Senem Velipasalar

Personal profile

Research interests

Dr. Velipasalar’s primary areas of research are embedded computer vision, mobile camera applications and wireless embedded smart cameras, which combine sensing, processing and communication on a single embedded platform. Dr. Velipasalar has been working on designing resource-efficient algorithms that are suitable for embedded platforms, fall detection, step counting and activity classification with wearable cameras, traffic light detection and alert signal detection with vehicle-mounted cameras, distributed target detection and tracking across overlapping and non-overlapping cameras, and resource allocation strategies and detection of events of interest on embedded smart cameras. Potential uses include military surveillance, public transportation, health care and elder care, traffic systems, and industrial and retail applications.

Education

Electrical Engineering, PhD, Princeton University

… → 2007

Electrical Engineering, MA, Princeton University

… → 2004

Electrical Sciences and Computer Engineering, MS, Brown University

… → 2001

Electric & Electronics Engineering, BS, Bogazici University

… → 1999

Fingerprint Dive into the research topics where Senem Velipasalar is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

11 Similar Profiles

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects

6 Active
10 Finished

Deep InSight: Deep Extraction of Driver State from Naturalistic Driving Dataset

Velipasalar, S.

United States Dept of Transportation - Federal Aviation Administration, Iowa State University

8/20/19 → 8/19/22

Project: Research project

Aerial Intelligence for Retrofit Building Energy Modeling (AirBEM)

Velipasalar, S. & Bogucz, E. A.

Department of Energy - National Nuclear Security Administration, Georgia Institute of Technology

8/1/19 → 7/31/22

Project: Research project

Reliable Perception and Control for UAV Navigation in 3D Space

Qiu, Q., Sanyal, A. & Velipasalar, S.

Semiconductor Research Corporation

5/1/19 → 4/30/22

Project: Research project

CHS:Small: Improved Cross-Subject Cognitive and Emotional State Classification Using Functional Near-Infrared Spectroscopy Data for Deep Learning

Velipasalar, S. & Hirshfield, L. M.

National Science Foundation

8/15/18 → 7/31/21

Project: Research project

MicroCam: A Low Power and Privacy Preserving Multi-modal Sensor Platform for Occupancy Detection and Counting

Velipasalar, S., Isik, C., Rakha, T. & Varshney, P. K.

Advanced Research Projects Agency - Energy

5/15/18 → 5/14/21

Project: Research project

Research Output

1358 Citations
20 h-Index
101 Conference contribution
39 Article
5 Chapter
1 Book
2 More
- 1 Editorial
- 1 Patent

3D Capsule Networks for Object Classification from 3D Model Data

Ahmad, A., Kakillioglu, B. & Velipasalar, S., Feb 19 2019, Conference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018. Matthews, M. B. (ed.). IEEE Computer Society, p. 2225-2229 5 p. 8645256. (Conference Record - Asilomar Conference on Signals, Systems and Computers; vol. 2018-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Actor-critic deep reinforcement learning for dynamic multichannel access

Zhong, C., Lu, Z., Gursoy, M. C. & Velipasalar, S., Feb 20 2019, 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 599-603 5 p. 8646405. (2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Classification of affect using deep learning on brain blood flow data

Bandara, D., Hirshfield, L. M. & Velipasalar, S., Jan 1 2019, In : Journal of Near Infrared Spectroscopy.

Research output: Contribution to journal › Article

Deep learning based power control for quality-driven wireless video transmissions

Ye, C., Gursoy, M. C. & Velipasalar, S., Feb 20 2019, 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 574-578 5 p. 8646470. (2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Deep Multi-Agent Reinforcement Learning Based Cooperative Edge Caching in Wireless Networks

Zhong, C., Gursoy, M. C. & Velipasalar, S., May 1 2019, 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 8762084. (IEEE International Conference on Communications; vol. 2019-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution