In recognition of this year’s International Women’s Day, IBM Research celebrates its female scientists.
By Angela Harp
Maria Gabrani: Teaching computers to recognize diseases
After catching pneumonia as a child and spending a month at the hospital in her native Greece, Maria Gabrani knew that she wanted to help cure people and solve medical problems when she grew up.
After she recovered, she would chase her little brother around the house until he allowed her to pretend to be his doctor, and perform ‘tests’ on him with a toy stethoscope. Later in high school though, Gabrani also fell in love with mathematics — and found a way to combine both passions. Today, at IBM Research in Zurich, she is solving medical problems through image processing, pattern recognition and machine learning techniques in different application areas, ranging from computational pathology to drug discovery.
And she is convinced that mathematical and computational power can help medicine reach its full potential. “Medical images make up an estimated 90 percent of all medical data –a volume that is overwhelming to even the most seasoned pathologists who currently assess these images manually,” she says. “Through deep learning, mathematical modeling and image processing, I can teach computers to see, extract and understand information from medical images, such as stained tissue images.”
This machine learning application enables physicians and medical professionals to study various forms of heterogeneities (tissues, intra-, and inter-tumor, cellular) –phenotypes in human tissue that make it difficult to personalize medical treatment. “We’re at ease when software automatically recognizes where we’re located and gives us directions to reach our destination,” Gabrani says. “Just imagine if a similar concept was applied to tissue images and other medical data such as radiology, clinical or molecular data, to help find the best diagnosis, prognosis and treatment for each individual.”
She believes that advancing image processing and pattern recognition technology, as well as multimodal data integration is a huge step towards tailored patient care. Her work is already impacting the medical industry — and she wants to be a role model for her two children, too. “My mom was my role model, so I’ve taught my kids what she taught me growing up –to be curious about life and never stop questioning. Inquiry broadens your vision, deepens your understanding and reveals answers to problems.”
Irem Boybat: Developing next generation AI hardware
Irem Boybat was born in Istanbul, Turkey — and was seven years old when she got her first computer. That may sound strange to today’s digital natives who may have beenexposed to iPads and tablets right out of the womb, but when she was a kid, computers and smartphones were not yet common in private homes.
While Boybat had no internet or elaborate programs on her computer, the simple games she could play were enough to awaken her ambition to become a part of the exciting world of computers. Today, she is not only part of the computer world, she’s at the cutting edge of it. As a scientist at IBM Research in Zurich, Boybat is working on in-memory computing–a new computing paradigm inspired by the working principles of human brain.
In-memory computing uses the physical properties of memory devices for both storing and processing information. This is counter to the current so-called von Neumann systems — such as our standard desktop computers, laptops and cellphones, which shuttle data back and forth between the memory and computing unit. While von Neumann architecture has been supporting our technology since 1945, it is not the most energy efficient.
And with the rise of artificial intelligence (AI), von Neumann systems have reached their limit. “AI implies prediction, inference and intuition,” says Boybat. “But the most creative machine learning algorithms out there are currently constrained by machines that can’t harness their power. So if we want to make great strides in AI, we need to upgrade our hardware too.”
She discovered her passion for in-memory computing by pure coincidence during an internship at the IBM Research laboratory in Almaden, California. Little did she know at the time that a few years later she would end up at IBM Research in Zurich, and that her work would appear in the peer-reviewed journal, Nature Communications.
Collaborating with scientists from IBM Research, EPFL and the New Jersey Institute of Technology, Boybat has recently developed and tested an artificial synapse architecture using one million devices. This is a significant step towards realizing large-scale and energy efficient in-memory computing technology.
When asked if her career path as a female scientist has been challenging, she says that gender has never been an issue for her in the workplace. “In the end it’s about bringing like-minded scientists together to develop future technologies,” she says.
Boybat appreciates that IBM Research promotes cultural and gender diversity and is very active in seeking the next generation of female leaders and talents. “My advice to young women and teenage girls interested in a science career: do what excites you and don’t be intimidated by hard work,” she says.
In her native Turkey, the gender gap continues to narrow in the areas of science, technology, engineering, health, and research and development. According to the United Nation’s 2017 Eurostat report, some 45 percent percent of Turkish women work in STEM fields, surpassing the EU average of 40.5 percent.
Svenja Mauthe: Making a big impact with small lasers
Did you know that data centers consume up to two percent of the world’s electricity? This is equivalent to the amount of CO2 emitted by the fuel used for aviation worldwide.
Svenja Mauthe, a physics PhD student at IBM Research –Zurich, is committed to solving this problem — using small lasers on a chip. She believes that her research in silicon photonics can have a positive impact on the future of optical communications.
“Data processing is a major energy guzzler because today’s systems send data from A to B through electrical links,” she says. “By having a small laser on a chip, the power-hungry electrical wires can be replaced with low power and high-speed optical lines, similar to how copper lines got replaced by glass fibers in internet connections.”
