Pardis Biglarbeigi | Computer Vision | Best Researcher Award

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Dr. Pardis Biglarbeigi | Arti  Vision | Best Researcher Award

👤 Dr. Pardis Biglarbeigi, University of Liverpool, United Kingdom

Pardis Biglarbeigi is a dedicated researcher and lecturer specializing in signal/image processing, data analytics, and artificial intelligence. She holds a BSc from Iran (2006-2010), an MSc from Italy (2011-2014), and a PhD in Engineering from Ulster University, UK (2015-2019). With over five years of teaching experience across multiple UK universities, she integrates research with academia, fostering interdisciplinary collaborations. Her expertise spans health data, bio-signal analysis, and pharmacological applications. She has made significant contributions to digital medicine, including NHS electronic health records analysis and ECG printout digitalization. As an editorial board member of npj Digital Medicine, she actively contributes to advancing AI-driven healthcare solutions. Pardis collaborates with Ulster University and the University of Liverpool to pioneer methodologies in Atomic Force Microscopy (AFM) and cardiovascular data science. Her work, published in high-impact journals such as ACS Nano and Science Advances, is shaping modern approaches in medical AI applications.

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Evaluation of Dr. Pardis Biglarbeigi for the Best Researcher Award

Dr. Pardis Biglarbeigi demonstrates a strong academic and research background, making her a competitive candidate for the Best Researcher Award. With a BSc, MSc, and PhD in Engineering, coupled with her experience as a Research Associate and Lecturer across multiple UK universities, she has built a multidisciplinary expertise in signal/image processing, data analytics, and AI-driven predictive models. Her transition into biomedical research and public health, particularly in pharmacology and therapeutics, showcases her adaptability and impact on healthcare innovations.

Her contributions to research are well-documented through her publications in high-impact journals such as ACS Nano, Small, Nanoscale Advances, Science Advances, and Expert Systems with Applications. Notably, her work on Wavelet Transform AFM (WT-AFM) has led to significant advancements in the characterization of biological materials. Additionally, her collaborations with Ulster University and the University of Liverpool have resulted in impactful research outcomes, including advanced methods for analyzing electronic health records.

🎓 Education

Pardis Biglarbeigi has a rich educational background in engineering and data analytics. She earned her BSc in Iran (2006-2010), followed by an MSc in Italy (2011-2014), where she refined her skills in computational modeling and data-driven research. Her academic journey culminated in a PhD in Engineering at Ulster University, UK (2015-2019), focusing on signal processing and AI applications in healthcare. During her PhD, she explored innovative computational methodologies, enhancing her expertise in interdisciplinary research. The transition from traditional engineering to digital health analytics was facilitated by her role as a Research Associate, where she delved into electronic health records and bio-signal/image processing. This robust academic foundation has positioned her at the forefront of AI-driven medical research. Now, as a Lecturer in Pharmacology and Therapeutics at the University of Liverpool, she applies her technical expertise to solve critical challenges in drug research and healthcare data analysis.

💼 Professional Experience 

Pardis Biglarbeigi has accumulated extensive experience in academia and research. She began her career as a Research Associate at Ulster University during her PhD, where she contributed to bio-signal/image processing and electronic health data analysis. Her expertise in computational modeling and AI led her to faculty roles at three UK universities, where she has been a lecturer for over five years. Currently, she is a Lecturer in Pharmacology and Therapeutics at the University of Liverpool, collaborating with medical professionals to address public health challenges, particularly in drug research. Pardis has played a pivotal role in projects such as the NHS electronic health records analysis and ECG printout digitalization with PulseAI. Her interdisciplinary collaborations have resulted in four high-impact publications and significant contributions to AI-driven healthcare analytics. As an editorial board member of npj Digital Medicine, she continues to drive innovation in medical AI applications and digital health solutions.

🏅 Awards and Recognition 

Pardis Biglarbeigi has been recognized for her contributions to AI-driven healthcare and biomedical signal processing. Her work has led to four high-impact publications in ACS Nano, Small, Nanoscale Advances, and Science Advances. She is an editorial board member of npj Digital Medicine, where she influences the future of AI applications in healthcare. Pardis has been an integral part of the CVD-COVID-UK/COVID-IMPACT consortium at the British Heart Foundation Data Science Centre, where she develops innovative analytical methods for complex health datasets. Her research on Wavelet Transform AFM (WT-AFM) has been widely acknowledged for its potential in enhancing biomedical material characterization. Additionally, her collaborations with NHS and PulseAI have positioned her as a leading figure in electronic health record analysis and digital signal processing. Through her groundbreaking contributions, she continues to shape the landscape of computational medicine and digital therapeutics, earning international recognition for her pioneering work.

