Eman Younis | Artificial Intelligence | Best Researcher Award

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Prof. Eman Younis | Artificial Intelligence | Best Researcher Award šŸ†

Professor at Minia university, Egypt.

Dr. Eman M.G. Younis is a distinguished academic and researcher in the fields of information systems, data mining, semantic web, machine learning, and geographic information systems (GIS). With a robust educational foundation, including a Ph.D. in Informatics from Cardiff University and numerous impactful publications, Dr. Younis has significantly contributed to advancements in data science and geospatial technologies. Her leadership roles at Minia University, Egypt, further emphasize her dedication to research, teaching, and community development.

Profile

Scopus

Orcid

Google Scholar

Education šŸŽ“:

Dr. Eman M.G. Younis holds a Doctor of Philosophy in Informatics from Cardiff University, UK (2009ā€“2013). Her Ph.D. thesis, titled “Hybrid Geo-spatial Query Processing on the Semantic Web,” explored the integration of semantic web technologies with spatial data queries. She earned her Master of Science in Information Technology from Menoufia University, Egypt (2004ā€“2007), where her thesis focused on “Automatic Web Page Classification with Data Mining Techniques.” Prior to this, she completed her Bachelor of Science in Information Systems & Technology from Zagazig University, Egypt (1998ā€“2002), graduating with honors (GPA: 82.5%). Throughout her academic journey, Dr. Younis demonstrated exceptional aptitude for research and innovation, laying the foundation for her interdisciplinary expertise in informatics, GIS, and data science. Her education reflects a consistent pursuit of cutting-edge technologies and methodologies, making her a leader in her field.

Work Experience šŸ’¼:

Dr. Eman M.G. Younis has a rich professional background encompassing teaching, research, and administrative roles. She began her academic career as a Teaching Assistant at Minia University, Egypt (2003ā€“2009), later serving as a Lecturer (2014) and Assistant Professor (2018ā€“2019). Her international experience includes a tenure as a Postdoctoral Researcher at Nottingham Trent University, UK (2015ā€“2017), focusing on emotion recognition and sensor data analysis. Currently, she is an Associate Professor and Vice Dean for Community Service and Environmental Development at Minia University. Dr. Younis also chaired the Information Systems Department (2019ā€“2021), demonstrating her leadership in academic administration. She supervises numerous masterā€™s and Ph.D. students, fostering innovation in fields such as machine learning and GIS. Her career reflects a commitment to interdisciplinary research, academic excellence, and community engagement.

Awards and Honors

Dr. Eman M.G. Younis has been recognized for her contributions to research and academia through numerous awards and honors. She was awarded scholarships for her postgraduate studies, including funding for her Ph.D. at Cardiff University. Her innovative research in GIS, semantic web technologies, and data science has earned her accolades at international conferences. Dr. Younis has also been acknowledged for her leadership and service as Vice Dean at Minia University. Her work on real-time machine learning applications for healthcare and environmental systems has received critical acclaim. Additionally, she has contributed to collaborative international research projects, showcasing her ability to address complex, interdisciplinary challenges. These accolades underscore her dedication to advancing knowledge, mentoring students, and applying technology for societal benefit.

Research Interests:

Dr. Eman M.G. Younisā€™s research focuses on Geographic Information Systems (GIS), Data Mining, Semantic Web, and Artificial Intelligence. Her interdisciplinary interests include geospatial query processing, social media mining, and emotion recognition using sensor data fusion. She explores innovative applications of machine learning and deep learning in fields such as healthcare, urban planning, and environmental monitoring. Dr. Younis is also interested in hybrid online-offline learning systems, big data analytics, and real-time predictions for critical systems like healthcare and disaster management. Her work bridges theoretical advancements and practical implementations, aiming to address pressing global challenges. She integrates cutting-edge technologies like distributed machine learning and streaming systems to enhance the accuracy and efficiency of predictive models. Her ongoing projects include emotion recognition through multimodal sensor data and the application of AI in geospatial data analysis.

