Dr. Anna Wróblewska | Word Embedding | Best Researcher Award

Dr. Anna Wróblewska | Word Embedding | Best Researcher Award 

Dr. Anna Wróblewska, Warsaw Univeristy of Technology, Poland

Anna Wróblewska is an Assistant Professor at the Warsaw University of Technology and a Senior Data Scientist at Applica.ai. With extensive experience in designing intelligent systems and semantic data analysis, she has led multiple R&D projects in text mining, image recognition, and model interpretability. Previously, she worked at Allegro, Eastern Europe’s largest e-commerce marketplace, specializing in intelligent data analysis methods. She has authored over 50 publications in Polish and international journals. Her research focuses on practical applications of machine learning, particularly semantic data understanding, modeling, and interpretability.

Professional Profile:

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Summary of Suitability for Best Researcher Award

Anna Wróblewska is a highly accomplished researcher with extensive experience in designing intelligent systems and analyzing semantic data in both commercial and scientific settings. As an assistant professor at the Warsaw University of Technology and a senior data scientist at Applica.ai, she has led multiple R&D projects in text mining, image recognition, and model diagnostics. Her expertise in machine learning, particularly in semantic understanding, data modeling, and interpretability, is well demonstrated through her contributions to various high-impact publications. With over 50 research articles in renowned Polish and international journals, she has made significant advancements in multimodal data fusion, document analysis, and medical imaging.

🎓 Education:

  • Holds a Ph.D. in Computer Science (specific university details not provided).
  • Specializes in intelligent systems, semantic data processing, and machine learning.

💼 Work Experience:

  • Assistant Professor at Warsaw University of Technology 🏫
    • Focuses on machine learning, semantic data modeling, and AI applications.
  • Senior Data Scientist at Applica.ai 🤖
    • Oversees R&D projects in text mining, image recognition, and model interpretability.
  • Former Data Scientist at Allegro 🛒
    • Worked on intelligent data analysis in Eastern Europe’s largest e-commerce platform.

🏆 Achievements & Contributions:

  • Published 50+ research papers in Polish and international journals 📄
  • Expert in machine learning for practical applications, especially in semantic understanding and AI model interpretability 🎯
  • Leading multiple AI-driven research projects in academia and industry 🔬

🎖 Awards & Honors:

  • Recognized as a leading researcher in AI & Data Science 🏅
  • Contributions in text mining, image recognition, and AI explainability earned industry recognition 🏆
  • Speaker at various AI & machine learning conferences 🎤

Publication Top Notes:

Kleister: key information extraction datasets involving long documents with complex layouts

CITED:132

Effective techniques for multimodal data fusion: A comparative analysis

CITED:63

Segmentation and feature extraction for reliable classification of microcalcifications in digital mammograms

CITED:60

GEval: Tool for debugging NLP datasets and models

CITED:39

Named Entity Recognition–Is there a glass ceiling?

CITED:37

 

 

Prof Dr. Ersin Elbasi | Machine learning Award | Excellence in Research

Prof Dr. Ersin Elbasi | Machine learning Award | Excellence in Research

Prof Dr. Ersin Elbasi, American University of the Middle East, Kuwait 

Ersin Elbasi, Ph.D., is a distinguished professor specializing in Computer Science and Engineering, currently serving at the American University of the Middle East in Kuwait. He earned his Ph.D. in Computer Science from the Graduate Center, CUNY, with a dissertation on robust video watermarking schemes, following a Master of Philosophy in the same field from the same institution. He holds a Master of Science in Electrical Engineering and Computer Science from Syracuse University and a Bachelor of Science in Industrial Engineering from Sakarya University, Turkey. Dr. Elbasi’s extensive academic career includes previous positions as Associate Professor at the American University of the Middle East and faculty roles at the Higher Colleges of Technology in the UAE and Çankaya University in Turkey. His research focuses on machine learning, multimedia security, and data mining, with notable projects in digital image and video watermarking and event mining in video sequences. He has also held significant roles in research and development at TÜBİTAK, contributed to SQL application development in New York City, and engaged in various international research activities. Dr. Elbasi’s technical expertise spans Visual C++, SQL programming, and Java, with a notable scholarship record and recognition for his contributions to the field.

Professional Profile:

Summary of Suitability for Excellence in Research 

Dr. Ersin Elbasi holds a Ph.D. in Computer Science from the Graduate Center, CUNY, with a specialization in robust video watermarking schemes in transform domains. His advanced degrees in computer science, electrical engineering, and industrial engineering demonstrate a strong interdisciplinary foundation.

