Giulia Iaconi | AI in Healthcare | Best Researcher Award

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Dr. Giulia Iaconi | AI in Healthcare | Best Researcher Award

PhD Student at University of Genoa, Italy

Giulia Iaconi is a passionate and driven PhD student at the Università degli Studi di Genova, where she is pursuing her doctoral studies in Science and Technology for Electronics and Telecommunications Engineering, with a specialization in Electromagnetism, Electronics, and Telecommunications. Her academic foundation in biomedical and neuroengineering provides her with a unique interdisciplinary approach to address complex challenges in biomedical signal processing and computational neuroscience. Her journey reflects a dedicated pursuit of innovation, especially at the intersection of engineering, healthcare, and data science, where she leverages computational tools and machine learning to advance diagnostic and rehabilitation methods. Giulia’s commitment to applying technology to improve human health has guided her academic and research efforts, culminating in multiple scholarly contributions and participation in prominent interdisciplinary projects aimed at advancing digital health solutions.

Profile

Orcid

Education

Giulia began her academic career at the Alma Mater Studiorum of Bologna, where she obtained her bachelor’s degree in Biomedical Engineering. Her undergraduate thesis focused on exploring bradykinesia in Parkinson’s disease patients through neural models, highlighting her early interest in neuroscience and computational approaches. She later pursued a master’s degree in Neuroengineering from the University of Genoa, where her thesis delved into developing a computational model of the cortico-hippocampal circuit to characterize in vitro experimental dynamics. These educational experiences equipped her with a strong foundation in signal processing, systems modeling, and neurobiological applications. Currently, she is in the final phase of her PhD, during which she continues to deepen her expertise in electronic and telecommunication engineering within biomedical contexts, contributing meaningfully to both academic research and applied innovations.

Experience

Giulia’s research experience spans various domains of biomedical engineering, with a particular focus on digital image processing, data analysis, and machine learning as supportive tools in diagnosis, classification, and rehabilitation. As part of the STORMS (Solution Towards Occupational Rehabilitation for Multiple Sclerosis) project, she worked as an engineer responsible for the design and development of serious games aimed at cognitive assessment and rehabilitation of multiple sclerosis patients. Her interdisciplinary collaborations have enabled her to integrate technological solutions with clinical practices, offering digital innovations to healthcare. Through her involvement in this and other initiatives, she has demonstrated proficiency in implementing supervised learning models, analyzing clinical datasets, and creating user-friendly rehabilitation platforms.

Research Interest

Giulia’s research interests lie at the convergence of computational neuroscience, biomedical signal processing, and intelligent healthcare systems. She is particularly invested in the development of machine learning algorithms and digital tools that enhance early diagnosis and personalized rehabilitation. Her work often involves constructing computational models that replicate brain circuitry behavior or employing image and signal processing to extract meaningful clinical insights. She is passionate about building systems that are not only technically robust but also accessible and impactful in clinical settings. Her recent work has emphasized the integration of these techniques into remote healthcare applications, such as telerehabilitation systems that assist in motor recovery monitoring for neurological patients.

Award

Giulia Iaconi is a strong candidate for the Best Researcher Award due to her continued excellence in research, particularly in biomedical engineering applications that merge computational tools with real-world clinical impact. Her contributions to digital health through machine learning and image processing have advanced diagnostic accuracy and patient rehabilitation techniques. Her interdisciplinary work, both in academia and in applied research projects like STORMS, has set a high benchmark in innovation-led healthcare engineering. Her scholarly achievements, active engagement in engineering communities such as IEEE, and ability to collaborate across disciplines collectively demonstrate her outstanding merit in research and development.

Publication

Giulia has published several impactful research articles that showcase her expertise and innovative contributions. Some of her notable publications include:

“Supervised learning algorithms for liver fibrosis classification using ultrasound images,” published in Electronics, 2023 – cited by 6 articles.

“Analysis of event-related potentials in multiple sclerosis rehabilitation: A case study,” in Biomedical Signal Processing and Control, 2022 – cited by 9 articles.

“Computational modeling of the cortico-hippocampal circuit for neurodynamics interpretation,” in Frontiers in Computational Neuroscience, 2023 – cited by 4 articles.

“Digital biomarkers in telehealth systems for cognitive assessment,” published in Sensors, 2022 – cited by 5 articles.

“Development of serious games for neurological rehabilitation,” in Journal of Medical Systems, 2021 – cited by 7 articles.

“Feature extraction from EEG signals for attention deficit assessment,” in IEEE Access, 2023 – cited by 3 articles.

“Artificial intelligence in biomedical imaging: A review on liver disease diagnostics,” in Diagnostics, 2022 – cited by 6 articles.

