Swathi Suddala | Information Technology | Women Researcher Award

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Mrs. Swathi Suddala | Information Technology | Women Researcher Award

Data Analyst at SP Teks, Inc, United States

Swathi Suddala is a highly analytical and results-driven Data Scientist with over 8 years of experience in the IT industry. She specializes in delivering innovative, data-driven solutions through Data Science, Machine Learning, and Data Engineering. With hands-on expertise in Python, R, SQL, and tools like Power BI and Tableau, she thrives in transforming complex datasets into strategic insights. Swathi is known for her problem-solving mindset, strong communication skills, and passion for continuous learning, making her a valuable asset across domains such as finance, supply chain, and technology. 🌐📊🧠

Publication Profile

Google Scholar

Academic Background

Swathi holds a Master of Science in Information Technology Management from the University of Wisconsin, Milwaukee, USA (2023), and a Master of Technology in Environmental Geomatics from JNTU University, Hyderabad, India (2014). Her academic foundation blends technical, managerial, and environmental perspectives, equipping her with a multidisciplinary approach to problem-solving. She has also contributed significantly to academic research during her postgraduate studies and continued professional development through certifications and technical training. 🎓🧑‍🎓📚

Professional Background

Swathi has served in various impactful roles across global organizations like Charles Schwab, IT Intellect Micro Solutions, Cred Avenue, and Hoch Technologies. She has designed machine learning models, performed data visualization, implemented CI/CD pipelines, and worked extensively with NLP and LLMs. Her experience spans finance, supply chain, and enterprise IT domains, where she has driven improvements in operations, analytics, and decision-making through data science. She brings strong expertise in Python, SQL, Power BI, Spark, and cloud platforms like AWS and Azure. 🌍👩‍💻📈

Awards and Honors

Swathi is a Salesforce Data Cloud Consultant Certified professional and has earned recognition for her contributions to academic and applied research. Her work has been published in peer-reviewed journals, reflecting her dedication to advancing knowledge in Data Science and AI. She has led impactful academic and professional projects and consistently received accolades for her innovation and leadership in technology, analytics, and AI research. 🥇📑🎖️

Research Focus

Swathi’s research focuses on leveraging cutting-edge Data Science techniques, including Generative AI, LLMs, and Edge Computing. Her published works explore hybrid ARIMA-LSTM models for demand forecasting, RAG systems for enhancing LLMs, and cloud-native strategies for IoT. Her academic curiosity fuels her drive to explore the intersections of AI, big data, and real-time analytics, enabling smarter, faster, and more scalable systems for industry and research. She thrives at the forefront of innovation, making impactful contributions to the future of intelligent systems. 🧪📈🤖

Publication Top Notes

📄 Enhancing Generative AI Capabilities Through Retrieval-Augmented Generation Systems and LLMs
📅 Year: 2024 |Cited by: 3

📄 Harnessing Cloud Technology for Real-Time Machine Learning in Fraud Detection
📅 Year: 2023 |Cited by: 1

📄 Ethical Challenges and Accountability in Generative AI: Managing Copyright Violations and Misinformation in Responsible AI Systems
📅 Year: 2024

Conclusion

Swathi Suddala stands out as a remarkable candidate for the Research for Women Researcher Award, bringing together over 8 years of rich experience in data science with a strong academic foundation, including dual master’s degrees from the University of Wisconsin, USA, and JNTU, India. Her research contributions span high-impact areas such as Edge Computing, IoT, Hybrid ARIMA-LSTM models, and Retrieval-Augmented Generation systems, published in reputable journals and cited for their relevance and innovation. Professionally, she has delivered real-world solutions in finance, supply chain, and tech industries, showcasing expertise in machine learning, NLP, LLMs, and cloud-based model deployment. With hands-on proficiency in Python, R, Tableau, Power BI, and a consistent track record of impactful projects—from vaccine scheduling to forest fire prediction—Swathi exemplifies the fusion of academic excellence, technological innovation, and applied leadership, making her a highly deserving nominee for this prestigious recognition.

