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Dr Belfrit Victor Batlajery

Industrial Research Fellow (Impact Lab)

 (+44) 7780 225436

 Environmental Futures & Big Data Impact Lab Innovation Centre Phase 1 H1

 

Upper Richardson, Exeter Science Park, EX5 2FS

 Office hours:

Mon - Fri: 9.00 - 16.00

Overview

I am an Industrial Research Fellow at the University of Exeter, UK. I'm delivering research-based projects to local SMEs in the area of data analytics. I work collaboratively with the local businesses with a set of deep learning and graph techniques.

Qualifications

  • University of Southampton - Phd in Computer and Information Sciences
  • University of Utrecht - Master of Business Informatics
  • Universitas Kristen Duta Wacana - First Degree in Informatics Engineering

Links

Research

Research interests

  1. Provenance
  2. Semantic Web
  3. Graph analytics
  4. Data analytics

Research projects

  • Visualization of complex configuration items

    A configuration management solution software is a software that helps users understand and manage the configuration of complex software systems, including dependency analysis, reporting, transport, revision control and comparison. The project will aim to explore means of implementing interactive graph visualisation that will allow users to meaningfully and usefully interact with the graph. Both the visualisation from the point of view of the whole graph or a single item will be explored. The goal will be to allow users to decrease and increase the amount of detail shown based on their need by grouping items together using contextual grouping mechanisms that preserve the maximum amount of useful information while obscuring unnecessary detail. Also, the project may allow us to perform graph analysis or other machine learning techniques on the configuration.

     

  • Clothes recommendation and body shape classification

    A new business intends to provide online personal styling advice to enable their users to make more informed and sustainable shopping decisions. It is expected that the services will contribute towards the reduction of fashion waste as people only purchase what really suits them. The project is aimed at achieving two things: 1) Developing a system that provides style, color and brand advice to users, based on the characteristics (such as body shape, budget and color features) of the users. 2) Building an approach that can be used to classify users as having one of the different body shapes.
    Domain: Data Science, Artificial Intelligent, Computer Vision, Deep Learning

     

  • Table detection in an unstructured document

    A company provides a service to analyze their clients’ documents and provides them with more insight into their data. They have the vision to eliminate manual laborious and repetitive tasks; hence, they want to automatically extract specific metrics from a set of documents. Those metrics are lying sporadically on the unstructured documents, which makes them challenging to be extracted; But, most of those metrics are often appears inside the tables of the documents. Thus, a project is set to identify tables on the unstructured documents.
    Domain: Data Science, Graph Neural Network, Deep Learning

     

  • Topics dependencies in math

    An online platform has developed a directed graph database of topics in math subject. Each of the topics is labelled with an associated difficulty level, and with dependencies between them determined through expert judgement. Treating these as hypothesised dependencies, the aim of the project is to find ways to collect and analyse data, generated through users’ use of the system, and to validate these dependencies between topics.
    Domain: Data Science, Bayesian Network, Graph Analytics

     

  • Brand recognition in a video

    A fan-based video company provides an online platform where their users can upload videos through their mobile phone while attending a public or private event (e.g. music concert, sport match, etc.). Those videos are curated into a new film out of all the uploaded video clips in an event. To extend their business, they intend to develop a new feature that is a brand/logo detection on the uploaded clips.

Publications

Key publications | Publications by category | Publications by year

Publications by category


Journal articles

Moreau L, Batlajery BV, Huynh TD, Michaelides D, Packer H (In Press). A Templating System to Generate Provenance—Supplementary Material—.
Brown PC, Batlajery BV, Weal M, Karim F, Al Naameh O (In Press). ICSC 2018.
Batlajery BV (In Press). Scenario-Based Requirement Analysis.
Moreau L, Batlajery BV, Huynh TD, Michaelides D, Packer H (2017). A templating system to generate provenance. IEEE Transactions on Software Engineering, 44, 103-121.
Moreau L, Batlajery B, Huynh T, MICHAELIDES DT, Packer H, others (2016). Prov-template evaluation dataset.
Batlajery BV, Susanto B, Krisnawati L (2011). Implementasi Rdf Untuk Anotasi Halaman Web. Jurnal Informatika, 4

Conferences

Batlajery BV (2021). Modeling and generating marketplace activities with PROV-DM. 2021 4th International Conference on Artificial Intelligence for Industries (AI4I).
Batlajery BV, Weal M, Chapman A, Moreau L (2018). Belief Propagation Through Provenance Graphs.
Batlajery BV, Weal M, Chapman A, Moreau L (2018). prFood: Ontology principles for provenance and risk in the food domain.
Khadka R, Batlajery BV, Saeidi AM, Jansen S, Hage J (2014). How do professionals perceive legacy systems and software modernization?.

Publications by year


In Press

Moreau L, Batlajery BV, Huynh TD, Michaelides D, Packer H (In Press). A Templating System to Generate Provenance—Supplementary Material—.
Brown PC, Batlajery BV, Weal M, Karim F, Al Naameh O (In Press). ICSC 2018.
Batlajery BV (In Press). Scenario-Based Requirement Analysis.

2021

Batlajery BV (2021). Modeling and generating marketplace activities with PROV-DM. 2021 4th International Conference on Artificial Intelligence for Industries (AI4I).

2018

Batlajery BV, Weal M, Chapman A, Moreau L (2018). Belief Propagation Through Provenance Graphs.
Batlajery BV, Weal M, Chapman A, Moreau L (2018). prFood: Ontology principles for provenance and risk in the food domain.

2017

Moreau L, Batlajery BV, Huynh TD, Michaelides D, Packer H (2017). A templating system to generate provenance. IEEE Transactions on Software Engineering, 44, 103-121.

2016

Moreau L, Batlajery B, Huynh T, MICHAELIDES DT, Packer H, others (2016). Prov-template evaluation dataset.

2014

Khadka R, Batlajery BV, Saeidi AM, Jansen S, Hage J (2014). How do professionals perceive legacy systems and software modernization?.
Batlajery B, Khadka R, Saeidi A, Jansen S, Hage J (2014). Industrial perception of legacy software system and their modernization. Technical Report Series

2013

Victor B (2013). Revisiting legacy systems and legacy modernization from the industrial perspective.

2011

Batlajery BV, Susanto B, Krisnawati L (2011). Implementasi Rdf Untuk Anotasi Halaman Web. Jurnal Informatika, 4

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