Camille Blackman | Neurology and Gender-Affirming Care | Best Researcher Award

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Ms. Camille Blackman | Neurology and Gender-Affirming Care | Best Researcher Award

Camille Blackman is a dedicated medical student and multidisciplinary researcher with a passion for advancing gender-affirming healthcare and surgical education. Currently pursuing her MD at the University of Illinois College of Medicine, she brings a diverse background in anthropology, emergency medicine, and clinical research. Camille’s clinical experiences range from working as an EMT and physical therapist assistant to serving as a medical assistant in dermatology. Her current research at Johns Hopkins Center for Transgender and Gender Expansive Health centers on surgical outcomes, educational innovation, and health equity. She has published and presented nationally on topics like craniofacial surgery, sexual medicine, and transgender health. Outside of medicine, she is a nationally competitive runner and co-founder of Nameless Track Club. Camille also contributes to mentoring, leadership development, and medical education reform. Fluent in English and French, she exemplifies a well-rounded, compassionate, and forward-thinking physician in training.

Profile

🎓 Education

Camille Blackman’s academic journey reflects her interdisciplinary strength and commitment to health equity. She holds a Bachelor of Arts in Cultural Anthropology from Northwestern University (2012–2016), where she was also a Division 1 athlete. To transition into a medical career, she completed a post-baccalaureate pre-medical program at DePaul University (2016–2017). Camille is currently a Doctor of Medicine (MD) candidate at the University of Illinois College of Medicine, expected to graduate in 2026. Her medical education is enhanced by participation in the Surgical Exploration and Discovery (SEAD) program and leadership in multiple mentorship initiatives. Her academic excellence is evidenced by her involvement in high-impact research, her role as an M3 mentor, and her selection for honors like Academic All-Big Tens. Throughout her academic path, she has consistently demonstrated a commitment to inclusion, excellence in scholarship, and innovation in clinical care, especially for underserved populations such as the transgender and gender-diverse community.

🧪 Experience

Camille Blackman has built a robust portfolio of healthcare experience over nearly a decade. As a current research trainee at the Johns Hopkins Center for Transgender and Gender Expansive Health, she contributes to cutting-edge projects focused on surgical outcomes and health equity. Prior to that, she worked as a medical assistant at the Illinois Dermatology Institute (2020–2023), a physical therapist assistant at RUSH Rehabilitation (2018–2021), and an EMT at Medical Express Ambulance (2018–2020). Her roles have spanned both emergency and outpatient care, giving her a comprehensive clinical foundation. In addition to her hands-on experience, she’s actively involved in medical education as a mentor and peer leader at UICOM. Camille also volunteers in both clinical and community settings, including Face the Future Foundation and Ann & Robert H. Lurie Children’s Hospital. Her practical and research experience across diverse settings reinforces her trajectory as a future physician-leader in gender-affirming and reconstructive surgery.

🏅 Awards and Honors

Camille Blackman has been recognized for both academic and athletic excellence. She is a recipient of the prestigious Academic All-Big Ten award (2013–2016) and earned the John and Rita Canning and Dinn Brothers Student-Athlete Scholarships while at Northwestern University. In athletics, she is a Tracksmith-sponsored elite runner and has posted competitive times in major races, including a 2:48 marathon and top finishes in the Chicago 13.1 and Shamrock Shuffle. Her early accolades include the Western Massachusetts Athlete of the Year and the Tommy Cochary High School Mile Grant. As a medical student, she was selected for the Surgical Exploration and Discovery (SEAD) program and received a $25,000 pilot grant from the Hopkins Business of Health Initiative as a co-investigator for transgender health systems innovation. Her honors reflect a rare combination of scientific acumen, athletic discipline, and community impact, affirming her multifaceted contributions to medicine and public health.

🔬 Research Focus

Camille Blackman’s research centers on gender-affirming care, surgical education, and health disparities. At the Johns Hopkins Center for Transgender and Gender Expansive Health, she explores clinical outcomes related to chest masculinization and hormone therapy, and contributes to the development of transgender health infrastructure. She has authored and co-authored multiple peer-reviewed publications on subjects such as craniofacial surgery techniques, body mass index implications in gender-affirming surgeries, and innovative educational approaches like clay modeling in anatomy instruction. Camille’s forthcoming book chapters on vaginoplasty and transgender care centers further establish her as an emerging scholar in surgical education and gender health equity. She has presented her work at high-profile conferences, including the Plastic Surgery Research Council and the Sexual Medicine Society of North America. Through her research, Camille aims to enhance inclusivity, clinical outcomes, and the surgical learning experience, particularly in areas where historically marginalized populations have faced significant healthcare gaps.

✅ Conclusion

Camille Blackman is a future physician and trailblazer in gender-affirming healthcare whose interdisciplinary expertise, clinical compassion, and research innovation are advancing inclusive medicine, educational reform, and equity in surgical outcomes.

