Sara Sharifzadeh

Dr

  • 41 Citations
  • 3 h-Index
20122018
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Personal profile

Biography

Dr Sara Sharifzadeh completed his PhD study in Computer Science  in Technical University of Denmark, Department of applied Mathematics and Computer Science in 2015. Upon Completion of her PhD, she started her new career as Research Associate in Data Science at Loughborough University. She joined Coventry University in 2018 as a Lecturer in the School Computing, Electronics and Mathematics.

During her study and research career, Dr Sharifzadeh was involved in several industrial research projects funded by EPSRC and Danish Council for Strategic Research and industrial partners. Her main areas of research include signal/image analysis, machine learning, artificial intelligence and 3D point cloud data analysis.

Research Interests

  • Signal, image and video analysis
  • Multivariate data analysis
  • Machine learning
  • Artificial Intelligence (AI)
  • Spectral signal/image analysis
  • 3D point cloud data analysis
  • Robotics
  • Embedded systems

 

Education/Academic qualification

Computer Science, Doctorate, Technical University of Denmark

20112015

Multimedia Technologies, MSc, Autonomous University of Barcelona

20092010

Electronics Engineering, MSc

20042007

Electronics Engineering, Degree

19992002

Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

Inspection Engineering & Materials Science
Robotics Engineering & Materials Science
Robots Engineering & Materials Science
Robot learning Engineering & Materials Science
Torque measurement Engineering & Materials Science
Principal component analysis Engineering & Materials Science
discrete cosine transform Physics & Astronomy
milk Physics & Astronomy

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

Research Output 2012 2018

  • 41 Citations
  • 3 h-Index
  • 6 Conference proceeding
  • 5 Article
  • 2 Poster

Abnormality detection strategies for surface inspection using robot mounted laser scanners

Sharifzadeh, S., Biro, I., Lohse, N. & Kinnell, P. May 2018 In : Mechatronics. 51, p. 59-74 16 p.

Research output: Contribution to journalArticle

Open Access
File
Inspection
Robots
Lasers
Geometry
Surface measurement
4 Citations

Sparse supervised principal component analysis (SSPCA) for dimension reduction and variable selection

Sharifzadeh, S., Ghodsi, A., Clemmensen, L. H. & Ersbøll, B. K. 1 Oct 2017 In : Engineering Applications of Artificial Intelligence. 65, p. 168-177 10 p.

Research output: Contribution to journalArticle

Principal component analysis
Labels
Processing
Feature extraction
Decomposition

Learning Industrial Robot Force/torque Compensation: A Comparison of Support Vector and Random Forests Regression

Al-Yacoub, A., Sharifzadeh, S., Lohse, N., Usman, Z., Goh, Y. M. & Jackson, M. 2016 (846) Telehealth and Assistive Technology / 847: Intelligent Systems and Robotics - 2016.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Robot learning
Torque measurement
Force measurement
Torque
Robots

Robust Surface Abnormality Detection for a Robotic Inspection System

Sharifzadeh, S., Biro, I., Lohse, N. & Kinnell, P. 10 Nov 2016 In : IFAC-PapersOnLine. 49, 21, p. 301-308 8 p.

Research output: Contribution to journalArticle

File
Robotics
Inspection
Lasers
Classifiers
Robots

The evaluation of a multi-sensor robotic visual inspection system

Biro, I., Sharifzadeh, S., Tailor, M., Kinnell, P. & Jackson, M. 2016 Proceedings of the 16th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2016. euspen

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

robotics
inspection
Robotics
Inspection
scanners