet the Data Scientist Behind DES’s New Data Science Division
Evelyn Rosengarten is the Chief Data Scientist of Pittsburgh AI Works, a division of DES. Read about her passion for numbers, airplanes, and robots.
By some fluke, I emerged as a lover of math amidst a family of math haters. With math, you are presented with a problem, and it’s up to you to prove the solution. Finding that solution is exciting to me – you know it’s there, and the challenge is in figuring it out. This concept is at the core of my work. I’ve worked in computer science for over 30 years, and it all comes down to that one idea: discovering alternate ways of viewing data and using those insights to make better decisions.
I grew up a little north of Pittsburgh, in Franklin, PA. I was the first in my immediate and extended family (aside for one aunt) to go to college. Not surprisingly, I majored in mathematics at Penn State, but computers always intrigued me. In high school, we had massive mainframe computers and my summer job was a punch card operator at a local state oil company. After college, I worked at Prudential Insurance and was part of team that explored Expert Systems, an early subset of Artificial Intelligence (AI). Expert Systems are computer systems that emulate decision-making capabilities through if-then rules: if you input certain data to the computer, then it’ll output a specific result. Initially, AI was very regimented, but as computer science has evolved, the inputs have become ever more complex and ambiguous. Expert Systems transitioned to Data Mining which then progressed to Predicative Analytics, Prescriptive Analytics and most recently Data Science — at this point, we enable computers to learn their own rules and make (almost) human decisions.
I was hooked at the idea of machines responding independently to stimuli. I earned my master’s in computer science from Pace University, then worked on a robotics team at Johnson & Johnson. Our mission was to design a robot that could load suture threads into needles and package them for pharmaceuticals. I built the computer vision system that enabled the robot to correctly detect and place the elements and package the kits.
For almost a decade, I worked for Boeing, developing data analytics for their commercial and military fleets. I was the lead forecasting analyst for the F/A-18 combat jets, using deep learning for inventory forecasting and optimization. There are parts to the fighter jets that are highly specialized with a significant fabrication lead time, and my model predicted when each part would be needed for replacement, how to best manage the supply chain, and how an inventory of over 5,000 parts should be available at the right location at the right time. Complex to say the least!
On the topic of airplanes, my hobby is aviation. I am a commercial, instrument-rated, multi-engine pilot. Along with flying single engine planes, including previously owning a Cessna C182RG and a Cessna C182M, I also did a stint flying cargo for a subsidiary of UPS. I’ve competed in the Women’s Air Race Classic and have also volunteered for Angel Flights, a charity that arranges free air transportation for people with medical needs. Flying gives me a great feeling of freedom that I don't find anywhere else. This quote from Leonardo da Vinci describes it perfectly: “Once you have tasted flight, you will forever walk the earth with your eyes turned skyward, for there you have been, and there you will always long to return.”
I am presently the Chief Data Scientist at Pittsburgh AI Works, a newly formed division of DES. We are a team of seasoned engineers with the programming skills to solve virtually any complex business problem through the tools of AI. Our team — myself; Rock Arkie, Chief Innovation Officer; Michael Pointer, Principal Solutions Architect; Srini Silam, Dir, AI Innovations — have each worked at IBM, and Pittsburgh AI Works is a designated IBM Silver Partner. We are proficient in the IBM Watson tool suite, an interface that integrates natural language with big data, as well as in data mining, deep learning and in predicative and prescriptive analytics.
What most compels me about DES is its commitment to provide solutions that get to the crux of their clients’ needs. The company doesn’t sell network servers, but they engineer a complete connectivity infrastructure; they don’t install cameras, but they design a unified surveillance system that achieves safety with intelligence and simplicity.
My vision of computer science is to create a world where everyone can make better decisions from trustworthy data and analytics. My new position at DES will allow me to do this. With Pittsburgh’s blend of top-tier healthcare, education, industry, and business, I know there will be spectrum of provoking challenges for us to solve. For example, we could design a system for universities that provides personalized learning for students who are having trouble understanding lessons, or a system for manufacturing that predicts equipment failure and reduces downtime. For healthcare, we could create algorithms that optimize bed occupancy or predicts which patients won’t comply with their prescriptions. The possibilities are endless — like flying the wide, blue skies.