Research Students

Mrs Tahani Aljohani

PhD Student

(email at tahani.aljohani@durham.ac.uk)

Biography

Mrs Aljohani is a Ph.D. researcher and a member of the Innovative Computing Group at the Computer Science Department, Durham University. Her primary research interest is Natural Language Processing and Machine Learning for classification/predication tasks based on direct/ indirect supervision learning via deep learning architectures.

Research Interests

  • Natural Language Processing
  • Data Science
  • Machine Learning
  • Deep Learning

Is supervised by

Peter Noble

PhD Student

(email at peter.noble@durham.ac.uk)

Is supervised by

Mr Olanrewaju Tahir Aduragba

PhD Student
Ph.D. Student in the Department of Computer Science

(email at olanrewaju.m.aduragba@durham.ac.uk)

Selected Publications

Conference Proceedings

Aduragba, Olanrewaju T. & Cristea, Alexandra I. (2019), Research on Prediction of Infectious Diseases, their spread via Social Media and their link to Education, Proceedings of the 2019 4th International Conference on Information and Education Innovations – ICIEI 2019. 38.

 

Is supervised by

Mr Charles Murray

PhD student
Postgraduate Student in the Department of Computer Science

(email at c.d.murray@durham.ac.uk)

Is supervised by

Mr Meshal Alharbi

PhD student
PhD Student in the Department of Computer Science

(email at meshal.g.alharbi@durham.ac.uk)

Selected Publications

Journal Article

Show all publications

Is supervised by

Mr Stephen Bonner

PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at s.a.r.bonner@durham.ac.uk)

Personal Information

Stephen is a PhD student in the Department of Computer Science at Durham University. He completed a Masters by research creating a semantic based Hadoop query system for NHS data. Currently he is working on the field of Graph Embeddings using machine learning.

He has experience teaching Object Orientated Programming, Parallel Computer Architectures, Digital Signal Processing and Software Engineering at undergraduate level. He also has worked as a High Performance Computing system administrator.

Research Interests

  • Big Data Related Technologies
  • Deep Learning
  • Graph Embeddings
  • High Performance Computing
  • Machine Learning
  • Network Science

Teaching Areas

  • COMP2201 – Group Project
  • COMP2191 – Software Engineering

Selected Publications

Journal Article

Chapter in book

  • Bonner, SBrennan, JKureshi, I & Theodoropoulos, G (2017). Exploring The Evolution of Big Data Technologies. In Software Architecture for Big Data and the Cloud. Elsevier.

Conference Paper

Show all publications

Is supervised by

Mr John Brennan

PhD student
PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at j.d.brennan@durham.ac.uk)

John Brennan is currently a PhD candidate at the School of Engineering and Computing Sciences at Durham University. His main research interests are Big Data analytics, complex network analytics, energy efficiency in large systems and computational resource scheduling. He received a BEng in Electronic Engineering and Computer Systems in 2012, followed by an MSc in Computer Science in 2014, from the University of Huddersfield.

Selected Publications

Journal Article

Conference Paper

Show all publications

Is supervised by

Mrs Latifah Almuqren

PhD student

Mrs Laila Alrajhi

PhD student

My name is Laila a Ph.D. researcher at the Innovative Computing Research Group, Computer Science Department, Durham University, U.k.

Research Interests:
• Machine Learning and Deep Learning.
• Natural Language Processing.
• Instructor Intervention in MOOC Environment.
Selected Publications:
Posters:

• Participate with poster in (Liverpool Early Career Researcher Conference 2019) with title ‘Classification of Instructor Intervention in MOOC Environment’.

Postgraduate Student in the Department of Computer Science

Contact Mrs Laila Alrajhi

Is supervised by

Ms Aljawharah Alnasser

PhD student

Mr Mohammed Alatiyyah

PhD student
Postgraduate Student in the Department of Computer Science
Room number: E2.0 (Christopherson Building)

(email at mohammed.h.alatiyyah@durham.ac.uk)

Is supervised by

Miss Muna Almushyti

PhD student

Mrs Latifah Abduh

PhD student

Miss Xin Zhang

PhD student
Postgraduate Student in the Department of Computer Science

(email at xin.zhang3@durham.ac.uk)

