Kirill Poletkin | Engineering | Best Research Article Award

Prof. Kirill Poletkin | Engineering | Best Research Article Award

Hefei University of Technology | China

Professor Kirill V. Poletkin is a distinguished researcher and academic specializing in micro- and nano-scale electromechanical systems, contactless levitation micro-actuators, MEMS inertial sensors, and precision instrumentation. He currently serves as a Professor (Talents Programme) at the School of Instrument Science and Optoelectronics Engineering, Hefei University of Technology, China. Prof. Poletkin earned his Ph.D. in Control Systems, Informatics, and Electrical Engineering from the Moscow Aviation Institute in 2007, where his doctoral research focused on closed-loop rotor vibratory gyroscopes. He obtained his M.Eng. with honors from Nizhny Novgorod State Technical University, with award-winning research in vibration theory and dynamically tuned gyroscopes recognized by the Ministry of Education and Science of the Russian Federation. With over two decades of international research experience, he has held academic and research positions at leading institutions including the Karlsruhe Institute of Technology, University of Freiburg, Nanyang Technological University, Innopolis University, and New Uzbekistan University. He is a former Alexander von Humboldt Research Fellow and has served as Principal Investigator on multiple competitively funded projects supported by the German Research Foundation (DFG) and Chinese provincial agencies. Prof. Poletkin has authored over 86 scientific publications, including 37 peer-reviewed journal articles, book chapters, and a Springer monograph titled Levitation Micro-Systems: Applications to Sensors and Actuators. His pioneering contributions to zero–spring-constant contactless suspensions, hybrid inductive–electrostatic levitation systems, and semi-analytical electromagnetic modeling have enabled new generations of high-precision sensors, actuators, and micro-transport technologies.

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Featured Publications

Soujanya Reddy Annapareddy | Engineering | Women Researcher Award

Mrs. Soujanyareddy Annapareddy | Engineering | Women Researcher Award

TAE Power Solutions | United States

Mrs. Soujanya Reddy Annapareddy is a seasoned Firmware Automation and Software Test Engineer with over 7.5 years of professional experience in embedded systems testing, automation frameworks, and data-driven validation methodologies. Her research and professional interests lie at the intersection of firmware validation, automation engineering, and intelligent system testing, focusing on how advanced test automation techniques enhance the performance, reliability, and scalability of embedded and IoT systems. At TAE Power Solutions, she has contributed to the automation and validation of Battery Energy Storage System (BESS) control platforms, integrating hardware-in-the-loop (HIL) environments and open-source frameworks such as PyTest, pandas, and matplotlib to improve regression coverage and testing efficiency. Her work explores the application of data analytics, fault-injection methods, and CI/CD pipeline integration in firmware testing to ensure real-world performance and fault tolerance. Her prior experience at Google Inc. involved automation testing for Android devices, wearable technologies, and data center systems, where she developed automation scripts in Python, Go, and C++, applied object-oriented design principles, and leveraged tools such as Mobly, Blueberry, and Buganizer for large-scale system validation. Soujanya’s analytical research focuses on automated testing frameworks, system-level reliability modeling, and signal strength optimization in wireless and connectivity domains. Methodologically, she employs Python-based automation, statistical analysis, and cloud-integrated validation frameworks, with hands-on experience in Linux environments, GCP cloud infrastructure, and RF system automation. Her interdisciplinary expertise bridges firmware engineering, test analytics, and computer science, offering insights into how automation accelerates innovation in embedded systems. Soujanya holds a Master of Science in Computer Technology from Eastern Illinois University and a Bachelor of Technology in Electronics and Communication Engineering from Jawaharlal Nehru Technological University Hyderabad (JNTUH), where she graduated with distinction. Her academic projects and industrial research underscore her commitment to advancing intelligent automation, embedded testing, and data-driven system optimization in modern technology ecosystems.

Profile: Google Scholar

Featured Publications

Annapareddy, S. R. (2025). Edge AI for real-time fault detection in embedded systems. International Journal of Emerging Trends in Computer Science and Information Systems.