🌍 Research Skills On Computer Vision

Pardis Biglarbeigi is a skilled researcher with expertise in signal/image processing, AI-driven predictive modeling, and biomedical data analytics. Her work focuses on integrating AI with electronic health data, contributing to groundbreaking research in digital medicine. She has developed innovative methodologies in Atomic Force Microscopy (AFM) for analyzing biological materials, leading to enhanced characterization techniques. As a member of the British Heart Foundation Data Science Centre, she designs advanced computational models for cardiovascular studies. Pardis has a strong foundation in time-series data analysis, machine learning, and statistical modeling, which she applies to healthcare applications. Her collaboration with NHS and PulseAI has enabled her to implement AI-based solutions for digital health record processing. With a track record of high-impact publications and interdisciplinary projects, she remains at the forefront of AI-driven healthcare research, pushing the boundaries of computational modeling in medical science.

📖 Publication Top Notes

  • Title: A data-driven simulator for the strategic positioning of aerial ambulance drones reaching out-of-hospital cardiac arrests: a genetic algorithmic approach
    Authors: C. Mackle, R. Bond, H. Torney, R. McBride, J. McLaughlin, D. Finlay, et al.
    Journal: IEEE Journal of Translational Engineering in Health and Medicine
    Citation Count: 26
    Year: 2020
  • Title: Partitioning the impacts of streamflow and evaporation uncertainty on the operations of multipurpose reservoirs in arid regions
    Authors: P. Biglarbeigi, M. Giuliani, A. Castelletti
    Journal: Journal of Water Resources Planning and Management
    Citation Count: 26
    Year: 2018
  • Title: COVID-19 modelling by time-varying transmission rate associated with mobility trend of driving via Apple Maps
    Authors: M. Jing, K.Y. Ng, B. Mac Namee, P. Biglarbeigi, R. Brisk, R. Bond, D. Finlay, et al.
    Journal: Journal of Biomedical Informatics
    Citation Count: 22
    Year: 2021
  • Title: Data-driven versus a domain-led approach to k-means clustering on an open heart failure dataset
    Authors: A. Jasinska-Piadlo, R. Bond, P. Biglarbeigi, R. Brisk, P. Campbell, F. Browne, et al.
    Journal: International Journal of Data Science and Analytics
    Citation Count: 20
    Year: 2023
  • Title: Epileptic multi-seizure type classification using electroencephalogram signals from the Temple University Hospital Seizure Corpus: A review
    Authors: N. McCallan, S. Davidson, K.Y. Ng, P. Biglarbeigi, D. Finlay, B.L. Lan, et al.
    Journal: Expert Systems with Applications
    Citation Count: 18
    Year: 2023
  • Title: What can machines learn about heart failure? A systematic literature review
    Authors: A. Jasinska-Piadlo, R. Bond, P. Biglarbeigi, R. Brisk, P. Campbell, et al.
    Journal: International Journal of Data Science and Analytics
    Citation Count: 10
    Year: 2022
  • Title: Data acquisition and imaging using wavelet transform: a new path for high-speed transient force microscopy
    Authors: A.F. Payam, P. Biglarbeigi, A. Morelli, P. Lemoine, J. McLaughlin, D. Finlay
    Journal: Nanoscale Advances
    Citation Count: 9
    Year: 2021
  • Title: Seizure classification of EEG based on wavelet signal denoising using a novel channel selection algorithm
    Authors: N. McCallan, S. Davidson, K.Y. Ng, P. Biglarbeigi, D. Finlay, B.L. Lan, et al.
    Conference: 2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference
    Citation Count: 8
    Year: 2021
  • Title: Epileptic seizure classification using combined labels and a genetic algorithm
    Authors: S. Davidson, N. McCallan, K.Y. Ng, P. Biglarbeigi, D. Finlay, B.L. Lan, et al.
    Conference: 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON)
    Citation Count: 7
    Year: 2022
  • Title: Many-objective direct policy search in the Dez and Karoun multireservoir system, Iran
    Authors: P. Biglarbeigi, M. Giuliani, A. Castelletti
    Conference: World Environmental and Water Resources Congress
    Citation Count: 7
    Year: 2014