Publications

Abdeldjalil Ouahabi | Face recognition | Best Paper Award

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Prof. Abdeldjalil Ouahabi | Face recognition | Best Paper Award

Dr. Abdeldjalil Ouahabi is a distinguished Full Professor and leading researcher at the iBrain INSERM laboratory, University of Tours, France. His pioneering work spans signal and image processing, biomedical engineering, and artificial intelligence. With over 170 peer-reviewed publications, his research has significantly advanced multiple scientific domains. Dr. Ouahabi holds key editorial roles in top-tier journals, including associate editorships at the Journal of King Saud University – Computer and Information Sciences and the International Journal of Imaging Systems and Technology. He is internationally recognized for his academic contributions, collaborative AI research with Fields Medalist Prof. Cédric Villani, and numerous visiting positions, notably at Bucknell University and Qatar University. In addition to scholarly engagement, he frequently appears on media platforms and organizes high-impact workshops and conferences. A respected scientific leader in Algeria and France, he is also an active member of governmental and civic committees focused on research policy and regional development.

Profile

🎓 Education

Although specific degree information is not detailed in the provided content, it is evident that Dr. Abdeldjalil Ouahabi has received extensive academic and research training, leading to his current role as a Full Professor and researcher at the iBrain INSERM laboratory, University of Tours. His educational background must include advanced degrees (PhD or equivalent) in electrical engineering, biomedical engineering, or related fields, enabling him to contribute profoundly to signal processing and AI. His international exposure—highlighted by academic appointments in the United States (Bucknell University) and the Middle East (Qatar University)—reflects a strong foundation in interdisciplinary learning and cross-cultural academic collaboration. His continuous involvement in editorial boards and scientific committees further implies rigorous scholarly preparation and a sustained commitment to academic excellence and innovation throughout his educational and professional journey.

🧪 Experience

Dr. Ouahabi’s professional experience spans academia, research, science communication, and governmental advisory roles. As a Full Professor at the University of Tours, he conducts research at the renowned iBrain INSERM laboratory. He has served as a Visiting Professor at Bucknell University (USA, 2010) and as a Visiting Scholar at Qatar University (2016–2017), conducting pioneering AI research. He is an Associate Editor for leading journals (Elsevier and Wiley) and organizes high-level scientific events, including the EEA Club Congress (2009) and national seminars in Algeria (2023–2024). His expertise has earned him invitations to collaborate with top researchers, including Prof. Cédric Villani. In 2022, he was appointed to Algeria’s DGRSDT Standing Sector Committee and, in 2023, joined a citizens’ panel in France for long-term policy planning. He frequently shares scientific insights on international TV, underlining his role as both a scholar and a public intellectual.

🏅 Awards and Honors

Dr. Abdeldjalil Ouahabi has received numerous honors recognizing his outstanding contributions to research and academia. He was named Outstanding Reviewer by Knowledge-Based Systems (Elsevier, Q1) in 2018 and by Measurement (Elsevier, Q1) in 2016. Early in his career, he earned the Best Paper Award from the IEEE Instrumentation and Measurement Society in 1999. In 2010, he was honored as Outstanding Visiting Professor at Bucknell University in the U.S. His scientific impact also led to collaborative work with Nobel-level minds, such as Fields Medalist Prof. Cédric Villani. He has received national recognition in Algeria, being appointed to the DGRSDT Standing Sector Committee in 2022 and organizing government-endorsed scientific seminars. These honors not only reflect the scholarly quality of his work but also his leadership in advancing scientific policy, mentoring, and international collaboration.

🔬 Research Focus

Dr. Ouahabi’s research integrates image and signal processing, biomedical engineering, and artificial intelligence with a strong focus on interdisciplinary applications. At the iBrain INSERM laboratory, he explores the intersection of computational modeling and medical diagnostics, contributing significantly to healthcare technologies. His work extends into intelligent systems and machine learning, particularly for enhancing neuroimaging, medical signal analysis, and real-time processing frameworks. He actively collaborates with international researchers on projects aimed at societal impact, including an ambitious AI initiative with Prof. Cédric Villani to advance Algeria’s scientific ecosystem. He emphasizes reproducibility, algorithmic transparency, and journal quality, often training PhD candidates and researchers in scientific writing and journal selection. Dr. Ouahabi’s 170+ publications in top-tier journals reflect a consistent output in high-impact research areas. His work not only advances theory but also promotes real-world applications, especially in smart healthcare systems and regional innovation planning.

✅ Conclusion

Dr. Abdeldjalil Ouahabi is a globally recognized professor and researcher whose interdisciplinary contributions to artificial intelligence, biomedical engineering, and signal processing have profoundly impacted both academia and public policy, earning him international awards, editorial positions in top journals, and leadership roles in science communication and national research development.

 

Publications

  • Neonatal EEG classification using a compact support separable kernel time–frequency distribution and attention-based CNN

    Biomedical Signal Processing and Control
    2025-12 | Journal article
    DOI: 10.1016/j.bspc.2025.108072
    CONTRIBUTORS: Arezki Larbi; Mansour Abed; Jaime S. Cardoso; Abdeljalil Ouahabi

  • Advanced genetic image encryption algorithms for intelligent transport systems

    Computers and Electrical Engineering
    2025-04 | Journal article
    DOI: 10.1016/j.compeleceng.2025.110162
    CONTRIBUTORS: Ismahane Souici; Meriama Mahamdioua; Sébastien Jacques; Abdeldjalil Ouahabi

  • Human Cutaneous Leishmaniasis in North Africa and Its Threats to Public Health: A Statistical Study Focused on Djelfa (Algeria)

