Federico D’ Asaro | Artificial intelligence | Best Researcher Award

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Mr. Federico D’ Asaro | Artificial intelligence | Best Researcher Award

Mr. Federico D’ Asaro, Politecnico di Torino, Italy

Based on Mr. Federico D’Asaro’s background and achievements, he appears to be a strong candidate for the Research for Best Researcher Award. Here’s an evaluation of his suitability:

Publication profile

Education 🎓

  • Polytechnic University of Turin: M.Sc. in Data Science and Engineering with a thesis on algorithm discrimination. Achieved a final grade of 110/110.
  • University of Palermo: B.Sc. in Engineering and Management, graduating cum laude with a final grade of 110/110.
  • Scientific Lyceum “Galileo Galilei”: High School Diploma with a grade of 83/100.

Work Experience 💼

  • Ph.D. Student at Polytechnic University of Turin: Conducting research on Modality-Gap in multimodal feature space and submitting articles to prominent conferences.
  • AI Applied Researcher at LINKS Foundation: Developed advanced applications in business analytics, sentiment analysis, retrieval systems, and speech emotion recognition. Engaged in proposal writing and reviewing conference papers.
  • Intern at Technology Reply: Gained experience in NLP, sentiment analysis, and textual data modelization.

Skills and Competencies 🛠️

  • Proficient in multiple programming languages and tools including Python, Java, TensorFlow, PyTorch, and SQL.
  • Experienced in data visualization, machine learning, and deep learning.
  • Competent in using various IT tools and frameworks like Apache Spark and Hadoop.

Other Information 🌍

  • Languages: Fluent in Italian and proficient in English (B2 level).
  • Interests: Diverse interests including sports, literature, and technology.
  • Certifications: B2 First (FCE) and driving license.

Publication Top Notes

Zero-Shot Content-Based Crossmodal Recommendation System

Sensitive attributes disproportion as a risk indicator of algorithmic unfairness

Conclusion🏆

Mr. Federico D’Asaro demonstrates a solid academic background, relevant work experience, and a diverse skill set, aligning well with the criteria for the Research for Best Researcher Award. His ongoing research and contributions to AI applications show a strong potential for impactful research and innovation.

Dharmapuri Siri | Deep Learning | Best Researcher Award

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Dharmapuri Siri | Deep Learning | Best Researcher Award

Assistant Prof Dharmapuri Siri, Gokaraju Rangaraju Institute of Engineering and Technology, india.

Dr. D. Siri is a dedicated academic professional with over 11 years of experience in teaching and research in the field of Computer Science and Engineering. She has served as an Assistant Professor in various prestigious institutions, including TRR Engineering College and Malla Reddy Engineering College for Women. Her work is focused on the intersection of software quality, machine learning, and data analysis.

Profile:

orcid

Education📚:

Dr. D. Siri holds a Ph.D. in Computer Science and Engineering from JJT University, obtained in 2022. She completed her M.Tech in Computer Science and Engineering from JNTU Hyderabad in 2010, and her B.Tech in Information Technology from the same university in 2006.

Professional Experience👩‍🏫:

Dr. Siri began her teaching career in 2008 as an Assistant Professor in the Department of Information Technology at TRR Engineering College, where she worked until 2013. She then transitioned to the Department of Computer Science and Engineering at TRR College of Engineering, continuing her role until 2017. From 2017 to 2019, she served as an Assistant Professor at Malla Reddy Engineering College for Women. Throughout her career, she has gained extensive experience in teaching core subjects like C, C++, Java, DBMS, Software Testing Methodologies, and Software Engineering.

Research Interests🔍:

Dr. Siri’s research interests are primarily focused on software quality improvement, bug prediction using machine learning techniques, and the application of deep learning methods to various domains such as sentiment analysis, medical imaging, and automated systems. Her work in these areas has been presented at numerous national and international conferences.

Awards and Recognitions🏆:

Dr. Siri’s innovation and contributions to the field have been recognized through a published patent titled “A Vehicle with Smart Biometric Device” (Application No. 201841019142-A), which was published in The Patent Office Journal No. 22/2018 on June 1, 2018.

Research Contributions 📚:

Dr. Siri’s research is primarily centered around software quality, machine learning, and data analysis. Her notable works include studies on bug prediction models, software engineering methodologies, and the application of machine learning techniques in software quality improvement. Her Ph.D. thesis on “Bug Prediction Model for Software Quality Using Machine Learning Techniques” reflects her deep commitment to enhancing software reliability and performance.

