Pratiksha Chaudhari | Machine Learning | Best Researcher Award

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Ms. Pratiksha Chaudhari | Machine Learning | Best Researcher Award

Ms. Pratiksha Chaudhari | Machine Learning | Doctoral Candidate at The University of Alabama | United States

Ms. Pratiksha Chaudhari is a dedicated researcher and emerging academic in the field of Computer Science, specializing in Artificial Intelligence (AI), Machine Learning (ML), and Computer Vision. She is currently pursuing her Ph.D. in Computer Science at the University of Alabama, USA, where her work focuses on developing intelligent and data-driven systems for smart buildings and environmental monitoring. She holds a Master of Science in Computer Science and a Bachelor of Engineering in Computer Engineering from the University of Pune, India, both completed with distinction. Throughout her academic career, Ms. Pratiksha Chaudhari has demonstrated exceptional technical proficiency, combining theoretical depth with practical implementation in areas such as deep learning architectures, AI-based automation, and hydrological modeling. Professionally, she has gained valuable experience as a Graduate Research Assistant and Teaching Assistant at the University of Alabama, contributing to federally funded projects by the Cooperative Institute for Research to Operations in Hydrology (CIROH), U.S. Geological Survey (USGS), and the Great Lakes Protection Fund (GLPF). Her expertise spans Python, C++, PyTorch, TensorFlow, OpenCV, and QT Creator, alongside an ability to build and optimize large-scale AI frameworks for IoT and environmental data analysis. Her research interests include smart infrastructure, sustainable AI systems, microplastic detection, and federated learning-based IoT applications. Ms. Chaudhari has published multiple peer-reviewed papers in IEEE and Scopus-indexed journals, contributing to the advancement of applied AI research. She has been recognized for her academic excellence, innovative research contributions, and mentoring roles in interdisciplinary learning environments. With her growing portfolio of impactful publications and ongoing collaborations, Ms. Pratiksha Chaudhari continues to demonstrate strong potential as a future leader in AI research, committed to creating intelligent, ethical, and sustainable technologies for real-world applications.

Profile: ORCID | Google Scholar

Featured Publications 

  1. Chaudhari, P. (2025). Translution: A Hybrid Transformer–Convolutional Architecture with Adaptive Gating for Occupancy Detection in Smart Buildings. Electronics. 5 Citations.

  2. Chaudhari, P. (2024). Fundamentals, Algorithms, and Technologies of Occupancy Detection for Smart Buildings Using IoT Sensors. Sensors. 8 Citations.

  3. Chaudhari, P. (2024). Deep Learning-Based Streamflow Reconstruction Using Hydro-Transformer Models for Climate Data Analysis. Environmental Modelling & Software. 4 Citations.

  4. Chaudhari, P. (2023). Real-Time Detection and Classification of Microplastic Particles Using OpenCV and Raman Spectroscopy. Journal of Environmental Informatics. 6 Citations.

  5. Chaudhari, P. (2023). Federated Learning Models for Anomaly Detection in IoT-Enabled Smart Environments. IEEE Internet of Things Journal. 9 Citations.

  6. Chaudhari, P. (2022). AI-Powered Vocal Coaching System Using Wearable Sensors and Machine Learning Feedback Loops. Computers in Human Behavior. 3 Citations.

  7. Chaudhari, P. (2022). Developing an AI Framework for Smart Building Energy Optimization Using Transformer Networks. Applied Energy. 7 Citations.

 

Srujana Manigonda | Data Science | Research Excellence Distinction Award

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Ms. Srujana Manigonda | Data Science | Research Excellence Distinction Award 

Ms. Srujana Manigonda | Data Science – Capital One, United States

Srujana Manigonda is an accomplished Data Scientist and Data Analyst with a strong background in statistical data analysis, machine learning, data governance, and business intelligence. With years of expertise in handling large-scale data processing, ETL development, and predictive modeling, she has played a pivotal role in transforming enterprise data ecosystems. Her contributions to data lineage, financial analytics, and scalable reporting solutions have significantly impacted major industries, including finance, manufacturing, and technology. As a recognized researcher, she has published multiple papers in renowned journals, advancing the field of data science and analytics. Through her research and technical proficiency, she has established herself as a leader in data-driven decision-making and AI innovation.

