Assist. Prof. Dr. Dumitru Radulescu | Machine Learning Awards | Top Researcher Award

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Assist. Prof. Dr. Dumitru Radulescu | Machine Learning Awards | Top Researcher Award 

Assist. Prof. Dr. Dumitru Radulescu, University of Medicine and Pharmacy Craiova (UMF Craiova), Romania

Dumitru Rădulescu, is a distinguished medical professional and researcher specializing in surgery and medical sciences. He earned his Bachelor’s degree in Medicine from UMF Craiova in 2009, followed by a Doctor of Medical Sciences degree, which he obtained in 2020 under the auspices of the Romanian Ministry of Health. Dr. Rădulescu’s academic journey is marked by his receipt of a competitive doctoral scholarship, highlighting his commitment to advancing his expertise in the medical field. Currently serving as a Specialist Surgeon at the Military Emergency Clinical Hospital “Dr. Ştefan Odobleja” in Craiova, he has accumulated extensive clinical experience through various residency programs in family medicine and general surgery. His professional roles include positions as a University Assistant at UMF Craiova, where he contributes to the education of future healthcare professionals in surgical specialties.

Professional Profile:

ORCID

Summary of Suitability for the Top Researcher Award

Dumitru Rădulescu is an accomplished researcher and specialist surgeon whose academic and professional journey highlights his commitment to advancing medical sciences, particularly in the areas of surgery and diagnostics. His education culminated in a Doctor of Medical Sciences degree from UMF Craiova, where he also received a doctoral scholarship, showcasing his academic excellence and dedication to research.

Education 📚

  • Doctor of Medical Sciences
    University of Medicine and Pharmacy Craiova (UMF Craiova)
    2014 – 2020
  • Doctoral Scholarship
    UMF Craiova (POSDRU/187/1.5/S/156069)
    2014 – 2015
  • Bachelor’s Degree in Medicine
    UMF Craiova
    2003 – 2009
  • High School Diploma
    Balş Theoretical High School
    1999 – 2003

Professional Development 🎓

  • Specialist Surgeon
    Ministry of Health Order no. 721/04.06.2018
    2018 – Present
  • General Surgery Resident
    2012 – 2018
  • Family Medicine Resident
    2010 – 2012

Areas of Competence 💪

  • DPPD Module (2008)
  • English for Specific Purposes – Medical English B2 (2021)

Professional Experience 🏥

  • Current Position:
    University Assistant, Military Emergency Clinical Hospital “Dr. Ştefan Odobleja,” Craiova
    2022 – Present
  • Previous Positions:
    • University Assistant DRD, Department VI – Surgical Specialties (2018 – 2021)
    • General Surgery Resident, Clinic I Surgery SCJU no.1 Craiova (2013 – 2018)
    • Family Medicine Resident, Filantropia Clinical Hospital Craiova (2010 – 2012)

Research Contributions 🔬

Dr. Rădulescu is a dedicated researcher who recently received a grant for his project titled:
“Discovery and validation of a new leukocyte formula marker for predicting mortality in patients with tuberculosis and malnutrition using machine learning.” 🤖
This project highlights his commitment to leveraging modern technology in medical research to address critical health issues.

Publication Top Notes

Enhancing the Understanding of Abdominal Trauma During the COVID-19 Pandemic Through Co-Occurrence Analysis and Machine Learning

Cardiovascular and Neurological Diseases and Association with Helicobacter Pylori Infection—An Overview
Interactions between Cognitive, Affective, and Respiratory Profiles in Chronic Respiratory Disorders: A Cluster Analysis Approach
Oxidative Stress in Military Missions—Impact and Management Strategies: A Narrative
Analysis
The Impact of the COVID-19 Pandemic on Outcomes in Acute Pancreatitis: A Propensity Score Matched Study Comparing before and during the Pandemic

 

 

Ms. Rachel Stephen Mollel | Machine Learning Awards | Best Scholar Award

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Ms. Rachel Stephen Mollel | Machine Learning Awards | Best Scholar Award

Ms. Rachel Stephen Mollel, University of Strathclyde, United Kingdom

Rachel Stephen Mollel is a Ph.D. student in Electrical and Electronic Engineering at the University of Strathclyde, UK. Her research focuses on machine learning, explainable AI, energy demand-side management, smart metering, and non-intrusive load monitoring (NILM). She holds a Master of Engineering from Arkansas Tech University, USA, and a Bachelor’s degree in Telecommunication Engineering from Visvesvaraya Technological University, India. Rachel has contributed significantly to the energy sector, exploring the role of smart meters in reducing energy costs and enhancing communication between energy providers and consumers. Her recent work, which investigates the potential of NILM to reveal hidden demand flexibility in residential energy consumption, has been published in various peer-reviewed journals and conferences. Additionally, she is actively involved in improving the interpretability of NILM models to enhance algorithm performance. Her contributions have been recognized with a Commonwealth Scholarship in 2020.