Publication:

Publications 📝:
Dr. Siri has published several research articles in reputed journals. Here are some of her notable publications:

  1. A Study on Bug Prediction in Determining The Software Quality | History Research Journal | 2019.
  2. Machine Learning Techniques on Historical Software Bugs for Prediction of Software Bugs | Think India Journal | 2019.
  3. Analyzing Public Sentiment on the Amazon Website: A GSK-Based Double Path Transformer Network Approach for Sentiment Analysis | IEEE Access | 2024.
  4. Segmentation Using the IC2T Model and Classification of Diabetic Retinopathy Using the Rock Hyrax Swarm-Based Coordination Attention Mechanism | IEEE Access | 2024.

 

 

 

Nafis Uddin Khan | Artificial Intelligence | Best Researcher Award

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Dr Nafis Uddin Khan | Artificial Intelligence | Best Researcher Award 

Dr Nafis Uddin Khan, SR University Warangal India, India

Dr. Nafis Uddin Khan is a distinguished academic and researcher at SR University in Warangal, India. His expertise spans a variety of fields, contributing significantly to both the academic community and industry advancements. Dr. Khan’s work is characterized by a strong focus on innovative solutions and sustainable practices, reflecting his commitment to addressing contemporary challenges through research and education. At SR University, he plays a pivotal role in mentoring students and leading research initiatives that aim to drive technological progress and societal impact.

Profile

Orcid

Education

       Bachelor of Engineering (B.E.) in Electronics and Telecommunication Engineering from Amravati University  Maharashtra, in 2003.

       Master of Technology (M.Tech.) in Software Systems from S.A.T.I. Vidisha under Rajiv Gandhi Technological University, Bhopal, in 2008.

        Doctor of Philosophy (Ph.D.) in Signal and Image Processing from the Atal Bihari Vajpayee – Indian Institute of Information Technology & Management, Gwalior

Professional experience

  1. Workshop Coordinator: Coordinated a two-day workshop titled “Synthesis of Wisdom: Crafting AI Tutor Assistants, Navigating Future-Ready Digital Libraries and Elevating Pedagogy in the Age of Skill Enhancement and AI Mastery” on February 02–03, 2024, at the School of CS & AI, SR University, Warangal, India.
  2. Faculty Development Program Coordinator: Coordinated “Utkarsh – Take Flight,” a two-day Faculty Development Program on Leadership and Excellence in Quality Education organized by Jaypee University of Information Technology, Solan (H.P.), on December 22–23, 2022.
  3. Chief Coordinator: Served as Chief Coordinator in a student outreach activity organized by the Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Solan (H.P.), on December 20, 2022.
  4. Invited Session Chair: Served as an Invited Session Chair in the Congress on Intelligent Systems (CIS 2020), World Conference in virtual format, on September 05–06, 2020.
  5. Organizing Committee Member and Reviewer: Participated as an Organizing Committee Member and Reviewer in the Congress on Intelligent Systems (CIS 2020), World Conference in virtual format, on September 05–06, 2020.
  6. Convener: Organized a one-week online short-term course on “Recent Advances in Computational Intelligence for Signal Processing” (RACISP – 2020) at Jaypee University of Information Technology, Solan (H.P.), from August 10–15, 2020.
  7. Coordinator: Coordinated a five-day short-term course on “Recent Advances in Signal and Image Processing” (RASIP – 2019) at Jaypee University of Information Technology, Solan (H.P.), from June 24–28, 2019.
  8. Organizing Committee Member: Served in the organizing committee for the 5th IEEE International Conference on “Signal Processing, Computing and Control” (ICSPC 2019) organized by the Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Solan (H.P.), from October 10–12, 2019.
  9. Invited Session Chair: Chaired an invited session in the 2019 IEEE International Conference on “Image Information Processing” (ICIIP 2019) organized by the Department of Computer Science and Engineering, Jaypee University of Information Technology, Solan (H.P.), from November 15–17, 2019.
  10. Organizing Committee Member: Participated as an organizing committee member in the 4th IEEE International Conference on “Signal Processing, Computing and Control” (ICSPC 2017) at Jaypee University of Information Technology, Solan (H.P.), from September 21–23, 2017.
  11. Invited Session Chair: Served as an invited session chair at the 7th IEEE International Conference on “Computational Intelligence and Communication Networks” (CICN 2015) at Gyan Ganga Institute of Technology and Science, Jabalpur (M.P.), on December 12, 2015.
  12. National Advisory Committee Member: Served on the National Advisory Committee for the National Conference on Contemporary Computing organized by the Department of Computer Science and Information Technology, Chameli Devi Group of Institutions, Indore (M.P.), from October 21–22, 2016.