Iustina Ivanova | Computer Science | Best Researcher Award

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Mrs. Iustina Ivanova | Computer Science | Best Researcher Award

👤 Mrs. Iustina Ivanova, FBK, Italy

Iustina Ivanova is an accomplished researcher in the field of Artificial Intelligence (AI) with a focus on computer vision and machine learning applications in real-world scenarios. She holds a Master’s degree in Artificial Intelligence from the University of Southampton, where she earned distinction for her research on neural networks for object detection. Currently, Iustina is engaged in AI research in smart agriculture at the Fondazione Bruno Kessler in Italy. Over the years, she has contributed to a variety of high-impact projects, including developing a recommender system for outdoor sport climbers and researching sensors for sports activity analysis. Her work has earned her several well-regarded publications and recognition in the AI and computer vision communities.

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🌟 Summary of Suitability for the Research for Best Researcher Award

Iustina Ivanova demonstrates exceptional qualifications for the “Research for Best Researcher Award.” Her academic background, professional experience, and research contributions highlight her significant impact on the fields of artificial intelligence (AI), machine learning, and computer vision. Her academic journey is distinguished by a Master’s degree in Artificial Intelligence with distinction from the University of Southampton and ongoing research pursuits during her Ph.D. studies. While her Ph.D. remains incomplete, the work she has undertaken—such as her contributions to recommender systems and computer vision—showcases her ability to address complex, real-world problems.

Professionally, Iustina’s research experience is diverse and impactful. At the Fondazione Bruno Kessler, she has been actively involved in applying AI to smart agriculture, addressing sustainability and innovation in the domain. Her previous roles, including as a Computer Vision Data Scientist and Data Science Moderator, further demonstrate her ability to bridge academia and industry.

🎓 Education

Iustina Ivanova has an impressive academic background in computer science and AI. She completed her Master of Science in Artificial Intelligence with distinction at the University of Southampton, UK, in 2018. Before that, she earned a Specialist degree in Software Engineering from Bauman Moscow State Technical University, Russia, in 2013. In 2019, she pursued a PhD in Computer Science at the Free University of Bolzano, Italy, although she later decided to focus more on practical AI applications. Her academic journey includes notable achievements such as developing research in neural networks for object detection, which has been the cornerstone of her professional career in AI.

💼  Professional Experience 

Iustina Ivanova has a diverse and robust professional background in AI and computer vision. She currently works as a researcher at the Fondazione Bruno Kessler, Italy, specializing in the use of AI for smart agriculture. Prior to this, Iustina served as a Data Science Moderator at Netology, Russia, where she designed and delivered online courses in statistics and mathematics for data science students. She also worked as a Computer Vision Data Scientist at OCRV, Russia, where she helped develop a video-based tracking system for railway workers, focusing on object detection and worker time measurement. Iustina’s role as a teacher of informatics and mathematics at Repetitor.ru involved preparing high school students for their final exams, ensuring that many students successfully entered top universities. Throughout her career, she has collaborated on numerous innovative projects in AI, particularly in outdoor sports and smart agriculture.

🏅Awards and Recognition 

Iustina Ivanova’s dedication and excellence in the field of AI have been recognized through multiple prestigious awards and accolades. Notably, she won several editions of the NOI Hackathon, including the SFSCON Edition (2021, 2022, 2024) and the Open Data Hub Edition (2022), showcasing her ability to create cutting-edge solutions in AI and data science. Her contributions to research and development in AI for sports activity analysis and computer vision have been published in highly regarded journals and conferences, such as the ACM Conference on Recommender Systems and IEEE Conferences. Iustina has also received recognition for her teaching contributions, inspiring future generations of data scientists. Her projects, especially those related to sports climbers’ recommender systems and sensor data analysis, have received wide acclaim for their innovation and real-world impact.

🌍 Research Skills On Computer Science

Iustina Ivanova’s research expertise spans artificial intelligence, machine learning, computer vision, and recommender systems. She is particularly skilled in using AI techniques to solve complex problems in real-world applications. Her work with neural networks for object detection and sensor data analysis has led to significant advancements in both sports and smart agriculture sectors. Iustina is proficient in Python, OpenCV, machine learning frameworks like PyTorch and TensorFlow, and data analysis tools such as Jupyter Notebook and Git. She is well-versed in the development of recommender systems and has implemented innovative solutions for outdoor sports, including climbing crag recommendations. Her interdisciplinary approach combines knowledge from software engineering, data science, and AI to design systems that enhance user experience and improve decision-making. Iustina is committed to the continual development of her skills, evident in her participation in advanced data science and deep learning courses, as well as her extensive practical work in AI.