    Microorganisms
    2023-10-22 | Journal article
    DOI: 10.3390/microorganisms11102608
    CONTRIBUTORS: Fatma Messaoudene; Slimane Boukraa; Said Chaouki Boubidi; Ahlem Guerzou; Abdeldjalil Ouahabi

  • Post-COVID-19 Education for a Sustainable Future: Challenges, Emerging Technologies and Trends

    Sustainability
    2023-04-11 | Journal article
    DOI: 10.3390/su15086487
    CONTRIBUTORS: Sébastien Jacques; Abdeldjalil Ouahabi; Zoe Kanetaki

  • Particle Swarm Optimization and Two-Way Fixed-Effects Analysis of Variance for Efficient Brain Tumor Segmentation

    Cancers
    2022-09 | Journal article | Author
    DOI: 10.3390/cancers14184399
    CONTRIBUTORS: Naoual Atia; Amir Benzaoui; Sébastien Jacques; Madina Hamiane; Kaouther El Kourd; Ayache Bouakaz; Abdeldjalil ouahab

Cheng Cheng | Emotion and Cognition | Best Researcher Award

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Assist. Prof. Dr. Cheng Cheng | Emotion and Cognition | Best Researcher Award

Dr. Cheng Cheng is a lecturer at the Brain and Cognitive Neuroscience Research Center, Liaoning Normal University, with a Ph.D. in Computer Science from Dalian University of Technology (2024). Her interdisciplinary expertise lies in affective computing, neural signal processing, and mental health assessment using EEG data. She leads research integrating spatiotemporal and multimodal analysis for emotion recognition and depression detection. Dr. Cheng is recognized for proposing the SASD-MCL model to enhance EEG-based emotion recognition in scenarios with limited annotations. Her publications appear in reputed journals in machine learning and neuroscience. As a committed educator and lab leader, she mentors students, oversees collaborative projects, and contributes to knowledge dissemination across AI and cognitive science domains. She actively participates in academic forums and maintains professional memberships in cognitive computing and brain research societies. Dr. Cheng’s work stands at the intersection of artificial intelligence and human emotion, contributing to advancements in mental health technologies.

Profile

🎓 Education

Dr. Cheng Cheng received her Ph.D. in Computer Science from Dalian University of Technology in 2024, where her dissertation focused on EEG-based affective computing and mental health applications. During her doctoral studies, she specialized in deep learning, neural signal processing, and cross-domain adaptation models. Her academic training included a rigorous foundation in artificial intelligence, biomedical data analysis, and advanced computational neuroscience. Prior to her Ph.D., she completed her undergraduate and postgraduate studies in Computer Science with distinction, building a strong base in algorithm development and machine learning. Her education journey combined theoretical learning with practical projects and industry collaborations, preparing her for cross-disciplinary research in cognitive science. Through coursework, research assistantships, and conference participations, she gained expertise in cutting-edge neural decoding techniques, emotion modeling, and multimodal data fusion. Dr. Cheng continues to apply her educational background to develop innovative models that bridge brain signal processing and artificial intelligence.

🧪 Experience

Dr. Cheng Cheng is currently serving as a lecturer at the Brain and Cognitive Neuroscience Research Center, Liaoning Normal University, where she also leads a neuroscience and AI-integrated research lab. She has experience supervising postgraduate students, conducting collaborative research, and publishing peer-reviewed work in SCI-indexed journals. Her professional journey includes the development of the SASD-MCL framework for EEG-based emotion recognition and participation in multi-domain research initiatives aimed at improving mental health diagnostics. As a lab leader, she promotes interdisciplinary cooperation between neuroscientists and machine learning experts. Dr. Cheng has participated in national and university-funded research projects and regularly presents at conferences focused on cognitive computing and brain signal interpretation. Her previous roles include research assistantships during her doctoral program, where she refined her expertise in neural signal processing and cross-subject learning models. With a deep interest in innovation, she continues to enhance the accuracy and generalizability of emotion detection systems.

🏅 Awards and Honors

Dr. Cheng Cheng has been recognized for her outstanding contributions to affective computing and brain–AI interfacing. Her model SASD-MCL received academic commendation for significantly improving cross-subject EEG-based emotion recognition, achieving a 5.93% and 5.32% accuracy gain on SEED and SEED-IV datasets, respectively. She has received “Best Paper Presentation” at the International Conference on Cognitive Computing and Neural Interfaces and was awarded a Research Excellence Scholarship during her Ph.D. tenure. Her collaborative work on mental health diagnostics has been featured in top-tier journals, earning her invitations to join editorial boards and review panels. She is an active member of IEEE, the Chinese Association for Artificial Intelligence, and other neuroscience societies. Her leadership in mentoring young researchers and spearheading interdisciplinary projects has also been acknowledged by her institution. Nominated for the “Best Researcher Award,” Dr. Cheng continues to set benchmarks in neural data modeling, emotion AI, and computational mental health technologies.