Is supervised by

Mr Pedro Cardenas

PhD student
PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at pedro.cardenas-canto@durham.ac.uk)

Research Interests

  • Deep learning
  • Machine Learning
  • Natural language processing

Is supervised by

Ms Amani Alsaqqaf

PhD student
Postgraduate Student in the Department of Computer Science
Room number: E2.0 (Christopherson Building)

(email at amani.z.alsaqqaf@durham.ac.uk)

Is supervised by

Ms Aeshah Almutairi

PhD student
PhD Student in the Department of Computer Science
Room number: E280

(email at aeshah.a.almutairi@durham.ac.uk)

Is supervised by

Mr Abdullah Sheikh

PhD student
Postgraduate Student in the Department of Computer Science

(email at abdullah.sheikh@durham.ac.uk)

Is supervised by

Mrs Aishah Alsehaim

PhD student

Mr Penghui Bu

PhD student

Mr Philip Adey

PhD student

Mr Will Prew

PhD student
PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 42530
Room number: E2.0 (Christopherson Building)
Postgraduate student in the Department of Engineering

(email at william.t.prew@durham.ac.uk)

Research Groups

Department of Psychology

Research Interests

  • Deep Learning
  • Computational Neuroscience
  • Robotics

Is supervised by

Ms Bruna Maciel-Pearson

PhD student
PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at b.g.maciel-pearson@durham.ac.uk)

Research Interests

  • Computer Vision
  • Machine learning
  • Robotic sensing
  • Transfer Learning

Teaching Groups

  • EDIC

Selected Publications

Conference Paper

Show all publications

Is supervised by

Mr Joshua Podmore

PhD student

Mr Naif Alshammari

PhD student
PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at naif.alshammari@durham.ac.uk)

Biography

Naif Alshammari is PhD student working on the challenging topic of automotive scene understanding under extreme variations in environmental conditions such as varying illumination and adverse weather. His research makes use of a range of varying approaches, spanning both illumination invariant image transformation and contemporary convolutional network approaches within the challenging real-time demands of automotive computer vision to support future vehicle autonomy. His aims to address key sensing challenges aimed towards future all-condition (i.e. illumination and weather invariant) road vehicle autonomy in terms of both effective semantic scene understanding and 3D environmental awareness under such adverse conditions.

Research Interests

  • Computer Vision (object detection and segmentation)
  • Machine Learning (deep learning)

Selected Publications

Conference Paper

Show all publications

Is supervised by

Mrs Shuaa Alharbi

PhD student
PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at shuaa.s.alharbi@durham.ac.uk)

Is supervised by

Mr Amir Atapour-Abarghouei

PhD student
PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at amir.atapour-abarghouei@durham.ac.uk)

Resaerch Interests:

  • Image Processing and Computer Vision
  • Depth Image Inpainting
  • Monocular Depth Estimation
  • Machine Learning and Neural Networks

Publications

  • 1: Atapour-Abarghouei, A. & Breckon, T.P. (2017), DepthComp: Real-time Depth Image Completion Based on Prior Semantic Scene Segmentation28th British Machine Vision Conference (BMVC) 2017. London, British Machine Vision Association (BMVA).
  • 2: Atapour-Abarghouei, A., de La Garanderie, G. P. & Breckon, T. P. (2016), Back to Butterworth-a Fourier basis for 3D surface relief hole filling within RGB-D imagery, International Conference on Pattern Recognition. Cancun, Mexico, IEEE, 2813-2818.
  • 3: Ghanizadeh, A., Atapour-Abarghouei, A., Sinaie, S., Saad, P. & Shamsuddin, S.M. (2011). Iris segmentation using an edge detector based on fuzzy sets theory and cellular learning automata. Applied optics 50: 19, 3191-3200.
  • 4: Erfani, M., Ghanizadeh, A., Atapour-Abarghouei, A., Sinaie, S. & Shamsuddin, S.M. (2010), A Modified PSO Method Enhanced with Fuzzy Inference System for Solving the Planar Graph Coloring Problem, International Conference on Artificial Intelligence. 160-165.
  • 5: Ghanizadeh, A., Sinaie, S., Atapour-Abarghouei, A., Mozafari, E. & Shamsuddin, S.M. (2010), A Robust Fuzzy and Cellular Learning Automata Edge Detection and Enhancement Method, International Conference on Image Processing, Computer Vision, & Pattern Recognition. Las Vegas, Nevada, 551-556.
  • 6: Atapour-Abarghouei, A., Ghanizadeh, A., Sinaie, S. & Shamsuddin, S.M. (2009), A survey of pattern recognition applications in cancer diagnosis, International Conference on Soft Computing and Pattern Recognition. IEEE, 448-453.
  • 7: Atapour-Abarghouei, A., Ghanizadeh, A. & Shamsuddin, S. M. (2009). Advances of Soft Computing Methods in Edge DetectionInternational Journal of Advanced Computer Science and Applications 1(2): 162-203.
  • Atapour-Abarghouei, Amir & Breckon, Toby P. (2018), Extended Patch Prioritization for Depth Filling Within Constrained Exemplar-Based RGB-D Image Completion, in Campilho, Aurélio, Karray, Fakhri & Romeny, Bart ter Haar eds, Lecture Notes in Computer Science 10882International Conference Image Analysis and Recognition. Póvoa de Varzim, Portugal, Springer, 306-314.