The aim of Mauthe’s research is to develop and integrate very small lasers on chips used in computers, phones and other electronic devices to make them even faster and more energy efficient. The challenge here is shrinking the laser to match the electrical devices. As part of the PLASMIC project, she is addressing this challenge by exploring the application of novel plasmonic materials to develop nanolasers on silicon, which could eventually be integrated with CMOS electronics.
“For as long as I remember, I’ve been fascinated by light,” says Mauthe. “In high school, I once did a simple double slit experiment. Shining light on a double slit, you’d naively assume to see two bright lines on the wall behind it. But surprise, light is a wave and interacts with the slits which results in a complex interference pattern on the wall. That was the moment I realized that I had to learn as much as possible about light.”
When Mauthe is not in the lab, she enjoys being outdoors and loves to go climbing to relax and clear her mind. Svenja is also a volunteer mentor in the FemaleTalents@KIT program at the Karlsruhe Institute of Technology in Germany. The program pairs female mentors from IBM with female students seeking support and guidance on their scientific career path.
“After being a mentee of this program myself, I find it rewarding and exciting to mentor great female scientists in STEM,” she says.
Rui Hu: Discovering Europe, AI and an electronic tongue
Rui Hu always dreamt of being a scientist and discovering the world beyond the small village where she grew up just outside of Xi’an, China.The first step towards realizing her dream was studying Electronic Engineering at Xidian University. There, one of the professors introduced her to artificial intelligence.
“I was hooked,” Hu exclaims. Her research in machine learning, computer vision and data science gave her the opportunity to go abroad. Before coming to Switzerland, Hu spent time in Germany, the UK and France. As a PhD student, she worked in top institutions, including the Centre for Vision, Speech and Signal Processing at the University of Surrey and the Xerox Europe Research Center.
In the summer of 2018, Hu joined the IBM Research lab in Zurich as a post-doctoral researcher. Her research focuses on developing AI engines that drive the cognitive IoT platforms for digital health in the projects, Activage and CAir. Recently, she started working on machine learning algorithms that support sensor design and data analytics of the electronic tongue technology in the Hypertaste project. Hypertaste is an AI-assisted, portable electronic tongue that can reliably ‘fingerprint’ complex liquids.
“Here at IBM’s Zurich Lab, I am lucky to have the opportunity to work in a multidisciplinary environment where I can constantly learn new technologies,” she says. “One example is the Cloud. Through the Hypertaste project, I am learning all about it, and it’s amazing.”
Rui has been living in Europe for 10 years now. Although her initial decision to leave China shocked her parents, they have been very supportive. Rui is still in awe of the fact that she lives in Switzerland: “I especially love to go skiing in the Swiss mountains,” she says.
Diana Davila Pineda: Contributing at the nanoscale
Diana Davila Pineda from Oaxaca, Mexico has one of those jobs that has a special dress code. On a typical day at the office she has to put on a special suit to enter the cleanroom, where she makes devices so small that you could fit hundreds of them in the cross-section area of a human hair.
These devices, such as microprocessors similar to those in electronic gadgets, are highly sensitive to contamination. This is why laboratories where the environment is highly controlled are so important to our high-tech lifestyle. Pineda is part of the Cleanroom Operations Team of the Binnig and Rohrer Nanotechnology Center, a collaborative infrastructure designed specifically for advancing micro-and nanofabrication and jointly operated by IBM Research and the Swiss Federal Institute of Technology in Zurich (ETH Zurich).
When asked what inspired her to get into science, she says it simply seemed like a natural thing to do. “As a child I always liked taking apart home appliances to ‘fix’ them, and in school, I preferred math and physics to history and grammar,” she says. But it wasn’t until college that she discovered her scientific calling. During a university exchange program in Finland, she entered a cleanroom for the first time to make a microbridge that emitted light when heated.
“This was a mind-blowing experience for me, after which I immediately knew that I wanted to build a career in micro and nanotechnology,” she says. Today, entering a cleanroom is a normal part of Pineda’s workday. As a senior advisory engineer, she supports scientists from various fields in finding the right processes to develop devices and structures that are needed to advance a particular technology.
This could be anything from exploring materials suitable for phase-change memory chips, crucial for building the next generation of AI hardware, to producing silicon nanostructures for qubits in a quantum computer. A great part of Pineda’s job is the variety of projects she gets to work in. “With a state-of-the-art laboratory in an environment rich in knowledge it is almost impossible not to do great things,” she says.
Currently, she is working on a few projects that involve graphene. “Graphene has amazing properties. It’s one of the best thermal conductors; it’s elastic and the most impermeable of materials, which makes it suitable for a range of applications in electronics, biomedical engineering, and even the textile industry,” she says.
One of the things Pineda likes most about her role is interacting with various scientists to understand the importance of their projects and needs. “Each day is different and it’s gratifying to see smiles on the faces of those I’ve helped,” she says.
She has worked hard to receive scholarships and grants to fuel her scientific career — and she believes it would be great to have PhD programs that specifically target young women in underdeveloped countries who dream of going into science.