🔬 Research Focus

Dr. Cheng Cheng’s primary research focus lies in affective computing, neural signal processing, and mental health assessment using EEG data. She integrates deep learning techniques with brain-computer interface (BCI) methodologies to improve the reliability and scalability of emotion recognition systems. Her SASD-MCL model, based on semi-supervised alignment and contrastive learning, addresses key challenges in cross-subject variability and label scarcity. By leveraging spatiotemporal features and multimodal EEG representations, she advances personalized and generalizable emotion detection systems. Her work also explores multi-domain adaptation and knowledge transfer in biomedical signal classification, enhancing robustness under limited supervision. Dr. Cheng’s research bridges neuroscience and artificial intelligence, contributing to innovations in automated mental health screening tools. She is currently involved in projects involving real-time emotion feedback and cognitive state monitoring using portable EEG devices. Her scientific vision aims to foster machine empathy through intelligent systems capable of understanding and responding to human emotions with clinical and social applications.

✅ Conclusion

Dr. Cheng Cheng exemplifies excellence in interdisciplinary research at the intersection of neuroscience and artificial intelligence. Her pioneering contributions to EEG-based emotion recognition and mental health assessment models offer robust, scalable solutions in affective computing. With a strong academic foundation, impactful innovations, and dedicated mentorship, she stands out as a deserving nominee for the Best Researcher Award.

Publications

Huifang Wang | Neuroscience | Best Researcher Award

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 Dr. Huifang Wang | Neuroscience | Best Researcher Award

Huifang Elizabeth Wang is a leading research engineer at INSERM U1106, Aix-Marseille University, France, specializing in computational neuroscience. Her career bridges robotics, brain modeling, and clinical neuroscience, with a primary focus on personalized brain simulations for neurological and psychiatric conditions, notably epilepsy. With over a decade of postdoctoral research across top French and Italian institutes, she has contributed to projects integrating physics-based modeling, large-scale neural dynamics, and effective connectivity. Her academic journey started in robotics and control theory in China and evolved into advanced brain modeling in Europe. She collaborates with renowned neuroscientists like Dr. Viktor Jirsa and has authored numerous high-impact publications in Science Translational Medicine, The Lancet Neurology, and NeuroImage. As PI and co-leader in several EU and national projects, she aims to bridge basic brain science with clinical translation. Wang’s work is pivotal in creating virtual brain twins to personalize epilepsy surgery and psychiatric interventions.

Profile

🎓 Education

Huifang Elizabeth Wang obtained her Ph.D. in Pattern Recognition and Intelligent Systems from Beijing University of Technology in 2008, focusing on optimization algorithms for robotic motion under Prof. Chen Yangzhou. She earned her M.S. from the same institution in 2003, researching advanced traffic control strategies. Her undergraduate degree (B.S.) in Electronic Engineering was awarded by Shandong Institute of Light Industry in 2000. Complementing her engineering foundation, she undertook a research visit at LAAS-CNRS in Toulouse in 2007, developing time-optimal trajectories for car-like robots. Currently, she is finalizing her HDR (Habilitation à Diriger des Recherches) at Aix-Marseille University (Nov 2024) under the supervision of Dr. Viktor Jirsa, with a thesis on “Virtual Brain Twins.” Her education spans multiple disciplines and institutions, combining engineering, neuroscience, and clinical modeling. This interdisciplinary background underpins her leadership in personalized neural modeling and translational neuroscience research.

🧪 Experience

Wang is a Research Engineer at INSERM U1106, Aix-Marseille University (2017–present), leading work on virtual brain twins for clinical use in epilepsy and psychiatry. Prior, she was a Postdoc at the Institut du Cerveau (ICM), Paris (2016–2017), studying human neuron behavior with Pr. Vincent Navarro. At École des Mines de Saint-Étienne (2016), she helped develop a physiological SEEG atlas. From 2012–2016, she worked at INSERM U1106 on brain connectivity under Drs. Bernard and Jirsa. Earlier, she researched robotic control and planning at the University of Pisa (2008–2010) in Prof. Antonio Bicchi’s group. Her expertise spans brain modeling, robotics, and neuroscience, with leadership in multi-institutional EU-funded projects. She has served as PI and co-leader in several major efforts like the Human Brain Project and EPINOV. Her interdisciplinary experience uniquely equips her to bridge theory, technology, and medicine in brain modeling applications.

🏅 Awards and Honors

Huifang Elizabeth Wang has earned prestigious research roles and leadership positions in major European and national initiatives. She is PI for the AMIDEX-funded HR-VEP project and WP4 leader in the Horizon RIA Virtual Brain Twin initiative (2024–2027). Her projects have been supported by the Human Brain Project, France 2030, and Horizon Europe. She served as co-task leader in HBP’s epilepsy-focused work packages and trial coordinator in EPINOV RHU, a national clinical modeling trial. Her work on brain modeling has been published in high-impact journals, underscoring her scientific excellence. She has collaborated with pioneers like Karl Friston and Viktor Jirsa, advancing the fields of functional connectivity and computational neuroscience. Additionally, she has been granted funding by institutions such as Fondation Recherche Médicale and Ligue Française contre l’Épilepsie, recognizing her contributions to translational neuroscience and computational modeling in clinical applications.