Professional Profile:

ORCID

Summary of Suitability for the Best Scholar Award:

Rachel Stephen Mollel is a highly suitable candidate for the Best Research Scholar Award based on her significant contributions to the fields of machine learning, explainable AI, and energy demand-side management. As a PhD student at the University of Strathclyde, her research aims to address critical energy issues through innovative approaches like Non-Intrusive Load Monitoring (NILM), which helps uncover hidden demand flexibility in residential energy consumption.

Education:

  • 2021 – Present: PhD in Electrical and Electronic Engineering, University of Strathclyde, UK
  • 2010 – 2012: Master of Engineering, Arkansas Tech University, USA (GPA: 3.75/4.0)
  • 2006 – 2010: Bachelor’s degree in Telecommunication Engineering, Visvesvaraya Technological University, India (First Class)

Work Experience:

  • 2011 – 2012: Graduate Assistant, Arkansas Tech University, USA
    Assisted in the Digital Logic and Robotics Course & Lab; delivered tutorials, graded lab reports and exams, and supported the development of course materials under faculty supervision.
  • 2014 – 2020: Assistant Lecturer, University of Dar es Salaam, Tanzania
    Delivered lectures, prepared and graded exams in Control Systems Engineering and Fundamentals of Electrical Engineering. Supervised undergraduate student projects, practical training, and fieldwork. Managed various administrative duties, such as student registration and coordination of departmental examinations.

Publication top Notes:

Explainability-Informed Feature Selection and Performance Prediction for Nonintrusive Load Monitoring

Using explainability tools to inform non-intrusive load monitoring algorithm performance

Using explainability tools to inform NILM algorithm performance

Dr. Tesfay Gidey | Machine Learning Awards | Best Researcher Award

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Dr. Tesfay Gidey | Machine Learning Awards | Best Researcher Award 

Dr. Tesfay Gidey, Addis Ababa Science and Technology University, Ethiopia

Tesfay Gidey Hailu is a distinguished Information and Communication Engineer and data scientist with a strong foundation in computer science, software engineering, data analytics, and machine learning. Holding a Ph.D. in Information and Communication Engineering from the University of Electronic Science and Technology of China, Tesfay specializes in advanced signal processing, indoor localization, information fusion, and health datasets. His expertise spans multiple programming languages, including Python, C++, SQL, and Java, as well as advanced statistical tools like SAS and R, which he uses to derive data-driven insights and support strategic decision-making in technology projects. Tesfay’s career includes notable leadership roles, such as Associate Dean for Research and Technology Transfer at Addis Ababa Science and Technology University (AASTU) and Head of Department at Jimma University. His work in academia has focused on curriculum development, student recruitment and retention, and faculty management, showcasing his commitment to fostering educational excellence. Additionally, Tesfay holds an M.Sc. in Software Engineering and an M.Sc. in Health Informatics and Biostatistics, underscoring his multidisciplinary expertise. With a deep commitment to problem-solving and continuous learning, Tesfay is adept at leveraging data and technology to drive impactful results across both academic and industry settings.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award for Tesfay Gidey Hailu

Overview: Tesfay Gidey Hailu is an accomplished Information and Communication Engineer, specializing in computer science, data science, and software engineering with extensive experience in machine learning, data structure, algorithm analysis, and business analytics. He holds a Ph.D. in Information and Communication Engineering, has published several journal articles, and serves as a journal reviewer for prestigious journals. His broad expertise and impactful contributions make him a strong candidate for the Best Researcher Award.

🎓 Education:

  • Ph.D. in Information and Communication Engineering (2023)
    University of Electronic Science and Technology of China
    Specialized in digital signal processing and information systems, with research in indoor positioning using machine learning algorithms.
  • MSc in Software Engineering (2018)
    HILCOE School of Computer Science and Information Technology
    Completed advanced courses in requirement engineering, project management, and software security.
  • MSc in Health Informatics and Biostatistics (2013)
    College of Health Sciences, Mekelle University
    Focused on health informatics, biostatistics, epidemiology, and public health project management.

