2018 - ACM Distinguished Member
His primary areas of study are Human–computer interaction, Activity recognition, Mobile phone, Ubiquitous computing and Artificial intelligence. His Human–computer interaction study combines topics from a wide range of disciplines, such as mHealth, Speech recognition and Physical health. His study in Mobile phone is interdisciplinary in nature, drawing from both Real-time computing, Mobile computing and Mobile search.
The Mobile search study combines topics in areas such as Telecommunications and Mobile Web. His Ubiquitous computing research is multidisciplinary, relying on both Multimedia, Wearable computer and Internet privacy. Tanzeem Choudhury works mostly in the field of Artificial intelligence, limiting it down to topics relating to Machine learning and, in certain cases, Pattern recognition, Inference and Data mining, as a part of the same area of interest.
Tanzeem Choudhury mainly focuses on Human–computer interaction, Artificial intelligence, Ubiquitous computing, Machine learning and Wearable computer. His Human–computer interaction research is multidisciplinary, incorporating perspectives in Social network analysis, mHealth, Mobile phone, Multimedia and Behavior change. His research integrates issues of Mobile computing and Mobile search in his study of Mobile phone.
His work in Artificial intelligence covers topics such as Social network which are related to areas like Sociometer. In general Machine learning study, his work on Activity recognition, Feature selection and Boosting often relates to the realm of Structure, thereby connecting several areas of interest. His Activity recognition research integrates issues from Variety, Real-time computing, Embedded system and Data mining.
Tanzeem Choudhury mainly investigates Human–computer interaction, Intervention, Mental health, Schizophrenia and Wearable computer. The various areas that Tanzeem Choudhury examines in his Human–computer interaction study include Tracking and Behavior change. His biological study deals with issues like Self-monitoring, which deal with fields such as Ubiquitous computing.
His Wearable computer research includes themes of Experience sampling method, Cognition and Cognitive psychology, Distraction. His biological study spans a wide range of topics, including Machine learning, Missing data and Artificial intelligence. His Audiology study integrates concerns from other disciplines, such as Generalized estimating equation and Mobile phone.
Tanzeem Choudhury mostly deals with Anxiety, Wearable computer, Mobile technology, Mental health and Intervention. His Anxiety research includes elements of Self-management, Feeling, Social psychology and Control. His Wearable computer research incorporates themes from Experience sampling method and Cognitive psychology.
He interconnects Socialization, Applied psychology and Clinical psychology in the investigation of issues within Mobile technology. His studies in Clinical psychology integrate themes in fields like Schizophrenia, Data management and Social isolation. His Mental health research is multidisciplinary, incorporating elements of Psychological intervention, Decision support system and Brief Psychiatric Rating Scale.
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A survey of mobile phone sensing
Nicholas D Lane;Emiliano Miluzzo;Hong Lu;Daniel Peebles.
IEEE Communications Magazine (2010)
SoundSense: scalable sound sensing for people-centric applications on mobile phones
Hong Lu;Wei Pan;Nicholas D. Lane;Tanzeem Choudhury.
international conference on mobile systems, applications, and services (2009)
A practical approach to recognizing physical activities
Jonathan Lester;Tanzeem Choudhury;Gaetano Borriello.
international conference on pervasive computing (2006)
The Mobile Sensing Platform: An Embedded Activity Recognition System
T. Choudhury;S. Consolvo;B. Harrison;J. Hightower.
IEEE Pervasive Computing (2008)
The Jigsaw continuous sensing engine for mobile phone applications
Hong Lu;Jun Yang;Zhigang Liu;Nicholas D. Lane.
international conference on embedded networked sensor systems (2010)
A hybrid discriminative/generative approach for modeling human activities
Jonathan Lester;Tanzeem Choudhury;Nicky Kern;Gaetano Borriello.
international joint conference on artificial intelligence (2005)
Bewell: A smartphone application to monitor, model and promote wellbeing
Nicholas Lane;Mashfiqui Mohammod;Mu Lin;Xiaochao Yang.
pervasive computing technologies for healthcare (2011)
StressSense: detecting stress in unconstrained acoustic environments using smartphones
Hong Lu;Denise Frauendorfer;Mashfiqui Rabbi;Marianne Schmid Mast.
ubiquitous computing (2012)
A Scalable Approach to Activity Recognition based on Object Use
Jianxin Wu;A. Osuntogun;T. Choudhury;M. Philipose.
international conference on computer vision (2007)
Mobility detection using everyday GSM traces
Timothy Sohn;Alex Varshavsky;Anthony LaMarca;Mike Y. Chen.
ubiquitous computing (2006)
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