Anjan Kumar Reddy Ayyadapu | Computer Science | Research Excellence Award

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Mr. Anjan Kumar Reddy Ayyadapu | Computer Science | Research Excellence Award

Bigdata Solution Architect / IT Cloudera | The University of Cloudera | United States

MR. Anjan Kumar Reddy Ayyadapu is a researcher focused on artificial intelligence, machine learning, and cloud security, particularly in the application of AI-driven big data analytics to strengthen cybersecurity frameworks. His research addresses critical areas such as privacy-preserving techniques, secure cloud infrastructures, and intelligent incident response systems within multi-cloud environments. By integrating machine learning models with advanced cryptographic methods, his work aims to develop scalable and efficient solutions for safeguarding sensitive data in distributed systems. He has authored 5 scholarly publications, accumulating 73 citations and an h-index of 3, demonstrating measurable research impact. His contributions continue to support the advancement of secure, intelligent, and resilient cloud computing technologies in modern digital ecosystems.

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Alexandra Takou | Computer Science | Research Excellance Award

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 Dr. Alexandra Takou | Computer Science | Research Excellance Award

Post Doctoral Researcher | The University of  Thessaly | Greece

Dr. Alexandra Takou conducts research in hardware security, reliability-aware VLSI design, and fault-tolerant integrated circuits, with particular emphasis on hardware Trojans, electromagnetic and power grid based attacks, and soft error propagation mechanisms. Her work introduces sensitivity-aware and reliability-driven methodologies for Trojan design, placement, and security closure, addressing emerging threats in advanced semiconductor technologies. She has authored 5 peer-reviewed research documents published in reputable conferences and international journals, contributing novel approaches to EM-based attacks, SET-induced soft errors, and secure circuit design methodologies. Her publications have accumulated 7 citations, and she holds an h-index of 2, reflecting a focused and developing impact within the hardware security and electronic design automation research domains.

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Kianeh Kandi | Machine Learning | Academic Excellence Award

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Mrs Kianeh Kandi |  Machine Learning |  Academic Excellence Award

Academic Researcher at politechnic of dimadrid,  Spain

Mrs. Kianeh Kandi is an accomplished software developer and researcher with a robust foundation in computer science and a passion for innovative solutions. Currently pursuing her PhD in Software Systems and Computing at the Polytechnic University of Madrid, she has demonstrated expertise in machine learning, data mining, statistical methods, and high-impact research.

Profile:

📚 Education:

  • PhD Candidate in Software Systems and Computing, Polytechnic University of Madrid (2022 – Present)
  • Bachelor and Master of Industrial Management, Azad University of Arak (2004 – 2011)
  • Bachelor of IT (Networking), Arak University (2017 – 2019)

🎯 Research & Professional Experience:

  • Researcher, Polytechnic University of Madrid (2022 – Present):
    Conducting innovative research on credit card risk assessment using machine learning and developing neural network models to predict and mitigate financial risks.
  • Specialist, Dana Insurance Company (2018 – 2022):
    Managed market risk assessments and drove sales operations to enhance revenue growth.
  • Digital Marketing Expert, Aryanik Software Company (2016 – 2017):
    Improved user experience through website design and executed digital marketing strategies.
  • Project Planner, Sala Dairy Company (2010 – 2011):
    Boosted production efficiency and optimized processes using mathematical methods.

🧠 Research Contributions:

  • Thesis: Optimal Scheduling in a Milk Production Line Based on Mixed Integer Linear Programming
  • Publications:
    • Enhancing Performance of Credit Card Models Using LSTM Networks and XGBoost Algorithms
    • Evaluating Deep Convolutional Neural Networks and Support Vector Regression for Creditworthiness Prediction

💡 Key Skills:

  • Programming Languages: Python, Java, C++
  • Machine Learning Tools: TensorFlow, PyTorch
  • Technologies: Docker, large-scale data processing, Power BI, IBM SPSS
  • Research Expertise: Neural networks, statistical data analysis, synthetic data generation

Publication Top Notes:

  • “Optimal Scheduling in a Milk Production Line Based on Mixed Integer Linear Programming”

  • “Enhancing Performance of Credit Card Models by Utilizing LSTM Networks and XGBoost Algorithms”

  • “Evaluating the Performance of Deep Convolutional Neural Networks and Support Vector Regression for Creditworthiness Prediction in the Financial Sector”