Research Focus

      Fuzzy Logic and Optimization: Utilizing fuzzy logic for applications in signal and image processing, including the development of fuzzy-based diffusion coefficient functions for selective noise smoothing.

      Medical Image Processing: Enhancing medical imaging techniques, such as de-speckling in ultrasound and X-ray images, and improving image de-noising using soft optimization techniques.

      Pattern Analysis in Machine Intelligence: Investigating pattern analysis and its applications within machine intelligence to improve the accuracy and efficiency of image processing algorithms.

Awards and Honors 

Rainer Knauf | Evolutionary Algorithms | Lifetime achievement Award

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Prof Dr Rainer Knauf |  Evolutionary Algorithms |  Lifetime achievement Award

Fachgebietsleiter für KI at  Technische Universität Ilmenau, Germany

Rainer Knauf is an apl. Prof. Dr.-Ing. habil., currently serving as the Chair of Artificial Intelligence at the Faculty of Computer Science and Automation, Technical University Ilmenau, Germany. He earned his Diploma Engineer (Dipl.-Ing.) in Electrical and Computer Engineering in 1987, followed by a Doctor of Engineering (Dr.-Ing.) in Computer Engineering in 1990, and a Doctor of Engineering habilitatus (Dr.-Ing. habil.) in Computer Science in 2000, all from Technical University Ilmenau. His research focuses on knowledge acquisition, validation, and refinement of intelligent systems, inductive inference, and machine learning.

 

profile

🎓 Education:

  • Dipl.-Ing. in Electrical and Computer Engineering
    Technical University Ilmenau, Germany
    📅 February 5, 1987
  • Dr.-Ing. in Computer Engineering
    Technical University Ilmenau, Germany
    📅 September 25, 1990
    Dissertation: “Applying Logic Programming to Design Knowledge Based Systems for Diagnostic Problems”
  • Dr.-Ing. habil. in Computer Science
    Technical University Ilmenau, Germany
    📅 November 15, 2000
    Habilitation: “Validating Rule Based Systems: A Complete Methodology”

💼 Professional Experience:

  • Full Professor (apl. Prof.)
    Chair of Artificial Intelligence, Technical University Ilmenau
    📅 March 2010 – Present
  • Associate Professor (Privatdozent)
    Chair of Artificial Intelligence, Technical University Ilmenau
    📅 April 2004 – February 2010
  • Assistant Professor (Privatdozent)
    Technical University Ilmenau
    📅 December 2000 – March 2004
  • Scientific Assistant
    Technical University Ilmenau
    📅 September 1991 – November 2000
  • Scientific Associate
    Ilmenau Institute of Technology
    📅 March 1987 – August 1991

🏅 Awards & Recognitions

  • Fellowship Awards from the Japan Society for the Promotion of Science 📜 (2008, 2011, 2015)
  • Graduate Faculty Scholar at the University of Central Florida 🎓 (2010)

Research Focus: Evolutionary Algorithms 🧬💡

Research Interests:

  • Optimization and Search Algorithms: Rainer Knauf’s work in evolutionary algorithms involves developing and improving algorithms for optimization and search problems. These algorithms are inspired by the principles of natural selection and genetics.
  • Artificial Intelligence Applications: He applies evolutionary algorithms to various AI challenges, including machine learning, robotics, and automated reasoning.
  • Knowledge Acquisition and Refinement: His research integrates evolutionary algorithms with knowledge-based systems to enhance the processes of knowledge acquisition, validation, and refinement.
  • Data Mining: Knauf explores the use of evolutionary algorithms in data mining, particularly in extracting meaningful patterns and insights from large datasets.
  • Inductive Inference: His work also includes using evolutionary algorithms for inductive inference, aiming to generalize from specific data to broader rules or patterns.

Citation:

Cited by:

  • All: 1082 citations
  • Since 2019: 253 citations

h-index:

  • Overall: 16
  • Since 2019: 7

i10-index:

  • Overall: 33
  • Since 2019: 4

Publication Top Notes:

  • “Didactic design through storyboarding: Standard concepts for standard tools”
    • Authors: KP Jantke, R Knauf
    • Publication: Proceedings of the 4th International Symposium on Information and Communication Technologies
    • Citations: 122 (2005)
    • Summary: This paper explores the use of storyboarding as a method for didactic design, emphasizing standard concepts to standardize tools for educational purposes.
  • “A framework for validation of rule-based systems”
    • Authors: R Knauf, AJ Gonzalez, T Abel
    • Publication: IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
    • Citations: 80 (2002)
    • Summary: This paper presents a comprehensive framework for validating rule-based systems, addressing the need for systematic validation processes in artificial intelligence.
  • “Validation of human behavior representation”
    • Authors: SY Harmon, VB Barr, AJ Gonzalez, DC Hoffmann, R Knauf
    • Publication: University Library
    • Citations: 45 (2006)
    • Summary: The authors discuss methodologies for validating models of human behavior representation, crucial for developing reliable AI systems that simulate human actions.
  • “Modeling didactic knowledge by storyboarding”
    • Authors: R Knauf, Y Sakurai, S Tsuruta, KP Jantke
    • Publication: Journal of Educational Computing Research
    • Citations: 39 (2010)
    • Summary: This research focuses on the use of storyboarding to model didactic knowledge, enhancing the design and delivery of educational content through structured visual methods.
  • “Toward reducing human involvement in validation of knowledge-based systems”
    • Authors: R Knauf, S Tsuruta, AJ Gonzalez
    • Publication: IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans
    • Citations: 25 (2006)
    • Summary: This paper proposes methods to minimize human intervention in the validation process of knowledge-based systems, aiming for more autonomous and efficient validation techniques.
  • “Tweet credibility analysis evaluation by improving sentiment dictionary”
    • Authors: T Kawabe, Y Namihira, K Suzuki, M Nara, Y Sakurai, S Tsuruta, R Knauf
    • Publication: 2015 IEEE Congress on Evolutionary Computation (CEC)
    • Citations: 24 (2015)
    • Summary: This work evaluates the credibility of tweets by enhancing sentiment dictionaries, leveraging evolutionary computation techniques to improve the accuracy of sentiment analysis.
  • “A simple optimization method based on backtrack and GA for delivery schedule”
    • Authors: Y Sakurai, K Takada, N Tsukamoto, T Onoyama, R Knauf, S Tsuruta
    • Publication: 2011 IEEE Congress of Evolutionary Computation (CEC)
    • Citations: 22 (2011)
    • Summary: The authors present an optimization method combining backtracking and genetic algorithms (GA) to improve delivery scheduling, demonstrating the application of evolutionary algorithms in logistics.
  • “Generation of a minimal set of test cases that is functionally equivalent to an exhaustive set, for use in knowledge-based system validation”
    • Authors: T Abel, R Knauf, AJ Gonzalez
    • Publication: Proceedings of the 9th FLAIRS Conference
    • Citations: 22 (1996)
    • Summary: This paper discusses a method for generating a minimal set of test cases that maintains functional equivalence to an exhaustive set, enhancing the efficiency of knowledge-based system validation.
  • “Modeling academic education processes by dynamic storyboarding”
    • Authors: Y Sakurai, S Dohi, S Tsuruta, R Knauf
    • Publication: Journal of Educational Technology & Society
    • Citations: 21 (2009)
    • Summary: The study models academic education processes through dynamic storyboarding, offering a structured approach to designing and implementing educational curricula.
  • “Validating Rule-Based Systems: A Complete Methodology”
    • Author: R Knauf
    • Publication: Shaker
    • Citations: 21 (2000)
    • Summary: This book provides a comprehensive methodology for the validation of rule-based systems, detailing systematic approaches to ensure the reliability and accuracy of these systems.

 

 

Zhidong CAO | Artificial Intelligence Award | Best Researcher Award

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Mr Zhidong CAO | Artificial Intelligence Award | Best Researcher Award

Mr Zhidong CAO, Institute of Automation, Chinese Academy of Sciences, China

Zhidong Cao 🎓 is a prominent Professor and Principal Investigator at the National Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences. He holds a Doctor of Science degree from the Institute of Geographic Sciences and Natural Resources Research, CAS. With over a decade of experience at CAS, Cao has contributed significantly to AI and automation research, leading over 20 national-level projects. His scholarly impact includes 120+ papers in prestigious journals and international conferences, along with authoring 3 books. Cao has been honored with multiple awards, highlighting his substantial contributions to Chinese scientific advancement.

Publication profile

Scopus

Education

Zhidong Cao 📚 pursued a rigorous academic journey that culminated in a Ph.D. from the Institute of Geographic Sciences and Natural Resources Research at the Chinese Academy of Sciences, completed from September 2005 to July 2008. Prior to his doctoral studies, he earned a Master’s degree from Changsha University of Science and Technology, spanning from September 2002 to July 2005. Cao’s educational foundation began with a Bachelor’s degree, also from Changsha University of Science and Technology, covering the period from September 1997 to July 2001. These academic milestones provided him with a comprehensive background for his subsequent influential research career in artificial intelligence and automation.

Experience