Annapareddy, S. R. (2024). Managing power flows and energy efficiency in embedded systems for BESS. IJAIDR – Journal of Advances in Developmental Research, 15(2), 1–5.

Annapareddy, S. R. (2024). Advanced fault detection and diagnostics in embedded control units for BESS. IJSAT – International Journal on Science and Technology, 15(4).

Annapareddy, S. R. (2024). Firmware architecture and safety standards in battery energy storage systems. International Journal of Innovative Research in Engineering.

Annapareddy, S. R. (2024). Optimizing Android device testing with automation frameworks. International Journal of Innovative Research and Creative Technology, 10(4), 1–7.

Annapareddy, S. R. (2024). Real-world applications of Python in firmware and software automation. International Journal of Innovative Research and Creative Technology, 10(2), 1–6.

Annapareddy, S. R. (2024). Advancements in firmware testing and validation techniques. ESP Journal of Engineering & Technology Advancements, 4(3).

Yonas Gezahegn | Engineering | Best Researcher Award

Dr. Yonas Gezahegn | Engineering | Best Researcher Award

Nestle Purina/Washington State University | United States

Dr. Yonas A. Gezahegn is a distinguished research and development engineer specializing in thermal and food process engineering, with extensive expertise in microwave-assisted thermal sterilization and pasteurization, heat and mass transfer, biochemical engineering, and food safety. With over 15 years of academic and industry experience, Dr. Gezahegn has developed a strong reputation for integrating engineering principles with advanced experimental and computational methods to optimize food processing and thermal treatment technologies. His research bridges the gap between fundamental engineering science and industrial applications, ensuring both efficiency and safety in food production systems. Dr. Gezahegn’s academic training includes a PhD in Biological Systems Engineering (Food Engineering) from Washington State University, where he focused on optimization of microwave-assisted thermal sterilization and pasteurization processes using analytical models and computer simulations. His prior degrees include a Master’s in Chemical Engineering from Addis Ababa University, and a Bachelor’s in Food and Biochemical Technology from Bahir Dar University, where his research addressed critical challenges in oil and fat extraction, fermentation, and food quality assessment. Currently serving as R&D Process Engineer – Thermal Process Expert at Nestle Purina, Dr. Gezahegn leads projects on process improvement, thermal sterilization validation, and retort commissioning for low-acid and acidified food products. He has successfully managed large-scale research projects, including microwave-assisted thermal processing of breaded meats, temperature distribution studies, and process optimization for commercial food production. His work also encompasses pilot-plant scale-up, analytical characterization, and data-driven modeling to ensure precise control of thermal processing conditions. Dr. Gezahegn has published over 12 peer-reviewed journal articles in top-tier journals, including the Journal of Food Engineering, Current Research in Food Science, Innovative Food Science & Emerging Technologies, Food Science and Nutrition, and LWT – Food Science and Technology. His publications focus on microwave-assisted processing, dielectric properties of foods, thermal pasteurization optimization, and oil extraction technologies. Notably, his research has led to multiple patents, including a utility model for screw expeller-based shea butter extraction and pending patents on gluten-free pizza crust and crispy breaded food processes. His work has been widely cited in the food engineering and process optimization communities, highlighting his influence in both academic and industrial research. In addition to research, Dr. Gezahegn has contributed extensively to industry-academic collaborations, securing competitive grants such as the USDA-NIFA and WSU Hatch projects totaling over USD 4 million, and Ethiopian national projects on drying and fermentation of plant-based products. Dr. Gezahegn published 12+ peer-reviewed articles, 550 Citations and 10 H-index.  His projects integrate  analytical modeling, simulation, experimental validation, and process design to improve efficiency, safety, and nutritional quality in food production. Dr. Gezahegn has served as a reviewer for journals including Applied Food Research, Journal of Food Engineering, and the International Journal for Vitamin and Nutrition Research, reflecting his standing in the research community. His leadership extends to professional societies, including IFT, IMPI, SoFE, and ASABE, and he has held roles such as President of the Food Engineering Club and departmental representative in the Graduate and Professional Student Association. Overall, Dr. Gezahegn’s work demonstrates a sustained commitment to advancing food engineering, thermal process optimization, and industrial innovation, making significant contributions to improving food safety, process efficiency, and product quality. His research portfolio combines rigorous academic scholarship with practical applications, establishing him as a leading expert in thermal food processing and microwave-assisted sterilization technologies.