Professional Profile :

Google Scholar

Education

Srujana Manigonda pursued her Master’s in Business and Information Systems from a prestigious institution, equipping her with advanced analytical and technical skills essential for modern data science applications. Prior to that, she earned a Bachelor’s degree in Information Technology, laying the foundation for her expertise in database management, software development, and algorithmic problem-solving. Her academic journey reflects a strong commitment to leveraging data science for industry transformation and shaping the future of data analytics and governance.

Experience

With extensive experience in data analytics, data governance, and AI-driven decision-making, Srujana has worked on high-impact projects across multiple industries. She has led initiatives in enterprise data systems, financial reporting automation, and digital marketing analytics, driving business intelligence and operational efficiency. Her work in cloud computing, data engineering, and machine learning model development has provided businesses with actionable insights, resulting in optimized business processes and cost savings. Throughout her career, she has collaborated with cross-functional teams, data engineers, and executives, ensuring the seamless integration of AI-driven solutions into enterprise frameworks. Additionally, her role as a peer reviewer for reputed scientific journals has contributed to the advancement of research methodologies in data science and AI.

Research Interest

Srujana’s research focuses on data governance, machine learning, data privacy, and AI-driven analytics. She is passionate about developing scalable data infrastructures, ensuring data integrity, security, and ethical AI applications. Her work explores metadata management, financial technology analytics, and predictive modeling to drive efficient business strategies. She is also deeply invested in researching automated data lineage tracking, anomaly detection, and enterprise data security frameworks, which are crucial for ensuring trustworthy AI systems. Through her research, she aims to bridge the gap between industry and academia, fostering innovation in big data analytics and cloud-based AI solutions.

Awards

Srujana Manigonda has received prestigious accolades recognizing her contributions to data analytics and research excellence. She was honored with the Titan Business Award (2024) for her leadership in data-driven innovation. Additionally, she received the Global Recognition Award (2024) for her outstanding research contributions to enterprise data management and analytics. In 2024, she was awarded the International Distinguished Researcher Award in Data Analytics, further solidifying her reputation as a leading expert in data science. Her ability to translate complex data into meaningful insights has earned her widespread recognition from both industry and academia.

Publications

📄 “Scaling Enterprise Data Systems for Complex Reporting and Analytics at the Enterprise Level” – IJACT, 2024
📄 “Empowering Data-Driven Decision Making in Manufacturing” – ESP JETA, 2021
📄 “Data Privacy and Sovereignty in Financial Technology: Governance Strategies for Global Operations” – IJSAT, 2021
📄 “The Role of Metadata Management in Data Governance: Enhancing Visibility and Control Across Complex Pipelines” – IJIRMPS, 2021
📄 “Data Lineage and Traceability in Manufacturing: Achieving End-to-End Data Visibility” – IJIRMPS, 2020
📄 “Data Governance in Manufacturing: Protecting Intellectual Property and Ensuring Data Integrity” – IJIRCT, 2019
📄 “Advanced Data Quality Assurance Techniques in Financial Data Processing: Beyond the Basics” – IJIRMPS, 2022

Conclusion

Srujana Manigonda’s contributions to data science, AI research, and enterprise analytics have positioned her as a pioneer in data-driven innovation. Her ability to bridge the gap between research and industry applications has led to breakthrough advancements in data governance, financial technology, and large-scale data processing. Through her academic excellence, extensive research, and real-world impact, she continues to shape the future of AI-driven business intelligence. With a strong foundation in data science methodologies, cloud computing, and enterprise analytics, Srujana remains committed to driving transformative change in the field. Her visionary approach and relentless pursuit of excellence make her a deserving candidate for the Research Excellence Distinction Award.