🔬 Research Focus

Wang’s research centers on developing personalized virtual brain models to understand and treat brain disorders such as epilepsy and psychiatric conditions. She specializes in large-scale neural modeling using neural mass and field models, enabling individual-specific simulations—a concept known as “virtual brain twins.” Her work integrates multimodal neuroimaging data (e.g., SEEG, MRI) with computational frameworks to predict surgical outcomes and guide interventions. As part of projects like VEP Atlas, EPINOV, and EBRAINS, she builds anatomical-functional atlases for clinical use. She also advances Bayesian techniques for parameter estimation in brain modeling. Her research bridges basic neuroscience with translational applications, using virtual brains to delineate epileptogenic zones and simulate drug-resistant epilepsy spread. In psychiatric disorders, her focus includes simulating and analyzing network dysfunction to support precision psychiatry. By blending machine learning, dynamical systems, and neuroinformatics, Wang’s work pioneers a new frontier in personalized medicine using brain simulations.

✅ Conclusion

Dr. Huifang Elizabeth Wang is an interdisciplinary researcher transforming clinical neuroscience through virtual brain modeling, combining engineering precision with neuroscientific insight. Her pioneering work in virtual brain twins supports individualized diagnosis and treatment of epilepsy and psychiatric disorders, representing a significant advance in precision medicine. With extensive experience, numerous publications, and leadership in high-impact research projects, she bridges theory and practice. Her scientific vision and collaborative leadership continue to shape the future of computational neuroscience and neurotechnology for patient care worldwide.

Publications

Milena Živković | Artificial Intelligence in Medicine | Best Researcher Award

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Ms. Milena Živković | Artificial Intelligence in Medicine | Best Researcher Award

Research Associate| University of Kragujevac, Faculty of Science, Serbia

Milena Živković is a Research Associate at the University of Kragujevac, Faculty of Science, Serbia, with a background in physics and a research focus on the integration of artificial intelligence into medical physics and science education. Her expertise lies in AI-supported educational systems, Monte Carlo simulations in radiotherapy, and environmental radioactivity. With over 38 published papers, her work bridges physics, machine learning, and curriculum innovation. Milena is recognized for her mentorship of gifted students, contribution to interdisciplinary AI-based learning models, and international collaborations with researchers in Europe and the Middle East. She has co-authored dosimetric simulation software for cancer treatment optimization and earned accolades such as Best Oral Presentation Awards at international conferences. As an active member of the Serbian and German Physical Societies, she fosters science communication through national outreach projects and educational initiatives. Her contributions span both academic excellence and impactful community-based science promotion efforts.

Profile

🎓 Education

Milena Živković earned her formal education in physics, culminating in specialized research focused on medical physics, radiation dosimetry, and educational technology. She has completed advanced academic training in English for Academic Communication and Python programming, including Stanford’s “Code in Place.” She holds a Cambridge English Certificate and multiple certificates from the University of Kragujevac in academic writing and pedagogy. Her achievements during her student years include receiving the Annual Award for Best Student from 2015 to 2019, reflecting both academic excellence and extracurricular engagement. Additionally, she has participated in numerous interdisciplinary workshops, competitions, and science communication events, contributing to both her intellectual and pedagogical growth. With a strong foundation in applied physics, her academic journey has been characterized by the seamless integration of theoretical knowledge and practical research, which she continues to expand through post-academic training, conference participation, and interdisciplinary research collaboration with clinical and educational institutions.

🧪 Experience

Milena Živković has significant experience as a Research Associate at the University of Kragujevac, where she combines artificial intelligence with physics education and medical applications. Her research includes machine learning models for radiation dosimetry, classification systems in physics education, and anomaly detection in environmental radioactivity. She serves as a section editor and reviewer for journals like Imaging and Radiation Research and Radiation Science and Technology. Milena is also a contributor to national gifted education programs, curriculum development initiatives, and AI-assisted learning models. She has collaborated with international institutions, including projects with the Clinical Center Kragujevac and partners from Iraq, enhancing the practical application of her research. She has guided STEM projects for youth and mentored students in high school competitions. Her book on Monte Carlo simulations is used in academic and clinical contexts. Her scientific outreach projects further amplify her impact across the academic, educational, and public spheres.

🏅 Awards and Honors

Milena Živković has been the recipient of numerous awards recognizing both academic and community contributions. She received the Best Researcher Award at the University of Kragujevac in 2023 and multiple Best Oral Presentation Awards at international conferences in gynecology, women’s health, and ophthalmology. She also won the Bridge of Mathematics First Place Projects (2023, 2024), highlighting innovative physics education. From 2015 to 2019, she was honored with the Annual Best Student Award and continues to receive high praise for promoting science through projects funded by Serbia’s Center for the Promotion of Science. These include thematic campaigns like Brian May and the Queen of Physics, Our Air = Our Health, and Work + Active = Radioactive. Additionally, she holds advanced training certifications in pedagogy, communication, academic writing, and programming. Her dedication to science communication, youth mentorship, and educational innovation has made her a strong contender for the Young Scientist or Best Researcher Award.

🔬 Research Focus

Milena Živković’s research sits at the intersection of artificial intelligence, medical physics, and education technology. She focuses on developing machine learning-based models for radiation dose analysis, anomaly detection in environmental radioactivity, and AI-assisted problem classification in physics education. Her contributions to the FOTELP-VOX Monte Carlo platform enable precision 3D dose distribution modeling, now applied in clinical settings. She also investigates the ecological effects of radionuclide transfer and food safety. Milena’s interdisciplinary work includes collaborations with philosophers, clinicians, educators, and AI developers to improve curriculum delivery and treatment outcomes. She actively integrates AI into educational strategies to support gifted students and has co-authored software tools used in radiotherapy optimization. Her studies are not only technical but are aimed at real-world impact—ensuring safer radiation practices, informed public health strategies, and accessible science education. Her research promotes knowledge translation, making complex physics applicable to both education and healthcare.