Profiles: Scopus | Orcid

Featured Publications

Gezahegn, Y., Tang, J., et al. (2024). Development and validation of engineering charts: Heating time and optimal salt content prediction for microwave assisted thermal sterilization. Journal of Food Engineering, 369, 111909. https://doi.org/10.1016/j.jfoodeng.2023.111909

Gezahegn, Y., Yoon-Ki, H., Tang, J., et al. (2023). Development and validation of analytical charts for microwave assisted thermal pasteurization of selected food products. Journal of Food Engineering, 349, 111434. https://doi.org/10.1016/j.jfoodeng.2023.111434

Zhou, X., Gezahegn, Y., et al. (2023). Theoretical reasons for rapid heating of vegetable oils by microwaves. Current Research in Food Science, 7, 100641. https://doi.org/10.1016/j.crfs.2023.100641

Gezahegn, Y., Tang, J., Sablani, S., et al. (2021). Dielectric properties of water relevant to microwave assisted thermal pasteurization and sterilization of packaged foods. Innovative Food Science & Emerging Technologies, 74, 102837. https://doi.org/10.1016/j.ifset.2021.102837

Gezahegn, Y., Emire, S., & Asfaw, S. (2016). Optimization of Shea (Vitellaria paradoxa) butter quality using screw expeller extraction. Food Science & Nutrition, 4(6), 840–847. https://doi.org/10.1002/fsn3.351

Gezahegn, Y., Emire, S., & Asfaw, S. (2016). Effect of processing factors on Shea (Vitellaria paradoxa) butter extraction. LWT – Food Science and Technology, 66, 172–178. https://doi.org/10.1016/j.lwt.2015.10.036

 

Dayeong An | Engineering | Women Researcher Award | 13446

Dr. Dayeong An | Engineering | Women Researcher Award

Dr. Dayeong An, Medical College of Wisconsin, United States

Dr. Dana (Dayeong) An is a Postdoctoral Fellow in the Department of Radiology at Northwestern University with a strong interdisciplinary background in biomedical engineering, computational sciences, and statistics. Her research focuses on machine learning and probabilistic modeling for multimodal biomedical data integration, particularly in neurovascular and cardiac imaging. She has developed advanced AI frameworks for stroke outcome prediction, perfusion analysis, and cardiac strain estimation. With multiple peer-reviewed publications and awards, Dr. An brings expertise in deep learning, medical image processing, and translational AI for precision medicine.

Profile

ORCID

🎓 Early Academic Pursuits

Dr. Dana (Dayeong) An’s academic journey is rooted in a solid foundation of mathematics, statistics, and computational sciences. She began her higher education at Minnesota State University, earning a B.S. in Mathematics with a minor in Economics in 2012. Her strong mathematical background laid the groundwork for advanced study, leading her to pursue dual M.S. degrees in Mathematics and Statistics (2014) and Computational Sciences (2018). These degrees reflect a growing interest in data analysis, modeling, and algorithmic thinking—skills that would become central to her future research. Her academic path culminated in a Ph.D. in Biomedical Engineering from the Medical College of Wisconsin in 2024. During her doctoral training, Dr. An fused her analytical skills with biomedical applications, working at the intersection of medical imaging and machine learning. Her education reflects a rare combination of quantitative rigor and domain-specific insight, enabling her to tackle complex problems in healthcare and precision medicine.

🧠 Professional Endeavors

Dr. An currently serves as a Postdoctoral Fellow in the Department of Radiology at Northwestern University, where she applies advanced machine learning techniques to neurovascular and cardiac imaging data. Her professional roles have spanned research, teaching, and clinical applications. At the Medical College of Wisconsin, she worked as a Research Assistant, refining deep learning algorithms for myocardial strain analysis, MRI-based diagnostics, and experimental studies on cardiotoxicity in animal models. Earlier in her career, she served as an Adjunct Professor and Teaching Assistant at multiple institutions, including Marquette University, Globe University, and South Central College, where she taught a variety of math and statistics courses. This teaching experience showcases her commitment to education and her ability to communicate complex topics to diverse audiences.