📖 Publication Top Notes

  • Climbing crags repetitive choices and recommendations
    • Author: Ivanova, I.
    • Citation: Proceedings of the 17th ACM Conference on Recommender Systems, RecSys 2023
    • Year: 2023
    • Pages: 1158–1164
  • How can we model climbers’ future visits from their past records?
    • Authors: Ivanova, I., Wald, M.
    • Citation: UMAP 2023 – Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2023
    • Pages: 60–65
  • Introducing Context in Climbing Crags Recommender System in Arco, Italy
    • Authors: Ivanova, I.A., Wald, M.
    • Citation: International Conference on Intelligent User Interfaces, Proceedings IUI
    • Year: 2023
    • Pages: 12–15
  • Climbing crags recommender system in Arco, Italy: a comparative study
    • Authors: Ivanova, I., Wald, M.
    • Citation: Frontiers in Big Data
    • Year: 2023
    • Volume: 6, Article: 1214029
  • Map and Content-Based Climbing Recommender System
    • Authors: Ivanova, I.A., Buriro, A., Ricci, F.
    • Citation: UMAP2022 – Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2022
    • Pages: 41–45
  • Climbing Route Difficulty Grade Prediction and Explanation
    • Authors: Andric, M., Ivanova, I., Ricci, F.
    • Citation: ACM International Conference Proceeding Series
    • Year: 2021
    • Pages: 285–292
  • Climber behavior modeling and recommendation
    • Author: Ivanova, I.
    • Citation: UMAP 2021 – Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2021
    • Pages: 298–303
  • Knowledge-based recommendations for climbers
    • Authors: Ivanova, I., Andrić, M., Ricci, F.
    • Citation: CEUR Workshop Proceedings
    • Year: 2021
    • Volume: 2960
  • Climbing activity recognition and measurement with sensor data analysis
    • Authors: Ivanova, I., Andric, M., Janes, A., Ricci, F., Zini, F.
    • Citation: ICMI 2020 Companion – Companion Publication of the 2020 International Conference on Multimodal Interaction
    • Year: 2020
    • Pages: 245–249
  • Video and Sensor-Based Rope Pulling Detection in Sport Climbing
    • Authors: Ivanova, I., Andrić, M., Moaveninejad, S., Janes, A., Ricci, F.
    • Citation: MMSports 2020 – Proceedings of the 3rd International Workshop on Multimedia Content Analysis in Sports
    • Year: 2020
    • Pages: 53–60

Dr. SENTHIL G. A | Computer Science | Research Excellence Award

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Dr. SENTHIL G. A | Computer Science | Research Excellence Award🏆

Doctor. SENTHIL G. A, Agni College of Technology, India 🎓

Professional Profile

🌟Dr. G.A. Senthil: A Distinguished Career in Engineering and Technology 

🎓Early Academic Pursuits 

Dr. G.A. Senthil’s academic journey commenced with a Diploma in Computer Science and Engineering from the Technical Education Board, Tamil Nadu, where he graduated with a commendable 72% in 1991. He then pursued a Bachelor’s degree in Computer Science and Engineering from SIR. M. Visvesvaraya Institute of Technology, Bangalore University, graduating in 1997. His academic excellence continued with an M.Tech in Information Technology from Sathyabama University, Tamil Nadu, where he graduated with distinction in 2007. Dr. Senthil’s scholarly dedication culminated in a Ph.D. from Vels Institute of Science, Technology & Advanced Studies (VISTAS), Chennai, in 2022, with a thesis focused on enhancing energy-efficient cluster-based routing using hybrid particle swarm optimization for IoT sensor networks.

💼Professional Endeavors 

Dr. Senthil’s career spans over 27 years in various esteemed engineering colleges. His professional journey began at Sir M. Visvesvaraya Institute of Technology, Bangalore, as a Lecturer in Computer Science and Engineering. He subsequently held positions at Annai Mathammal Sheela Engineering College, Aarupadai Veedu Institute of Technology, and Dhaanish Ahmed College of Engineering, where he advanced from Lecturer to Senior Lecturer and eventually to Head of Department. He currently serves as an Associate Professor at AGNI College of Technology, Chennai. Dr. Senthil’s extensive teaching experience includes undergraduate and postgraduate courses, reflecting his deep commitment to education and student development.