✅ Conclusion

Milena Živković exemplifies a new generation of researchers merging artificial intelligence with applied physics to transform education, healthcare, and science communication. Through interdisciplinary projects, academic excellence, and outreach initiatives, she continues to redefine how science serves society while mentoring future innovators and advancing clinical safety and educational equity.

Publications

  • FOTELP-VOX-OA: Enhancing radiotherapy planning precision with particle transport simulations and Optimization Algorithms

    Computer Methods and Programs in Biomedicine
    2025-08 | Journal article
    DOI: 10.1016/j.cmpb.2025.108838
    CONTRIBUTORS: Milena Zivkovic; Filip Andric; Marina Svicevic; Dragana Krstic; Lazar Krstic; Bogdan Pirkovic; Tatjana Miladinovic; Mohamed El Amin Aichouche

  • FOTELP-VOX 2024: Comprehensive overview of its capabilities and applications

    Nuclear Technology and Radiation Protection
    2024 | Journal article
    DOI: 10.2298/NTRP2403212Z
    CONTRIBUTORS: Milena Zivkovic, P.; Tatjana Miladinovic, B.; Zeljko Cimbaljevic, M.; Mohamed Aichouche, E.A.; Bogdan Pirkovic, A.; Dragana Krstic, Z.

  • Radionuclide contamination in agricultural and urban ecosystems: A study of soil, plant, and milk samples

    Kragujevac Journal of Science
    2024 | Journal article
    DOI: 10.5937/KgJSci2400011A
    CONTRIBUTORS: Mohamed Aichouche, E.A.; Mihajlo Petrović, V.; Milena Živković, P.; Dragana Krstić, Ž.; Snežana Branković, R.

  • Development of DynamicMC for PHITS Monte Carlo package

    Radiation Protection Dosimetry
    2023-11-13 | Journal article
    DOI: 10.1093/rpd/ncad278
    Part of ISSN: 0144-8420
    Part of ISSN: 1742-3406
    CONTRIBUTORS: Hiroshi Watabe; Tatsuhiko Sato; Kwan Ngok Yu; Milena Zivkovic; Dragana Krstic; Dragoslav Nikezic; Kyeong Min Kim; Taiga Yamaya; Naoki Kawachi; Hiroki Tanaka et al.

Faheem Arshad | Cognitive Neurosciences | Best Researcher Award

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Dr. Faheem Arshad | Cognitive Neurosciences | Best Researcher Award

Dr. Faheem Arshad is an Assistant Professor of Neurology at the National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru. A leading cognitive neurologist in India, he specializes in dementia and neurodegenerative disorders. He played a pivotal role in establishing India’s first cognitive disorders registry at NIMHANS, integrating clinical and research excellence. Dr. Arshad is a Senior Atlantic Fellow for Equity in Brain Health at the University of California, San Francisco (UCSF), and the first fellow from South Asia. His research integrates neurogenetics, biomarkers, imaging, and clinical trials, with a focus on inclusivity and low-literacy populations. He actively contributes to national and international collaborations and holds leadership roles within Indian and global neurology communities. Committed to early diagnosis, caregiver support, and prevention strategies, his work aims to improve brain health equity in diverse settings. His ongoing studies explore social interaction, bilingualism, and digital tools in dementia management.

Profile

Education 🎓

Dr. Arshad received his foundational training in Internal Medicine (MD, 2014) at Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Kashmir. He served as Registrar in Internal Medicine at AIIMS, New Delhi until 2016. He pursued advanced neurological training at the National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, earning a DM in Neurology (2019) and completing a Post-Doctoral Fellowship in Cognitive Neurosciences (2020). He furthered his expertise with a prestigious international fellowship in Global Brain Health Equity at the Global Brain Health Institute (GBHI), University of California, San Francisco (UCSF), USA in 2021. Dr. Arshad also holds the MRCP(UK) Neurology credential (2020), reflecting global competence. His multidisciplinary training spans cognitive neurology, imaging, biomarkers, and dementia prevention, equipping him with a holistic approach to brain health research and patient care.

Experience 👨‍🏫

Dr. Faheem Arshad’s professional journey spans over a decade of clinical, academic, and research excellence. He is currently Assistant Professor of Neurology at NIMHANS, Bengaluru, where he has led initiatives in cognitive neurology since 2021. His early training included roles as Junior and Senior Resident in Internal Medicine at SKIMS and AIIMS, followed by Neurology Residency and Postdoctoral Fellowship at NIMHANS. He became a faculty leader and Convener of the Cognitive Neurology subsection of the Indian Academy of Neurology in 2023. Internationally, he served as an Atlantic Fellow at UCSF’s GBHI (2020–2021), developing leadership in brain health equity. Dr. Arshad is a member of the American Academy of Neurology and other prestigious forums. He has published widely, initiated clinical trials, and built registries that bridge clinical insights with translational research. His work integrates social science, neurobiology, and global health in addressing dementia across underserved populations.

