Helma Torkamaan is an assistant professor in AI for Health Systems and a member of the Systems Engineering section in the Multi-Actor Systems Department at Delft University of Technology (TU Delft).
Her research aims at: Building solutions for challenges inherent in the complex nature of health systems; Developing the future of technology-enhanced mental and physical well-being; Designing human-centered personalized interactive systems for empowering users and improving various areas; Creating technologies and tools that support better understanding, modeling, and prediction of human behavior and needs; and Evaluating these AI solutions responsibly and properly considering their long-term individual, mental, environmental, and societal challenges and impacts.
Helma builds systems and solutions using a highly interdisciplinary and collaborative approach to technology design that involves tools, techniques, resources, and perspectives from computer science, psychology, business, and healthcare. She collects and investigate multimodal data, derive requirements considering scientific theories of user behavior and with a data-driven approach, and design and creates innovative solutions to complex problems of human behavior and health, considering both multistakeholder and end-user needs, satisfaction, and experiences.
Recent Publications
See more
Projects
PAX
Mood Tracker
PAnalytics
DE3P
IWG Credibility
UCSM
Packaging
B2B Persona
Smart Home
DRS
PMIS
E-Health
See more
Selected Media Coverage
Contact
h.torkamaan@acm.org | |
Room B1.270, Building 31, Jaffalaan 5, 2628 BX Delft, The Netherlands | |
Please contact for an appointment | |
Follow Me on Twitter | |
Skype Me |
Download
Request to download Apps, source code, or datasets for non-profit academic research purposes
To request applications, datasets, or source codes related to the publications, please send me an email. These materials are open only for non-profit academic research purposes as specified in the respective publication. In the email, you need to specify the publication that you request materials from, your academic affiliation, the aim of the project that you will use the app or dataset for, and your institutional email address.