šŸ“š PublicationsĀ 

    • Deep learning analysis of mobile physiological, environmental and location sensor data for emotion detection
      Authors: E. Kanjo, E.M.G. Younis, C.S. Ang
      Citations: 303
      Year: 2019
    • Sentiment analysis and text mining for social media microblogs using open source tools: an empirical study
      Authors: E.M.G. Younis
      Citations: 174
      Year: 2015
    • Heart disease identification from patientsā€™ social posts, machine learning solution on Spark
      Authors: H. Ahmed, E.M.G. Younis, A. Hendawi, A.A. Ali
      Citations: 164
      Year: 2020
    • Towards unravelling the relationship between on-body, environmental and emotion data using sensor information fusion approach
      Authors: E. Kanjo, E.M.G. Younis, N. Sherkat
      Citations: 121
      Year: 2018
    • An efficient Manta Ray Foraging Optimization algorithm for parameter extraction of three-diode photovoltaic model
      Authors: E.H. Houssein, G.N. Zaki, A.A.Z. Diab, E.M.G. Younis
      Citations: 93
      Year: 2021
    • Predicting Coronavirus Pandemic in Realā€Time Using Machine Learning and Big Data Streaming System
      Authors: X. Zhang, H. Saleh, E.M.G. Younis, R. Sahal, A.A. Ali
      Citations: 64
      Year: 2020
    • NeuroPlace: Categorizing urban places according to mental states
      Authors: E.M.G. Younis, L. Al-Barrak, E. Kanjo
      Citations: 64
      Year: 2017
    • Fuzzy-based hunger games search algorithm for global optimization and feature selection using medical data
      Authors: E.H. Houssein, M.E. Hosney, W.M. Mohamed, A.A. Ali, E.M.G. Younis
      Citations: 40
      Year: 2023
    • Hybrid geo-spatial query methods on the Semantic Web with a spatially-enhanced index of DBpedia
      Authors: E.M.G. Younis, C.B. Jones, V. Tanasescu, A.I. Abdelmoty
      Citations: 35
      Year: 2012
    • Comparing automated and nonā€automated machine learning for autism spectrum disorders classification using facial images
      Authors: B.R.G. Elshoky, E.M.G. Younis, A.A. Ali, O.A.S. Ibrahim
      Citations: 33
      Year: 2022
    • Designing and evaluating mobile self-reporting techniques: crowdsourcing for citizen science
      Authors: E.M.G. Younis, E.K.A. Chamberlain
      Citations: 32
      Year: 2019
    • Evaluating ensemble learning methods for multi-modal emotion recognition using sensor data fusion
      Authors: E.M.G. Younis, S.M. Zaki, E. Kanjo, E.H. Houssein
      Citations: 29
      Year: 2022
    • Hybrid onlineā€“offline learning to rank using simulated annealing strategy based on dependent click model
      Authors: O.A.S. Ibrahim, E.M.G. Younis
      Citations: 24
      Year: 2022

ConclusionĀ 

Dr. Eman M.G. Younis is an outstanding candidate for the Best Researcher Award. Her groundbreaking contributions to the fields of informatics, GIS, and machine learning, coupled with her leadership roles, technical expertise, and commitment to advancing science, make her a highly deserving nominee. With further strategic collaborations and public engagement, her already stellar impact could be further enhanced.

 

 

Arti Jha | Artificial Intelligence | Best Researcher Award

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Ms Arti Jha |Ā Ā Artificial Intelligence |Ā Ā Best Researcher AwardĀ 

 

Senior Research Fellow atĀ Birla Institute of Technology and Science, Pilani,Ā India

 

šŸ“š šŸ‘©ā€šŸ’» Arti Jha is a Senior Research Fellow at BITS Pilani, specializing in machine learning, natural language processing, statistics, game theory, and deep learning. Currently pursuing a PhD in Web Intelligence and Social Computing, she focuses on AI-enabled design of optimal advertisement campaign strategies in collaboration with CommerceIQ, Bangalore. With industry experience at CommerceIQ, she develops predictive models for e-commerce platforms. Arti holds a BTech-MTech dual degree from the Centre for Converging Technologies, University of Rajasthan. Her research spans object detection, machine learning, and teaching roles as a TA at BITS Pilani.

Professional Profile:

 

Education šŸŽ“

PhD Candidate in Web Intelligence and Social Computing, BITS Pilani, Pilani, India, Feb 2022 – Present.

BTech-MTech Dual Degree, Centre for Converging Technologies, University of Rajasthan, Aug 2015 – Jul 2020. Cumulative GPA: 3.8/4.00.

Research Focus šŸ”¬

Arti Jha’s research focuses on several key areas in the realm of artificial intelligence and data science. She specializes in machine learning šŸ¤–, natural language processing šŸ“œ, statistics šŸ“Š, game theory šŸŽ², and deep learning šŸ§ . Her work spans from optimizing e-commerce advertising campaigns using advanced machine learning techniques to developing reinforcement learning strategies for real-time bidding in digital marketing. With a strong foundation in both theoretical research and practical applications, Arti contributes actively to the fields of AI-enabled advertisement strategies, predictive modeling, and algorithmic optimizations aimed at enhancing business intelligence and decision-making processes in digital platforms.

Professional Experience šŸ’¼

  • Senior Research Fellow, BITS-CommerceIQ Collaboration Project, BITS Pilani, Pilani, India, Feb 2022 – Present.
  • Designing optimal and targeted ad campaign strategies on e-commerce platforms.
  • Developing prediction models for optimizing ad campaigns on Amazon.
  • Working on interpretable and explainable AI models.
  • Industry Experience at CommerceIQ, Bangalore, India.