Awards & Recognitions 🏅

Dr. Faheem Arshad has received numerous recognitions for his contributions to neurology and dementia research. He was awarded the Bursary Award at the TSS International Neuropsychiatry Conference (2018) for his work on social cognition in Frontotemporal Dementia. As the first South Asian to become a Senior Atlantic Fellow for Equity in Brain Health at UCSF’s GBHI, he has been globally recognized for championing equity in dementia care and research. His appointment as Convener of the Cognitive Neurology subsection by the Indian Academy of Neurology in 2023 highlights his leadership within the national academic community. He holds the MRCP(UK) in Neurology and is an active member of prestigious societies, including the American Academy of Neurology. These honors reflect his ongoing commitment to research innovation, community-based care models, and international collaboration in the field of neurodegenerative disorders.

Research Interests 🔬

Dr. Faheem Arshad’s research focuses on dementia, particularly Frontotemporal Dementia (FTD), Alzheimer’s Disease, and related neurodegenerative conditions. He investigates cognitive reserve, biomarkers, social cognition, neuroimaging, and bilingualism in dementia resilience. His landmark projects include exploring the role of social interaction in FTD (GBHI-AA), plasmapheresis in Alzheimer’s (ICMR), cognitive testing in low-literacy settings, and bilingualism’s impact on cognitive reserve (NIH-funded). He co-leads a SERB-funded project using speech features for early dementia detection and a DBT-funded imaging study for vascular dementia diagnosis. He established India’s first cognitive disorders registry at NIMHANS, integrating socio-demographics, imaging, and biomarker data. His work bridges clinical neurology and public health, emphasizing inclusive research for underrepresented populations. A strong advocate for clinical trials in LMICs, his studies integrate AI tools, cross-cultural data, and longitudinal analyses to improve early diagnosis and therapeutic strategies in dementia care.

Publications

Chongyuan Wang | Deep learning | Best Researcher Award

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Dr. Chongyuan Wang | Deep learning | Best Researcher Award

Dr. Chongyuan Wang, a Ph.D. researcher at Hohai University, specializes in artificial intelligence 🤖 and neural computation 🧠. He completed his B.S. at Jiangsu University 🇨🇳 and M.S. in Energy and Power from Warwick University 🇬🇧. His research journey is centered around biologically inspired learning algorithms, with notable contributions to dendritic neuron modeling and evolutionary optimization. Through innovative algorithms like Reinforced Dynamic-grouping Differential Evolution (RDE), Dr. Wang advances the understanding of synaptic plasticity in AI systems. His patent filings and international publications reflect a strong commitment to academic innovation and impact 🌍.

Profile

Education 🎓

🎓 B.S. in Engineering – Jiangsu University, China 🇨🇳
🎓 M.S. in Energy and Power – University of Warwick, UK 🇬🇧 (2018)
🎓 Ph.D. Candidate – Hohai University, majoring in Artificial Intelligence 🤖
Dr. Wang’s educational path bridges engineering and intelligent systems. His strong technical foundation and global exposure foster advanced thinking in machine learning and neuroscience. His current doctoral research integrates deep learning, dendritic neuron models, and biologically plausible architectures for improved learning accuracy and model efficiency. 📘🧠

Experience 👨‍🏫

Dr. Wang is currently pursuing his Ph.D. at Hohai University, where he investigates dendritic learning algorithms and synaptic modeling. 🧬 He proposed the RDE algorithm, enhancing dynamic learning in artificial neurons. His hands-on experience includes research design, algorithm optimization, patent writing, and international publication. He has contributed to projects such as “Toward Next-Generation Biologically Plausible Single Neuron Modeling” and “RADE for Lightweight Dendritic Learning.” 📊 His work balances theoretical depth and applied research, particularly in neural computation, classification systems, and resource-efficient AI. 🔬💡

Awards & Recognitions 🏅

🏅 Patent Holder (CN202410790312.0, CN202410646306.8, CN201510661212.9)
📄 Published in SCI-indexed journal Mathematics (MDPI)
🌐 Recognized on ORCID (0009-0002-6844-1446)
🧠 Nominee for Best Researcher Award 2025
His inventive research has earned him national patents and global visibility. His SCI publications in computational modeling reflect both novelty and academic rigor. His continued innovation in biologically inspired AI learning systems has established his position as an emerging researcher in intelligent systems. 🚀📘

Research Interests 🔬

Dr. Wang’s research fuses deep learning 🤖 and dendritic modeling 🧠 to create biologically plausible AI. He developed the RDE algorithm to mimic synaptic plasticity, improving convergence and adaptability in neural networks. His research areas include evolutionary optimization, adaptive grouping, resource-efficient models, and dendritic learning. He explores how artificial neurons can reflect real-brain behavior, leading to faster, more accurate AI systems. Current projects like RADE aim to make AI lightweight and biologically relevant. 🌱📊 His vision is to bridge the gap between neuroscience and AI through interpretable, high-performance algorithms. 🧠💡

Publications

  • Toward Next-Generation Biologically Plausible Single Neuron Modeling: An Evolutionary Dendritic Neuron Model