Is supervised by

Mr Philip Jackson

PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at p.t.g.jackson@durham.ac.uk)

Research Interests

  • Computer Vision
  • Image Processing
  • Machine Learning

Is supervised by

Mrs Haifa Alhasson

PhD student
PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at h.f.alhasson@durham.ac.uk)

PhD Research

BioImage Informatics for Spatio – Temporal Biological Networks

My research is aimed at developing ,validating and disseminating image informatics solutions to extract the architecture and dynamics of structural biological networks from 2D time-series, 3D, and 3D time-series biological images.

Qualifications

MSc in Computer Science from King Saud University , Riyadh ,Saudi Arabia.

Research Interests

  • Image Processing
  • Image Analysis
  • Bioimage Informatics
  • Satellite images analysis

Is supervised by

Miss Cigdem Sazak

PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at cigdem.sazak@durham.ac.uk)

Research Interests

  • Image Analysis
  • Image Enhancement
  • Image Processing

Teaching Areas

  • Computer System (8 hours/year.)
  • Programming Paradigms (6 hours/year.)
  • Software, Systems and Applications III (4 hours/year.)

Selected Publications

Conference Paper

Conference Proceeding

  • (2014). Mobile Device Application For Speech Therapy. The International conference on Applied Informatics for Health and Life Sciences in conjunction with Turkish-German Workshop on Bioinformatics: Recent Developments from Health to NanoTechnology, Izmir-Turkey.

Show all publications

Is supervised by

Mr Amit Gajbhiye

PhD student
PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at amit.gajbhiye@durham.ac.uk)

I am a PhD candidate at Durham University, UK. Doctoral Researcher with a demonstrated history of working in the higher education and software development industry (3 Years). Skilled in Natural Language Processing, Machine Learning, Deep Learning, Keras (Deep Learning Library), Python (Programming Language) and Linux.

Is supervised by

Mr Thomas Winterbottom

PhD student

Mr Dean Slack

PhD student
Postgraduate Student in the Department of Computer Science

(email at dean.l.slack@durham.ac.uk)

Research Interests

  • Deep Learning
  • Natural Language Processing

Is supervised by

Mr Matthew Poyser

PhD student

Mr Jack Barker

PhD student
Postgraduate Student in the Department of Computer Science

Contact Mr Jack Barker

Research Interests

  • Computer Vision
  • Deep Learning
  • Machine Learning

Is supervised by

Mr Amit Gajbhiye

PhD student
PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at amit.gajbhiye@durham.ac.uk)

Is supervised by

Mr Zakhriya Alhassan

PhD student
PhD Student in the Department of Computer Science
Room number: E280

(email at zakhriya.n.alhassan@durham.ac.uk)