Research Experience šŸ“Š

  • Research Scholar, BITS Pilani, Pilani, India, Feb 2022 – Present.
  • Building algorithmic campaign optimizers.
  • Implementing multi-stage campaign classification and clustering models.
  • Designing explainable models for risk-averse modeling.
  • Project Trainee, Indian Space Research Organisation (ISRO), RRSC Jodhpur, India, Aug 2019 – Apr 2020.
  • Thesis on Object Detection using Satellite Images.
  • Data Analysis Intern, Robotics And Machine Analytics Lab (RAMAN), MNIT Jaipur, India, Mar 2019 – May 2019.
  • Developed a Movie Recommendation System.

Academic Experience šŸ“š

  • Teaching Assistant, BITS Pilani, Pilani, India.
  • C Programming (Feb 2022 – Dec 2023).
  • Data Warehousing (Jan 2024 – Present).

Publications:Ā 

 

Pritom Jyoti Goutom | Artificial Intelligence | Best Researcher Award

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Mr Pritom Jyoti Goutom | Artificial Intelligence | Best Researcher Award

 

Research Scholar and Project Associate I at Dibrugarh University ,India

Profile:

ScopusĀ 

Education:

Pritom Jyoti Goutom is affiliated with the Centre for Computer Science and Applications at Dibrugarh University in Assam, India šŸ‡®šŸ‡³. His research focuses on natural language processing (NLP), particularly related to the Assamese language šŸ—£ļø.

Some of his notable contributions include:

  1. Text Summarization šŸ“„: He has co-authored papers on text summarization techniques using deep learning, such as “An Abstractive Text Summarization Using Deep Learning in Assamese” and “Text Summarization in Assamese Language Using Sequence to Sequence RNNs”怐5ā€‹ (ORCID)ā€‹ā€‹ (Dibrugarh University)ā€‹2. Collaboration with Dr. Nomi Baruah šŸ¤: He often works with Dr. Baruah and others on projects aimed at improving NLP for low-resource languages.

For more details about his educational background and academic contributions, you can check his profile on academic platforms like ORCID怐5ā€‹ (ORCID)

Professional Experience:

šŸŽ“ Research Scholar at Dibrugarh University
Specializing in Natural Language Processing (NLP) and AI-generated text in Assamese.
šŸ” Research Focus: Text summarization, part-of-speech tagging, and fake news detection.

šŸ‘Øā€šŸ’» Project Associate I, Dept. of Computer Science and Engineering
Contributing to cutting-edge projects and innovations in AI and NLP.

Research Ā FocusĀ  Ā :

  • Text Summarization: Developing algorithms for concise representation of Assamese text.
  • Machine Translation: Enhancing language conversion models for Assamese.
  • Sentiment Analysis: Analyzing opinions and emotions expressed in Assamese text.
  • Named Entity Recognition (NER): Identifying and categorizing entities in Assamese text.
  • Fake News Detection: Implementing models to identify misinformation in Assamese news sources.
  • Language Modeling: Building computational models to understand and generate Assamese text.

 

Contributions :

  • Co-authored research on abstractive text summarization using deep learning approaches, focusing on the nuances of the Assamese language.
  • Investigated LSTM and BiLSTM algorithms for fake news detection, enhancing accuracy and reliability in Assamese news sources.
  • Developed attention-based transformer models for text summarization in Assamese, improving content extraction and generation.
  • Worked on automatic spelling error identification using deep learning algorithms tailored for Assamese language nuances.

Citations:

Total Citations: šŸ“ˆ 13

Total Documents:Ā  šŸ“‚3

h-index: šŸŒŸ 1

Publication Top Notes:

  • Goutom, P. J., Baruah, N., & Sonowal, P. (2023). An abstractive text summarization using deep learning in Assamese. International Journal of Information Technology, 15(5), 2365-2372. (6 citations)

 

  • Phukan, R., Goutom, P. J., & Baruah, N. (2024). Assamese Fake News Detection: A Comprehensive Exploration of LSTM and Bi-LSTM Techniques. Procedia Computer Science, 235, 2167-2177.

 

  • Goutom, P. J., Baruah, N., & Sonowal, P. (2024). Attention-based Transformer for Assamese Abstractive Text Summarization. Procedia Computer Science, 235, 1097-1104.

 

  • Phukan, R., Neog, M., Goutom, P. J., & Baruah, N. (2024). Automated Spelling Error Detection in Assamese Texts using Deep Learning Approaches. Procedia Computer Science, 235, 1684-1694.

 

  • Goutom, P. J., & Baruah, N. (2023). Text summarization in Assamese language using sequence to sequence RNNs. Indian Journal of Science and Technology, 16(SP2), 22-29.