🧪 Contributions and Research Focus

Dr. An’s research is centered on machine learning and probabilistic modeling for multimodal biomedical data integration. Her contributions span multiple domains:

  • Neurovascular Imaging: She has developed frameworks using Bayesian priors and transformer models to estimate physiological parameters from perfusion MRI data. She also works with large-scale databases such as NVQI-QOD to predict stroke outcomes and recurrence risks in intracranial atherosclerotic disease (ICAD).

  • Cardiac MRI and Strain Analysis: Dr. An fine-tuned U-Net and GAN architectures to automate strain generation and displacement field analysis from cine MRI images. These tools enhance early detection of cardiotoxicity and improve diagnostic accuracy.

  • Image Processing and Simulation: She built deep learning-based deformable registration tools to reduce motion artifacts in angiography and improve vascular fidelity. Additionally, she contributed to differentiable projection modeling for fluoroscopic pose estimation.

  • Translational AI: Her work aims to bridge the gap between algorithm development and clinical implementation, with models designed for real-time, patient-specific analysis.

Her research is not only technical but also translational, addressing real-world challenges in healthcare delivery and diagnostics.

🏆 Accolades and Recognition

Dr. An has received numerous honors for her research excellence and academic contributions:

  • Poster Competition Winner at Marquette University and the Medical College of Wisconsin.

  • Scholarship and Travel Grants from prestigious societies such as the Global Cardio Oncology Summit, ISMRM, and Marquette University.

  • Kayoko Ishizuka Award and Graduate Student Association Awards at MCW.

  • Recognition for conference presentations at RSNA, ISMRM, SCMR, and ASNR.

Her work has been published in well-regarded journals including Radiology and Oncology, Journal of Imaging Informatics in Medicine, and Tomography, reflecting her influence across multiple disciplines.

🌍 Impact and Influence

Dr. An’s interdisciplinary expertise positions her as a valuable contributor to both the academic and clinical communities. Her collaborations with leading institutions such as Cleveland Clinic and Purdue University demonstrate the broader impact of her research. Whether improving stroke outcome prediction or refining cardiac diagnostics, her contributions are making real-world differences in how clinicians approach patient care. She is also actively involved in professional societies like RSNA, ISMRM, IEEE, and the American Statistical Association, fostering knowledge exchange and staying at the forefront of innovation.

🌱 Legacy and Future Contributions

Looking ahead, Dr. An aspires to expand her impact by continuing to develop explainable, reliable, and patient-specific AI tools for medical imaging. Her future work will likely delve deeper into probabilistic deep learning, longitudinal outcome modeling, and integrated diagnostics using multi-modal data sources such as imaging, genomics, and electronic health records. She is poised to be a leader in translational AI, driving innovations that not only push the boundaries of computational medicine but also enhance patient outcomes and healthcare efficiency.

🔗 Final Thoughts

Dr. Dana (Dayeong) An exemplifies a new generation of biomedical engineers—fluent in mathematics, passionate about clinical impact, and committed to advancing the future of precision medicine through data-driven innovation. Her legacy is being built at the nexus of technology, healthcare, and humanity.

📄 Publication Top Notes

Radiation-Induced Cardiotoxicity in Hypertensive Salt-Sensitive Rats: A Feasibility Study

Author: Dayeong An; Alison Kriegel; Suresh Kumar; Heather Himburg; Brian Fish; Slade Klawikowski; Daniel Rowe; Marek Lenarczyk; John Baker; El-Sayed Ibrahim

Journal: Life

Year: 2025

Elucidating Early Radiation-Induced Cardiotoxicity Markers in Preclinical Genetic Models Through Advanced Machine Learning and Cardiac MRI

Author: Dayeong An; El-Sayed Ibrahim

Journal: Journal of Imaging

Year: 2024