Work Experience

  1. Associate Dean for Research and Technology Transfer
    • Institution: AASTU, Addis Ababa, College of Natural and Social Sciences
    • Duration: 2017-2019
    • Responsibilities: Initiated quality improvement initiatives for manufacturing industries, faculty recruitment, supervised admissions, student recruitment, and conducted industry-related research.
  2. Associate Dean, Interdisciplinary Programs Directorate
    • Institution: AASTU, Addis Ababa
    • Duration: 2015-2016
    • Responsibilities: Managed student services and retention, supervised curriculum quality initiatives, admissions, and presented research findings.
  3. Head of Department
    • Institution: Jimma University, Jimma
    • Duration: 2008-2009
    • Responsibilities: Led department meetings, evaluated performance, streamlined operations to enhance student satisfaction.
  4. Coordinator, Community-Based Training Program (CBTP)
    • Institution: Jimma University, Faculty of Natural and Information Sciences Extension Division
    • Duration: 2007-2008
    • Responsibilities: Oversaw the CBTP initiative, focusing on community-based training programs.

Publication top Notes:

Theories and Methods for Indoor Positioning Systems: A Comparative Analysis, Challenges, and Prospective Measures

Ada-LT IP: Functional Discriminant Analysis of Feature Extraction for Adaptive Long-Term Wi-Fi Indoor Localization in Evolving Environments

MultiDMet: Designing a Hybrid Multidimensional Metrics Framework to Predictive Modeling for Performance Evaluation and Feature Selection

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

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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

 

 

 

Mr. CHENGYONG JIANG | Machine Learning Award | Best Researcher Award

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Mr. CHENGYONG JIANG | Machine Learning Award | Best Researcher Award 

Mr. CHENGYONG JIANG, Fudan university, China

Chengyong Jiang is a promising neurobiology Ph.D. candidate at Fudan University, China, with an outstanding academic record and significant research experience. He earned his Master’s degree in Biotechnology from Minzu University of China, graduating in the top 5% of his class, and is currently pursuing his doctoral studies at Fudan University, where he is ranked in the top 10% of his cohort. Jiang’s research focuses on the regulation of sleep and eye movement by cholinergic neurons in the oculomotor nerve nucleus. Jiang has demonstrated a strong commitment to academic and practical excellence through various roles, including as a teaching assistant at Beijing Foreign Studies University and a high school biology tutor at Hangzhou Zhipeng Network Technology Co., Ltd. His involvement in innovative projects, such as studying the therapeutic effects of Polygonum multiflorum on stress-induced depression and leading a social practice team analyzing undergraduate education in biology, highlights his leadership and research capabilities.

Professional Profile:

Summary of Suitability for Best Researcher Award:

Chengyong Jiang has demonstrated a strong academic background and research capability in neurobiology and biotechnology. His work, including his master’s research on stress-induced depression and his ongoing doctoral research on sleep and eye movement regulation, reflects a deep understanding of complex biological processes. His publications in reputable journals like Frontiers in Neuroscience and Advanced Science underscore his ability to conduct impactful and high-quality research.

Education

Fudan University, Shanghai, China
Neurobiology Doctor
September 2020 – June 2026
Top 10%

Minzu University of China, Beijing, China
Master of Biotechnology
September 2015 – June 2019
Top 5%

Work Experience

Institutes of Brain Science, Fudan University
Researcher
September 2020 – Present

  • Conducting research on “Regulation of sleep and eye movement by cholinergic neurons in the nucleus of the oculomotor nerve.”

Hangzhou Zhipeng Network Technology Co., Ltd., Hangzhou, China
High School Biology Tutor (Part-time)
September 2017

  • Provided online tutoring in biology to middle and high school students.

Beijing Foreign Studies University, Beijing, China
Teaching Assistant
July 2017 – September 2017

  • Participated in and organized the “E PLUS Beiwai Yijia Study Tour” summer camp, served as homeroom teacher, and assisted in English teaching activities.

Publication top Notes:

MLS-Net: An Automatic Sleep Stage Classifier Utilizing Multimodal Physiological Signals in Mice

Exosomes Derived from M2 Microglial Cells Modulated by 1070-nm Light Improve Cognition in an Alzheimer’s Disease Mouse Model.

Tracking Eye Movements During Sleep in Mice.

2,3,5,4′-Tetrahydroxystilbene-2-O-beta-D-glucoside Reverses Stress-Induced Depression via Inflammatory and Oxidative Stress Pathways.