Conclusion

In conclusion, Giulia Iaconi exemplifies a new generation of researchers who are reshaping biomedical engineering through the application of cutting-edge technologies. Her deep academic grounding, coupled with her research innovation in neuroengineering and digital health, makes her a promising contributor to the future of intelligent healthcare systems. Her collaborative efforts, scholarly publications, and real-world project involvement reflect her commitment to enhancing patient outcomes using data-driven solutions. Through her doctoral studies and beyond, Giulia continues to push the boundaries of what technology can achieve in medical science, making her an ideal nominee for the Best Researcher Award.

Yuriy Gusev | AI in Healthcare | Best Use of Data in Healthcare Award

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Assoc. Prof. Dr. Yuriy Gusev | AI in Healthcare | Best Use of Data in Healthcare Award

Director of Health Informatics and Data Science Program at Georgetown University, United States

Yuriy Gusev is an esteemed Associate Professor of Bioinformatics at Georgetown University Medical Center’s Innovation Center for Biomedical Informatics (ICBI) and Department of Oncology. He is recognized for his extensive expertise in computational biology, bioinformatics, and systems biology, with a particular focus on cancer research. Dr. Gusev has dedicated his career to bioinformatics, computational modeling, and the development of innovative bioinformatics tools and methodologies. He also plays a leading role in the Health Informatics and Data Science graduate program, and co-directs the Biostatistics and Bioinformatics Shared Resource at the Lombardi Cancer Center. Throughout his career, Dr. Gusev has contributed significantly to multi-institutional cancer research efforts, particularly through large-scale studies, including the Georgetown Database of Cancer (G-DOC), and various NIH-funded programs.

Profile

Scopus

Education

Dr. Gusev’s academic journey began with a Master of Science in Applied Mathematics from State University of St. Petersburg in Russia. He later earned his Ph.D. in Computational Biology from the Central Research Institute of Roentgenology & Radiology in St. Petersburg, Russia. Dr. Gusev further honed his expertise with a postdoctoral position at the Waksman Institute, Rutgers University, where he focused on Computational Modeling in Cancer Research. These experiences laid the foundation for his innovative approach to bioinformatics and cancer research.

Experience

Dr. Gusev’s professional journey spans over three decades, with pivotal positions at several renowned institutions. After his postdoctoral work at Rutgers, he held various roles, including faculty research associate at Johns Hopkins University, senior research scientist at Molecular Staging Inc., and assistant professor at the University of Oklahoma Health Sciences Center. In 2009, he joined Georgetown University as an Associate Professor. Alongside his academic appointments, Dr. Gusev has directed numerous research projects and collaborated extensively in multi-disciplinary research programs across cancer genomics, bioinformatics, and computational biology.

Research Interests

Dr. Gusev’s research interests lie at the intersection of computational biology, bioinformatics, and cancer research. His primary focus includes the study of tumor heterogeneity, chromosomal instability, microRNA, and long-noncoding RNA regulation in cancer. He is particularly invested in the application of computational models and bioinformatics methods to analyze large-scale genomic and transcriptomic data. Dr. Gusev is also passionate about integrating molecular, imaging, and clinical data to advance personalized medicine and precision oncology. His work involves high-throughput data analysis, machine learning techniques for biomarker discovery, and the development of cloud-based platforms to streamline cancer research workflows.

Awards

Dr. Gusev has been recognized with numerous accolades throughout his career. Notable awards include the Charles and Johanna Bush Postdoctoral Fellowship, NSF travel awards for his work in tumor heterogeneity and mathematical population dynamics, and the Executive Leadership Award from the Mid-South Computational Biology and Bioinformatics Society. His contributions to computational cancer research were further acknowledged with the 2008 Executive Leadership Award, and his research impact continues to be recognized by various scientific bodies.

Publications

Dr. Gusev has authored or co-authored numerous influential publications. His research in tumor heterogeneity, chromosomal instability, and microRNA profiling has resulted in multiple highly cited papers. Some key publications include:

Axelrod DE, Gusev Y, Kuczek T. “Persistence of cell cycle times over many generations as determined by heritability of colony sizes of ras oncogene-transformed and non-transformed cells.” Cell Proliferation, 1993, 26(3), 235-249.

Gusev Y, Kagansky V, Dooley WC. “Long-term dynamics of chromosomal instability in cancer: a transition probability model.” Mathematical and Computer Modelling, 2001, 33(12), 1253-1273.

Gusev Y, Bhuvaneshwar K, Song L, Zenklusen JC, Fine H, Madhavan S. “The REMBRANDT study, a large collection of genomic data from brain cancer patients.” Nature Scientific Data, 2018; 5:180158.

Bhuvaneshwar K, Belouali A, Singh V, et al. “G-DOC Plus – an integrative bioinformatics platform for precision medicine.” BMC Bioinformatics, 2016; 17(1):193.

Lei Song, Krithika Bhuvaneshwar, Yue Wang, et al. “CINdex: a bioconductor package for analysis of chromosome instability in DNA copy number data.” Cancer Informatics, 2017, Volume 16, PMID: 29343938.

His works have been cited extensively, contributing to advances in cancer bioinformatics, precision oncology, and the study of molecular biomarkers in cancer.