Education

  • Ph.D. in Computer Science
    Graduate Center, CUNY, New York City, NY
    Graduated: April 2007
    Dissertation: “Robust Video Watermarking Scheme in Transform Domains”
  • Master of Philosophy in Computer Science
    Graduate Center, CUNY, New York City, NY
    Graduated: May 2006
  • Master of Science in Electrical Engineering & Computer Science
    Syracuse University, Syracuse, NY
    Graduated: May 2001
  • Bachelor of Science in Industrial Engineering
    Sakarya University, Sakarya, Turkey
    Graduated: June 1997

Work Experience

  • Professor
    American University of the Middle East (QS ranking 500-600), Kuwait
    June 2022 – Current
  • Associate Professor
    American University of the Middle East (QS ranking 500-600), Kuwait
    October 2016 – June 2022

    • Taught courses including CNIT 180, CNIT 280, CNIT 380, CNIT 315, CS 159, CNIT 480, CNIT 372, CNIT 399/499, TECH 330, and TECH 320.
  • Faculty Member
    Computer and Information Science, Higher Colleges of Technology, Al Ain, Abu Dhabi, UAE
    August 2015 – July 2016

    • Taught courses including Introduction to Multimedia, Research Methods in Emerging Technologies, Statistics and Probability, and Information Systems in Organizations and Society.
  • Instructor/Associate Professor
    Çankaya University (400-500 by Times ranking), Department of Computer Engineering, Ankara
    September 2007 – June 2015

    • Taught courses including Data Mining, Multimedia Security, Object-Oriented Languages, Database Management, Multimedia and Internet, Data Management and File Structures, and Formal Languages and Automata.
  • Expert/Chief Expert of Scientific Programs
    TÜBİTAK, Ankara, Turkey
    August 2007 – July 2014

    • Served as Executive Secretary to the Electrical, Electronics, and Informatics Research Grant Committee, National Scientific Expert in COST Information and Communication Domain, and National Delegate in COST (FP 7) Trans Domain Proposals.
  • SQL Application Developer
    Bureau of Revenue Enhancement and Automation, Finance Office, New York City Government
    November 2004 – July 2007

    • Developed SQL applications, performed ad-hoc queries, and managed staff training in SQL and related software tools.
  • Instructor
    The City University of New York (CUNY)
    September 2004 – May 2007

    • Taught courses at Brooklyn College, Borough Manhattan Community College, and Lehman College, including Operations Management, Introduction to Computer Applications, Database Management, Discrete Structures, and GMAT Math.
  • Research Assistant
    Electrical Engineering and Computer Science, Syracuse University
    January 2003 – May 2004

    • Worked on Automated Scenario Recognition in Video Sequences and implemented data mining and machine learning techniques.
  • Engineer
    Calik Textile, Istanbul, Turkey
    January 1999 – August 1999

    • Focused on Production Planning.
  • Engineer
    HES Machine, Kayseri, Turkey
    June 1997 – March 1998

    • Focused on Production Planning and Quality Control.

Publication top Notes:

Transformer Based Hierarchical Model for Non-Small Cell Lung Cancer Detection and Classification

Anticipate Movie Theme from Subtitle: A Deep Learning Approach

Robust and Secure Watermarking Algorithm Based on High Frequencies of Integer Wavelet Transform

Fortifying Integrity and Privacy in Medical Imaging: Discrete Shearlet and Radon Transform-Based Watermarking Approach

Machine Learning-Based Analysis and Prediction of Liver Cirrhosis

 

 

 

Dr. Xianchao Zhu | Reinforcement Learning | Best Researcher Award

Dr. Xianchao Zhu | Reinforcement Learning | Best Researcher Award 

Dr. Xianchao Zhu, School of Artificial Intelligence and Big Data/Henan University of Technology, China

Dr. Xianchao Zhu is a Lecturer at the School of Artificial Intelligence and Big Data at Henan University of Technology, a position he has held since 2022. He completed his Ph.D. in Physics at the Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, where his research focused on “Abstraction-based Reinforcement Learning Algorithms and its Quantization.” Prior to his doctoral studies, Dr. Zhu earned a Master of Science in Computer Architecture from the School of Computer, Central China Normal University, with a thesis on “Research on Dimensionality Reduction Visualization Method of High-Dimensional Biological Data Based on Gradient Descent and Adaptive Learning.” His academic interests span artificial intelligence, reinforcement learning, and high-dimensional data analysis.

Professional Profile:

 

ORCID

Education

  • Ph.D. in Physics
    Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China
    2018 – 2022
    Thesis Title: Abstraction-based Reinforcement Learning Algorithms and its Quantization.
  • M.Sc. in Computer Architecture
    School of Computer, Central China Normal University
    2015 – 2018
    Thesis Title: Research on Dimensionality Reduction Visualization Method of High-Dimensional Biological Data Based on Gradient Descent and Adaptive Learning.

Employment History

  • Lecturer
    School of Artificial Intelligence and Big Data, Henan University of Technology
    2022 – Present

Publication top Notes:

Salience Interest Option: Temporal abstraction with salience interest functions

Generalization Enhancement of Visual Reinforcement Learning through Internal States

Efficient relation extraction via quantum reinforcement learning

MDMD options discovery for accelerating exploration in sparse-reward domains