Asif Salekin

Assistant Professor

Electrical Engineering & Computer Science

Degree:

  • Ph.D. in Computer Science, University of Virginia
  • Master of Computer Science, University of Virginia
  • B.S. in Computer Science and Engineering, Bangladesh University of Engineering and Technology

 

 

Research interests:

  • Internet of Things (IoT)
  • Pervasive and Ubiquitous Computing
  • Machine Learning
  • Connected and Mobile Health
  • Cyber-Physical Systems (CPS)

Current Research:

My research takes a multi-disciplinary approach to develop novel and practical human behavioral and physical event sensing technologies that overlap with machine learning, human-centered Computing (e.g., health computing, human-machine interaction, and wellness monitoring applications), internet of things, cyber-physical systems and natural language processing. I enjoy building data-driven, application-specific novel technologies, as well as new systems and applications that involve sensors, mobile devices and cloud services. Research challenges that I deal with are the uncertainties in physical world sensing, human factors, such as, the user-context and mobility, limitation of current technologies, and resource constraints of the sensing data and platform. Technologies and systems that I develop are human-centric, several of them are attributed to health and wellness, and in general, they are in the scope of ubiquitous computing.

Teaching Interests:

  • Design and Analysis of Algorithms

Honors:

  • Graduate Student Award for Outstanding Research, UVA Department of Computer Science, 2018
  • Nominated for Best Paper Award, Wireless Health 2016

Recent Publications:

  • A. Salekin, S. Ghaffarzadegan, Z. Feng and J. Stankovic. A Real-Time Audio Monitoring Framework with Limited Data for Constrained Devices, The 15th International Conference on Distributed Computing in Sensor Systems (DCOSS 2019).
  • A. Salekin, Jeremy W. Eberle, Jeffrey J. Glenn, Bethany A. Teachman, and John A. Stankovic. 2018. A Weakly Supervised Learning Framework for Detecting Social Anxiety and Depression, ACM Interactive, Mobile, Wearable, and Ubiquitous Technologies (IMWUT), Vol. 2, No. 2, Article 81 (June 2018), 26 pages. (and Ubicomp 2018)
  • A. Salekin, Z. Chen, M. Ahmed, J. Lach, D. Metz, K. de la Haye, B. Bell, and J. Stankovic, Distance Emotion Recognition, ACM Interactive, Mobile, Wearable, and Ubiquitous Technologies (IMWUT), Vol. 1, Issue 3, Sept. 2017, 96:1-96:24. (Ubicomp 2017)
  • A. Salekin, H. Wang, K. Williams, and J. Stankovic, DAVE: Detecting Agitated Vocal Events, The IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), July 2017.
  • Z. Chen, M. Ahmed, A. Salekin, and John A. Stankovic, ARASID: Artificial Reverberation-Adjusted Indoor Speaker Identification Dealing with Variable Distances, International Conference on Embedded Wireless Systems and Networks (EWSN), 2019.