🔍Contributions and Research Focus 

Dr. Senthil has made significant contributions to the field of computer science and engineering. His research interests include the Internet of Things (IoT), wireless sensor networks (WSN), and advanced algorithms. He has published 11 journal articles, 50 conference papers, and several book chapters in prestigious publications such as Springer and Wiley. His patent portfolio includes 7 published inventions and 5 grants. Dr. Senthil has also been involved in funded projects, contributing to the advancement of technology and innovation.

🏆Accolades and Recognition 

Throughout his illustrious career, Dr. Senthil has received numerous accolades. He was awarded the Best Researcher Award for the academic year 2023 by the Human Rights Association & ACT. His role as a journal reviewer for Springer, Elsevier, and Hindawi highlights his expertise and recognition in the academic community. Dr. Senthil has also been a session chair and technical program committee member for various conferences, further showcasing his leadership and influence in the field.

🌐Impact and Influence 

Dr. Senthil’s influence extends beyond academia through his active participation in professional societies such as ISTE, CSI, and SCRS. He has mentored numerous students and guided several research projects, fostering a culture of innovation and critical thinking. His contributions to curriculum development, including the publication of three books aligned with Anna University regulations, have significantly impacted engineering education.

🔮Legacy and Future Contributions 

As a dedicated educator and researcher, Dr. G.A. Senthil continues to shape the future of engineering and technology. His ongoing research and commitment to academic excellence ensure a lasting legacy in the field. Dr. Senthil’s future contributions are poised to inspire and guide the next generation of engineers and technologists, cementing his role as a pivotal figure in the advancement of computer science and engineering.

 

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Mrs. Sravani Nalluri | Computer Science and Engineering | Best Researcher Award

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Mrs. Sravani Nalluri | Computer Science and Engineering | Best Researcher Award🏆

Mrs. Sravani Nalluri, VIT Vellore, India 🎓

Professional Profile

🌟Sravani Nalluri: A Comprehensive Overview

🎓Early Academic Pursuits

Sravani Nalluri’s academic journey began with a Bachelor’s degree in Electronics and Communication Engineering from Idhaya Engineering College for Women, Anna University, in 2006. She continued her education with a Master’s degree in Computer Science and Engineering from St. Joseph’s College of Engineering, Anna University, Chennai, in 2008. Her quest for knowledge led her to the Vellore Institute of Technology, where she pursued a Ph.D. in Computer Science and Engineering, with her thesis submitted in April 2024. Alongside, she completed a Junior Data Analyst Program from Npower Canada in August 2023, further diversifying her skill set.

💼Professional Endeavors

Sravani’s career has been marked by a 13-year tenure as an Assistant Professor in the Department of Computer Science and Engineering at VNR VJIET, Hyderabad. During her tenure, she excelled in teaching programming languages such as C and Java, and developed a deep understanding of data structures, algorithms, and software development. She has also held roles as a QA Consultant and Training Process Member at Zemoso Technologies, Hyderabad, from May 2022 to August 2022. Her professional memberships include being a life member of The Indian Society for Technical Education (ISTE) and a member of the Computer Society of India, Hyderabad Chapter.

🔍Contributions and Research Focus

Sravani has made significant contributions to computer science education and research. She has developed and taught both undergraduate and graduate courses, guided numerous major and minor projects, and participated in curriculum development. Her expertise extends to machine learning, deep learning, and cloud concepts. She has actively contributed to various technical roles, including being a Hackathon Coordinator and Lab In Charge, and has played a pivotal role in the NAAC and NBA accreditation processes.

🏆Accolades and Recognition

Throughout her career, Sravani has been recognized for her dedication and contributions. Her certifications include Microsoft AZ-900, IBM Data Analyst Professional Certificate, and specialized courses in AI, Big Data Analytics, and Natural Language Processing. These certifications highlight her commitment to continuous learning and staying updated with industry advancements.

🌐Impact and Influence

Sravani’s influence extends beyond academia. Her role as a faculty mentor, involvement in hackathons, and contributions to innovative projects reflect her impact on student development and the academic community. Her commitment to improving educational practices and integrating technology into teaching has had a lasting effect on her students and colleagues.

🔮Legacy and Future Contributions

As she continues her journey, Sravani Nalluri remains dedicated to advancing the field of computer science through her research and teaching. Her future contributions are poised to shape the next generation of computer scientists and engineers. Her ongoing research and commitment to educational excellence ensure a lasting legacy in the field.

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