D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 54 Citations 15,768 93 World Ranking 2257 National Ranking 1221

Research.com Recognitions

Awards & Achievements

2018 - ACM Distinguished Member


What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • The Internet
  • Machine learning

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.

His most cited work include:

  • A survey of mobile phone sensing (1834 citations)
  • SoundSense: scalable sound sensing for people-centric applications on mobile phones (559 citations)
  • The Mobile Sensing Platform: An Embedded Activity Recognition System (520 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Human–computer interaction (27.70%)
  • Artificial intelligence (20.27%)
  • Ubiquitous computing (13.51%)

What were the highlights of his more recent work (between 2016-2021)?

  • Human–computer interaction (27.70%)
  • Intervention (6.08%)
  • Mental health (10.14%)

In recent papers he was focusing on the following fields of study:

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.

Between 2016 and 2021, his most popular works were:

  • CrossCheck: Integrating self-report, behavioral sensing, and smartphone use to identify digital indicators of psychotic relapse. (69 citations)
  • Semi-Automated Tracking: A Balanced Approach for Self-Monitoring Applications (52 citations)
  • Predicting Symptom Trajectories of Schizophrenia using Mobile Sensing (35 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • The Internet
  • Machine learning

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.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

A survey of mobile phone sensing

Nicholas D Lane;Emiliano Miluzzo;Hong Lu;Daniel Peebles.
IEEE Communications Magazine (2010)

2613 Citations

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)

777 Citations

A practical approach to recognizing physical activities

Jonathan Lester;Tanzeem Choudhury;Gaetano Borriello.
international conference on pervasive computing (2006)

740 Citations

The Mobile Sensing Platform: An Embedded Activity Recognition System

T. Choudhury;S. Consolvo;B. Harrison;J. Hightower.
IEEE Pervasive Computing (2008)

736 Citations

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)

687 Citations

A hybrid discriminative/generative approach for modeling human activities

Jonathan Lester;Tanzeem Choudhury;Nicky Kern;Gaetano Borriello.
international joint conference on artificial intelligence (2005)

570 Citations

Bewell: A smartphone application to monitor, model and promote wellbeing

Nicholas Lane;Mashfiqui Mohammod;Mu Lin;Xiaochao Yang.
pervasive computing technologies for healthcare (2011)

440 Citations

StressSense: detecting stress in unconstrained acoustic environments using smartphones

Hong Lu;Denise Frauendorfer;Mashfiqui Rabbi;Marianne Schmid Mast.
ubiquitous computing (2012)

439 Citations

A Scalable Approach to Activity Recognition based on Object Use

Jianxin Wu;A. Osuntogun;T. Choudhury;M. Philipose.
international conference on computer vision (2007)

407 Citations

Mobility detection using everyday GSM traces

Timothy Sohn;Alex Varshavsky;Anthony LaMarca;Mike Y. Chen.
ubiquitous computing (2006)

386 Citations

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Diane J. Cook

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