Selected Publications

  • 1: Alhassan, ZakhriyaBudgen, David, Alshammari, Riyad, Daghstani, Tahani, McGough, A. Stephen & Al Moubayed, Noura (2018), Stacked Denoising Autoencoders for Mortality Risk Prediction Using Imbalanced Clinical Data, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA). Orlando, FL, USA.
  • 2: Alhassan, Zakhriya, McGough, Stephen, Alshammari, Riyad, Daghstani, Tahini, Budgen, David & Al Moubayed, Noura (2018), Type-2 Diabetes Mellitus Diagnosis from Time Series Clinical Data using Deep Learning Models, Lecture Notes in Computer Science International Conference on Artificial Neural Networks (ICANN). Rhodes, Greece, Springer.
  • 3: Alessa, Ali, Faezipour, Miad & Alhassan, Zakhriya (2018), Text Classification of Flu-Related Tweets Using FastText with Sentiment and Keyword Features, 2018 IEEE International Conference on Healthcare Informatics (ICHI). New York, NY, USA.

Show all publications

Is supervised by

Ms Nik Khadijah Nik Aznan

PhD student
PhD Student in the Department of Computer Science
Postgraduate student in the Department of Engineering

(email at nik.k.nik-aznan@durham.ac.uk)

Personal Information

Nik Khadijah is a PhD student in the School of Engineering and Computer Science and is collaborating with the Department of Psychology at Durham University. She completed a Masters degree in Engineering focused on the classification of motor imagery-based BCI (Brain Computer Interface). Currently, she is working on BCI applications by using Video interpretation as SSVEP Stimuli.

Research Interests

  • Artificial Intelligence
  • Brain-Computer Interface Application
  • Humanoid Robot
  • Machine Learning

Publications

Journal Article

Chapter in book

Conference Paper

Is supervised by

Mr Amar Vijai Nasrulloh

Research Associate
PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at amar.v.nasrulloh@durham.ac.uk)

Research Interests

  • 3D Image Segmentation

Is supervised by

Mr Samet Akcay

PhD student
PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at samet.akcay@durham.ac.uk)

Biography

Samet Akcay is a third year Ph.D. Student in the Department of Computer Science at Durham University, UK. He received his MSc degree from the Department of Electrical Engineering at Penn State University, USA. His primary research interests are real-time image classification/detection, anomaly detection, unsupervised feature learning via deep/machine learning algorithms.

Education

  • PhD – Durham University, UK, 2015 – 2019 (Expected)
  • MSc – Penn State University, US, 2013-2015
  • BSc – Gazi University, TR, 2007-2011

Research Interests

  • Real Time Object Detection
  • Deep Learning
  • Machine Learning
  • Computer Vision

Selected Publications

Journal Article

  • Akcay, S, Kundegorski, ME, Willcocks, CG & Breckon, TP (Accepted). Using Deep Convolutional Neural Network Architectures for Automated Object Detection and Classification within X-ray Baggage Security Imagery. IEEE Transactions on Information Forensics and Security

Conference Paper

Show all publications

Is supervised by

Mr Grégoire Payen de La Garanderie

PhD student
PhD Student in the Department of Computer Science
Telephone: +44 (0) 191 33 41736
Room number: E289

(email at gregoire.p.payen-de-la-garander@durham.ac.uk)

Biography

I am a Computer Science PhD student in my final year of study at Durham University. Prior, I worked as a Graduate Research Engineer at Imagination Technologies. I received a MSc from Cranfield University in 2013. I work on situational awareness for autonomous driving. My primary research interests are centered around perception for self-driving vehicles, computer vision, machine learning and more specifically deep learning, object detection and tracking, visual question answering and related challenges. This project is sponsored by Jaguar Land Rover and EPSRC.

Research Interests

  • Computer Vision
  • Deep Learning
  • Image Processing
  • Machine Learning

Selected Publications

Chapter in book

Conference Paper

Show all publications

Is supervised by

Mr Henry Westmacott

PhD student

I am a 1st year PhD student in computer science at Durham University. Currently researching methods for enhanced diagnostic output and performance from the gridless scatter correction system in development by IBEX Innovations Ltd.

Is supervised by

Mr Mohammad Alshehri

PhD student
Postgraduate Student in the Department of Computer Science
Room number: E2.0 (Christopherson Building)

Contact Mr Mohammad Alshehri (email at mohammad.a.alshehri@durham.ac.uk)

Bio

I am a PhD Candidate at the Innovative Computing research group at the Computer Science Department, Durham University. My research interests span MOOCs learners analytics, learners behaviour and educational data mining.

