Diagnosing depression is a complicated endeavor that requires health professionals to detect responses of individuals to questions and observe lifestyle changes. It is life-saving work that assistant professor of computer engineering Tuka Alhanai believes can be substantially enhanced through machine learning models.
Alhanai works on the interface of human and computational machinery to build algorithms that can help measure subjective elements of human behavior. Her research has shown the potential of using machine learning systems to quantify formerly immeasurable human qualities such as determining the characteristics of a group of people that form a successful team or the elements of an idea that lead to a hit in the marketplace.
It’s work that she began while conducting her PhD at the Massachusetts of Technology (MIT). In her thesis she explored the use of speech to automatically detect the presence of cognitive impairment due to dementia and Alzheimer’s disease in individuals, a heavily underutilized biomarker that may help in the early diagnosis of the 10 million yearly cases of the debilitating syndrome.
Her research has garnered much attention and piqued the interest of her academic circles, but it also has been recognized for its potentially impactful use cases. Bill Gates, co-founder of Microsoft and co-chair of the Bill & Melinda Gates Foundation, even highlighted on his personal blog the research that Alhanai had worked on with colleagues at MIT, Boston University, and the Framingham Heart Study.
Building upon her success, Alhanai co-founded the machine-learning consultancy company, Ghamut Corporation, in 2016 to utilize her technical experience to solve business challenges across a variety of industries. For her entrepreneurial and translational work, she received awards from MIT and a Small Business Innovation Research grant from the National Science Foundation. She continues to share learnings from these industrial experiences through her teaching and student mentorship activities at NYUAD.
Tuka Alhanai’s drive and curiosity towards becoming a master of computer engineering has been present since she was an undergraduate at the Petroleum Institute in the UAE. The Emirati’s self-starter nature and dedication to excellence allowed her to sustain an academically rigorous and demanding career, but it’s her stalwart belief in the importance of mentorship and learning from others that allowed her to excel.
“Finding mentors, relying on a network of colleagues and professionals to help guide me through these challenges is a key component of my career. A lot of the time, especially when you’re conducting research or working in a cutting-edge field, there is no text book on how to progress, and that’s where I find mentors to be important,” she said.
As a computer engineer, Alhanai continues to build and utilize her network of colleagues, former educators, and family members to help guide her through her work.
As a professor, she now finds herself in a position to give back in the mentorship cycle. Her Lab for Computer-Human Intelligence has hosted over 25 high-school, undergraduate, and full-time researchers; several student research assistants have pursued top industrial positions (Palantir, Noon, Goldman Sachs) while others have gone on to continue their post-graduate education, with one even conducting a DPhil at Oxford University motivated by research they worked on in Alhanai’s lab.
“It’s probably the single most important thing, ask for advice, work with others. Having an opportunity to be mentored by NYUAD staff, and helping students and other researchers I work with is an amazing experience that is really key to the academic world,” she said.