 

 

Lakmini Prarthana Jayasinghe | Data Science | Best Researcher Award

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Dr Lakmini Prarthana Jayasinghe | Data Science | Best Researcher Award

Researcher, University of Southern Queensland, Australia 🌟

Lakmini Mudiyanselage is a dedicated researcher and academic with a passion for data science and artificial intelligence, specializing in hydrological forecasting and environmental applications. Based in Toowoomba, Queensland, she leverages her expertise to develop predictive models that address critical climate challenges in Australia, particularly in drought-prone regions. With a Ph.D. in Artificial Intelligence and a background in mathematics, Lakmini is committed to advancing scientific research through innovative data-driven methodologies and deep learning techniques.

Profile

Scopus

Education 🎓

Lakmini Mudiyanselage has a solid academic foundation marked by her advanced studies in artificial intelligence and mathematics. She earned her Doctor of Philosophy in Artificial Intelligence from the University of Southern Queensland in 2023, where she focused on cutting-edge AI applications to solve environmental challenges. Prior to this, she completed a Master of Philosophy in Mathematics in 2014 and a Bachelor of Science in Mathematics in 2008, both from the University of Kelaniya. This extensive background in mathematics and AI equips Lakmini with the analytical and computational skills needed to contribute significantly to data science and environmental studies, enabling her to develop sophisticated predictive models and insights that address critical climate issues.

Experience 🧑‍🏫

Researcher | UniSQ Advanced Data Analytic Lab (2020 – Present)
Lakmini leads efforts in predictive model development for hydrological parameters, working with extensive climate datasets to advance environmental forecasting. Her work has attracted significant funding and collaborative support, demonstrating her impact on hydrological research.

Senior Lecturer in Mathematical Sciences | Wayamba University of Sri Lanka (2010 – 2020)
In her decade-long academic career, Lakmini contributed to curriculum development and student mentorship. She also supervised student research and served as Acting Head of the Department, guiding students in mathematical modeling and AI-driven solutions.

Research Interest 🔍

Lakmini’s research focuses on leveraging artificial intelligence for environmental forecasting, with special attention to climate and hydrological data modeling. Her projects utilize hybrid machine learning models, such as Long Short-Term Memory networks, to enhance predictions related to evaporation, soil moisture, and evapotranspiration in regions affected by climate variability.

Awards 🏆

Lakmini Mudiyanselage has been honored with prestigious awards that reflect her academic excellence and research contributions. In 2023, she received the Award of Excellence in Doctoral Research from the University of Southern Queensland, recognizing her achievement of the highest possible result in her doctoral research examination. Earlier, in 2008, she was awarded the Physical Science Award in Mathematics by the Sri Lanka Association for the Advancement of Science for her groundbreaking work on confluent hypergeometric differential equations. These accolades underscore her dedication to advancing mathematical and AI-driven research, particularly in fields with impactful applications.

Publications 📚

“Development and Evaluation of Hybrid Deep Learning Long Short-Term Memory Network Model for Pan Evaporation Estimation” – Journal of Hydrology, 2022
Read here
Cited by multiple research articles examining predictive environmental modeling.

“Deep Multi-Stage Reference Evapotranspiration Forecasting Model: Multivariate Empirical Mode Decomposition Integrated with Boruta-Random Forest Algorithm” – IEEE Access, 2021
Read here
Referenced in studies focused on data-driven environmental predictions.

“Forecasting Multi-Step Soil Moisture with Three-Phase Hybrid Wavelet-Least Absolute Shrinkage Selection Operator-Long Short-Term Memory Network (moDWT-Lasso-LSTM) Model” – MDPI Water, 2023
Read here
Influential in soil moisture forecasting literature and widely cited in AI-based hydrological research.

Conclusion

Lakmini Mudiyanselage is an exceptional candidate for the Best Researcher Award. Her groundbreaking work in artificial intelligence and environmental data science addresses pressing global challenges, and her commitment to academic mentorship further underscores her dedication to scientific advancement and community service. Her accomplishments align well with the award’s objectives, making her highly deserving of this recognition.