Is supervised by

Mr Jialin Yu

PhD student

Postgraduate Student in the Department of Computer Science

I am a first year PhD student at Durham University under the supervision of Professor Alexandra and I started my PhD since February 2019. My current research interest lies in the fields between computer science and statistical science.

Contact Mr Jialin Yu

Is supervised by

Mr Ahmed Alamri

PhD Student

Mr Ahmed Alamri

Postgraduate Student in the Department of Computer Science

 

I am a PhD student at Durham University under the supervision of Dr Alexandra .I joined the Innovative Computing Group in October 2017. My background is in computer science whereas my current research lies at data mining and learner analytics. In 2015 I obtained my master’s degree from Nottingham Trent University. The main field of study Software engineering , System science and IT.

Publications

Conference Paper

1. Ahmed Alamri, Mohammad Alshehri, Alexandra Cristea, Filipe D. Pereira, Elaine Oliveira, Lei Shi and Craig Stewart. ” Predicting MOOCs Dropout Using only two easily obtainable Features from the First Week’s Activities.” In International Conference on Intelligent Tutoring Systems, Springer, Kingston, Jamaica, 2019. Core A

2. Alamri A, Rusby H, Cristea AI, Kayama M, Khan J, Shi L, Stewart C. An Intuitive Authoring System for a Personalised, Social, Gamified, Visualisation-supporting e-learning System. InProceedings of the 2018 The 3rd International Conference on Information and Education Innovations 2018 Jun 30 (pp. 57-61). ACM.

3. Cristea, A. I., Alamri, A., Kayama, M., Stewart, C., Alshehri, M., & Shi, L. (2018). Earliest predictor of dropout in MOOCs: a longitudinal study of FutureLearn courses. In 27th International Conference on Information Systems Development (ISD2018), Lund, Sweden (Vol. 22). Core A

4. Cristea, A. I., Alshehri, M., Alamri, A., Kayama, M., Stewart, C., & Shi, L. (2018, August). How is learning fluctuating? FutureLearn MOOCs fine-grained temporal analysis and feedback to teachers and designers. In 27th International Conference on Information Systems Development (ISD2018), Lund, Sweden (Vol. 22). Core A

5. Filipe D. Pereira1 , Elaine Oliveira2 , Alexandra Cristea3 , David Fernandes2 , Luciano Silva1 , Gene Aguiar1 , Ahmed Alamri3 , and Mohammad Alshehri3. “Early Dropout Prediction for Programming Courses supported by Online Judges .” The 2019 conference on Artificial Intelligence in Education (AIED) Core A

6. Cristea, A. I., Alshehri, M., Alamri, A., Kayama, M., Stewart, C., & Shi, L. (2018, August). How is learning fluctuating? FutureLearn MOOCs fine-grained temporal analysis and feedback to teachers and designers. In 27th International Conference on Information Systems Development (ISD2018), Lund, Sweden (Vol. 22). Core A

7. Alshehri, M., Foss, J., Cristea, A. I., Kayama, M., Shi, L., Alamri, A., & Tsakalidis, A. (2018, June). On the need for fine-grained analysis of Gender versus Commenting Behaviour in MOOCs. In Proceedings of the 2018 The 3rd International Conference on Information and Education Innovations (pp. 73-77). ACM.

8. Khan, Javed, Alexandra I. Cristea, and Ahmed Alamri. “A Large-Scale Category-Based Evaluation of A Visual Language for Adaptive Hypermedia.” Proceedings of the 2018 The 3rd International Conference on Information and Education Innovations. ACM, 2018.

Journal articles

1. , Alamri, A., Alshehri, M., Cristea, A. I., Pereira, F., Oliveira, E., Shi, L., & Stewart, C(2019, April). Early Prediction of Dropout in MOOCs based on a few Features. Interactive Learning Environments (ILE), (will be submitted)

2. Alshehri, M., Alamri, A., Pereira, F., Cristea, A. I., Toda, A., Oliveira, E., Shi, L., & Stewart, C (2018, November). Exploration of the effect of engagement on short-term and long-term student success for MOOCs. IEEE Transactions on Learning Technologies (TLT), (will be submitted)

 

 

 

 

 

Contact Mr Ahmed Alamri

Is supervised by

 

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