Conclusion

Dr. Yuriy Gusev has made significant contributions to the field of computational biology and bioinformatics, particularly in cancer research. His work has greatly advanced the understanding of tumor heterogeneity, chromosomal instability, and non-coding RNA regulation in cancer. As an educator, researcher, and leader, he continues to influence the development of bioinformatics tools and platforms that facilitate precision medicine. Dr. Gusev’s expertise in computational modeling, genomic data analysis, and multi-omics integration positions him as a pivotal figure in cancer research and bioinformatics. His ongoing efforts to apply innovative computational approaches to clinical oncology will undoubtedly lead to further breakthroughs in cancer treatment and personalized therapies.

Hossein Nikzad | AI in Healthcare | Best Researcher Award

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Prof. Hossein Nikzad | AI in Healthcare | Best Researcher Award

Kashan University of Medical Sciences, Iran

Hossein Nikzad is a distinguished academic and researcher affiliated with the Kashan University of Medical Sciences in Kashan, Iran. He is a key figure in the Anatomical Science Research Center at the university, contributing significantly to research in areas such as male infertility, pharmacology, oxidative stress, and reproductive biology. His scientific work is marked by his expertise in understanding complex biological mechanisms and exploring potential therapeutic approaches to treat infertility and related disorders.

Profile

Google Scholar

Education

Dr. Hossein Nikzad earned his academic qualifications from reputable institutions, building a solid foundation in the fields of anatomy and reproductive health. Over the years, his educational journey has been intertwined with his commitment to advancing scientific research in reproductive medicine, with a specific focus on male infertility and related pathologies.

Experience

Dr. Nikzad’s professional experience spans multiple research and teaching roles, where he has been a key contributor to both academic and scientific communities. His work at Kashan University of Medical Sciences is complemented by collaborations with national and international researchers. His research focuses on reproductive medicine, particularly the effects of oxidative stress on male infertility, therapeutic interventions, and the molecular biology of various reproductive conditions. His experience extends into various research domains, including the use of herbal medicine in infertility treatment and the exploration of novel biological markers.

Research Interests

Dr. Nikzad’s primary research interests lie in the areas of oxidative stress, male infertility, and the molecular underpinnings of reproductive health. He is also interested in the therapeutic potential of antioxidants and other herbal remedies in treating infertility. His studies have delved into various related fields, such as the interaction between long noncoding RNAs and gynecological cancers, the effects of diet on reproductive health, and the development of therapeutic strategies to combat viral infections like COVID-19.

Awards

Dr. Nikzad has earned recognition for his outstanding contributions to the field of anatomical sciences and reproductive medicine. His work has been cited widely in numerous scientific journals, reflecting his influence and leadership in these research areas. While specific awards or nominations are not detailed, his research impact, including over 3000 citations, speaks to his global recognition as a leader in his field.

Publications

Barati E, Nikzad H, Karimian M. “Oxidative stress and male infertility: current knowledge of pathophysiology and role of antioxidant therapy in disease management,” Cellular and Molecular Life Sciences, 77, 93-113, 2020.

Hosseini ES, Kashani NR, Nikzad H, Azadbakht J, Bafrani HH, et al. “The novel coronavirus Disease-2019 (COVID-19): Mechanism of action, detection and recent therapeutic strategies,” Virology, 551, 1-9, 2020.

Hosseini ES, Meryet-Figuiere M, Sabzalipoor H, Kashani HH, Nikzad H, et al. “Dysregulated expression of long noncoding RNAs in gynecologic cancers,” Molecular Cancer, 16, 1-13, 2017.

Kabir-Salmani M, Nikzad H, Shiokawa S, Akimoto Y, Iwashita M. “Secretory role for human uterodomes (pinopods): secretion of LIF,” Molecular Human Reproduction, 11(8), 553-559, 2005.

Mohammadi F, Nikzad H, Taherian A, Amini Mahabadi J, Salehi M. “Effects of herbal medicine on male infertility,” Anatomical Sciences Journal, 10(4), 3-16, 2017.

Aghaei S, Nikzad H, Taghizadeh M, Tameh AA, Taherian A, Moravveji A. “Protective effect of Pumpkin seed extract on sperm characteristics, biochemical parameters, and epididymal histology in adult male rats treated with Cyclophosphamide,” Andrologia, 46(8), 927-935, 2014.

Mobasseri N, Babaei F, Karimian M, Nikzad H. “Androgen receptor (AR)-CAG trinucleotide repeat length and idiopathic male infertility: A case-control trial and a meta-analysis,” EXCLI Journal, 17, 1167-1174, 2018.

Conclusion

Dr. Hossein Nikzad is a renowned researcher whose work has profoundly impacted the fields of reproductive biology, male infertility, and related therapeutic interventions. His extensive publications and research collaborations highlight his commitment to advancing scientific understanding of infertility and related disorders. Through his research, he continues to contribute valuable insights into improving the quality of life for individuals facing reproductive health challenges.