Behzad Naderalvojoud

Data Scientist
  • Deep Learning
  • Big Data Analytics
  • Information Retrieval
  • Natural Language Understanding

About me

I am a data scientist with 3+ years of experience at Mantis Software Company. I received my Ph.D. degree from the Department of Computer Engineering at Hacettepe University. I am a member of Hacettepe University Multimedia Information Retrieval laboratory (HUMIR). During my academic career, I was immersed in the fields of Information Retrieval, Machine Learning and Text Mining. I also published my works on the imbalanced data problem in machine learning algorithms. I continued my research on sentiment analysis, task-specific word embedding, and deep learning models through national and international academic projects. To make large-scale data processing, I joined international industry-driven R&D&I projects (ITEA/Eureka) and incorporated the academic solutions into the industry problems. My main research goals in this area focus on the health and education problems, such as Health Recommendation Systems, Big Data Analytics, and Social Media Analysis.

Research Interests

Information Retrieval

I have accomplished studies on the term evaluation metrics, imbalanced document indexing, word sense disambiguation, semantic analytics, and lexical search engines. I am also interested in semantic search engines and concept-oriented text retrieval. In some domains, semantic information retrieval plays an important role in providing access to information, such as health and biomedical domain.

Natural Language Understanding

I have studied word semantics, word embeddings, neural language models, probabilistic topic models, sentiment analysis, word sense disambiguation, and text classification. I am also interested in compositional semantics and task-specific/knowledge-based word embeddings.

Deep Learning

In the context of deep learning, I have worked with RNN, CNN, LSTM, and BiLSTM models. My research objective in this area is to exploit different deep models in multistream networks to learn complex events in the text. In addition, I am interested in seq2seq models with encoder-decoder architecture to learn compositional semantics.

Big Data Analytics

In this area, I have studied several distributed Big data analytics systems. I have worked with Solr Search, Elasticsearch, MongoDB, and Cassandra database and also familiar with Hbase, Druid, OpenTSDB, and OrientDB. In addition, I am interested in modern health data monitoring systems with near real-time data processing.

Publications


full list at my Google Scholar Profile


Development of a Framework for Decision Support in Industrial Projects Scheduling, Control and Software Support
  • TÜBİTAK SOBAG 1001 Program
  • Funding Body: The Scientific and Technological Research Council of Turkey
  • Supervisors: Dr. Oncu Hazir and Dr. Klaus Werner Schmidt
  • Duration: 10/2014 – 10/2015
[More]

My main role in this project is to develop a graph-based representation for scheduling and controlling industrial projects.

A Novel Approach to Rule-Based Turkish Sentiment Analysis Using Sentiment Lexicon
  • TÜBİTAK EEEAG 1001 Program
  • Funding Body: The Scientific and Technological Research Council of Turkey (TUBITAK 1001 program)
  • Supervisor: Prof. Dr. Ebru Sezer
  • Duration: 09/2015 – 03/2017
[Web Page] [More]

My main role in this project is to propose a cross-lingual distributional semantic model to create a sense-based sentiment lexicon for Turkish language using bilingual movie subtitles.

Effective and Efficient Parallelization of String Matching Algorithms Using GPGPU Accelerators, Machine Learning, and Big Data Frameworks
  • TÜBİTAK-3501 Program
  • Funding Body: The Scientific and Technological Research Council of Turkey
  • Supervisor: Dr. Adnan ÖZSOY
  • Duration: 05/2018 – 04/2020
[Web Page] [More]

My main role in this project is to incorporate the GPU-based string matching algorithms into word embedding models for non-sequential refining of particular word vectors.

Media News Analysis System
  • Funding Body: Mantis
  • Supervisor: Dr. Güven Köse
  • Duration: 04/2015 – 04/2016
[More]

This project provides a system for the analysis of news in the media.

Journal Citation Reports (JCR) in TRDizin
  • Funding Body: Turkish Academic Network and Information Center (TÜBİTAK ULAKBİM)
  • Supervisor: Prof. Dr. Umut Al
  • During: 06/2019 – 12/2019
[More]

This project provides a journal citation analysis system for TRDizin and implements all standard evaluation metrics for TRDizin journals.

Subject Heading and Subject Term Recommendation in Citation Index Systems
  • Funding Body: Turkish Academic Network and Information Center (TÜBİTAK ULAKBİM)
  • Supervisor: Dr. Güven Köse
  • During: 04/2019 – 04/2020
[More]

In this project, I propose a machine learning based recommendation system for assigning subject headings and subject terms to academic papers to be used in search engines when indexing papers. This system is used in TRDizin.

Citation Network Analysis
  • Funding Body: Turkish Academic Network and Information Center (TÜBİTAK ULAKBİM)
  • Supervisor: Dr. Güven Köse
  • During: 01/2019 – 03/2019
[More]

This project determines academic collaboration networks between authors, countries, institutions, and subject areas using citation and reference information.

Personal Health Empowerment (PHE)
  • ITEA3 Program
  • Funding Body: The Scientific and Technological Research Council of Turkey
  • Project Leader: Gema Maestro Molina (Experis ManpowerGroup, S.L.U., Spain)
  • During: 2018 – 2021
[Web Page] [More]

The main goal of this project is to empower people to monitor and improve their health using personal data and technology-assisted coaching. My role in this project is to propose a data monitoring and analytics architecture for health recommendation systems as well as a data-driven coaching engine to provide intelligent models for recognizing health problems, exacerbations and patients at risk.

POLicy Data Exploitation & Re-use (POLDER)
  • ITEA3 Program
  • Funding Body: The Scientific and Technological Research Council of Turkey
  • Project Leader: Emilio Mulet (Accuro Technology S.l, Spain)
  • During: 2018 – 2022
[Web Page] [More]

This project proposes a hybrid policy-making model based on data-driven, model-driven, and societal-driven sources. My role in this project is to propose a social media monitoring and analytics system using topic-based sentiment analysis models.

Research Fellowship

  • I was awarded a research fellowship for the Collaborative Research Center 991 at Heinrich-Heine University Düsseldorf for 6 months in 2017 (06/2017 – 12/2017).

Best Sentiment Model

  • My proposed lexicon-based neural sentiment model was known as the best model in the GermEval2017: Shared Task on Aspect-based Sentiment in Social Media Customer Feedback,Berlin,Germany (09/2017)

Research Scholarship

  • I was awarded a TÜBİTAK(The Scientific and Technological Research Council of Turkey) research scholarship for 15 months during 05/2018 – 08/2019

Research Scholarship

  • I was awarded a TÜBİTAK research scholarship for 18 months during 09/2015 – 03/2017

Research Scholarship

  • I was awarded a TÜBİTAK research scholarship for a year during 10/2014 – 10/2015