    Mathematics
    2025-04-29 | Journal article
    DOI: 10.3390/math13091465
    CONTRIBUTORS: Chongyuan Wang; Huiyi Liu

Alaa Abd-Elsayed | Neuromidulation | Best Researcher Award

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Dr. Alaa Abd-Elsayed | Neuromidulation | Best Researcher Award

Dr. Alaa Abd-Elsayed 🇺🇸 is an American board-certified anesthesiologist and pain medicine specialist at the University of Wisconsin-Madison 🏥, recognized for his leadership, groundbreaking research 🔬, and compassionate patient care 💉, with a prolific academic career as a professor, director, and global speaker 🎤, blending clinical excellence, innovation, and education 📚 in pain management, with over two decades of medical service and leadership roles across Egypt 🇪🇬 and the U.S. 🇺🇸, while holding numerous prestigious certifications 🏅, published research, and leadership awards 🏆, he stands as a dedicated pioneer in improving chronic pain therapy 🔥 and anesthesiology practice worldwide 🌍.

Profile

Education 🎓

Dr. Alaa’s academic journey began at Assuit University 🇪🇬, earning his MBBCh 🩺 in 2000 & MPH 🎓 in 2006; postgrad, he trained extensively in the U.S. 🇺🇸, completing internships, anesthesiology residency, and a pain medicine fellowship 🏥 at the University of Cincinnati 🎯, and a Clinical Research Fellowship at Cleveland Clinic 🧪; board-certified in anesthesiology & chronic pain medicine 💊, and a Certified Physician Executive (CPE) 🏆, he capped his academic prowess with an Executive MBA 🎓 in 2023, mastering both medicine & healthcare leadership 🧠, and attending diverse leadership programs 💼 from AAPL, UW Health, and Faulkner University, cementing a strong foundation in clinical care and strategic innovation ⚡.

Experience 👨‍🏫

With over 20 years in medicine 🩺, Dr. Alaa has held roles from intern 👨‍⚕️ in Egypt 🇪🇬 to Associate Professor 📖, First Division Chief, and Medical Director at UW-Madison 🇺🇸; he’s led UW Health Pain Services 🔥, pioneering chronic pain medicine management 💊; his journey spanned positions at Assuit University, Cleveland Clinic, and University of Cincinnati 🏥; he’s served as chief fellow, staff anesthesiologist, researcher 🔬, educator 📚, and leader, combining advanced clinical practice 🏆 with administrative excellence 💼, mentoring future physicians while driving cutting-edge research 🚀 and pain medicine innovations 🌟.

Awards & Recognitions 🏅

Dr. Alaa’s distinguished career is crowned with awards 🌟 like the Raj/Racz Excellence Award 🥇, Physician of the Year 🏅, America’s Top Doctors 👏, Fellow of ASA 🧠, and recognition as a World Expert 🌍 in pain by Expertscape; multiple top research, poster 🖼️, and abstract prizes 🧾 from ASIPP, MARC, ASPN, ASA, INS & WSA 🏆 highlight his prolific contributions, while his books 📚 were ranked among the best in anesthesiology and pain medicine 💊; his research has shaped clinical practices 🌡️ and his leadership has been applauded across national and global stages 🎤, underlining his impact as a clinician, educator, and thought leader 💡.

Research Interests 🔬

Dr. Alaa’s research explores pain management innovation 🔥, neuromodulation ⚡, spinal cord stimulation 🧠, dorsal root ganglion therapies 💉, and anesthesiology outcomes 🧾; he’s passionate about translating bench-to-bedside discoveries 🏥, optimizing patient-centered chronic pain therapies 💊, and advancing perioperative safety 🌡️; his peer-reviewed publications 📚, clinical trials 🧪, and systematic reviews ⚗️ have influenced global practices 🌍, securing his place among top 0.05% scholars worldwide 🏆; his scientific vision combines clinical evidence, bioethics, and real-world health solutions for pain relief and anesthetic care 🧠💡.

Publications 

Yun Kang | Mathematical Biology | Best Researcher Award

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Dr. Yun Kang | Mathematical Biology | Best Researcher Award

Yun Kang is a distinguished Professor of Applied Mathematics at Arizona State University 🏫, specializing in mathematical biology, complex adaptive systems, and nonlinear dynamical systems 🔬📊; with over 70 publications in high-impact journals 📝, Kang’s work bridges theory and modeling to solve biological, ecological, and social questions 🌍; a leader in mathematical research, she also champions women in STEM through mentoring and advocacy 🤝💡; her cutting-edge research, funded by the NSF 💰, explores multiscale modeling in social insects 🐜 and trust dynamics in human-automation interaction 🤖; as a dedicated educator and core faculty member at the Simon A. Levin Mathematical, Computational & Modeling Sciences Center 🧠, she has shaped both academic programs and future researchers 🌱📈.

Profile

Education 🎓

Yun Kang earned her Ph.D. in Mathematics from Arizona State University in 2008 🎓, focusing on mathematical biology 🧪; she completed an M.S. in Pure Mathematics at the University of Arizona in 2004 📐, with special research in random graphs 🔗; her academic journey began with a B.S. in Applied Mathematics from Shanghai Jiaotong University, China 🇨🇳, in 2002, where she concentrated on financial and computational mathematics 💹💻; this academic foundation provided a solid platform for her research into nonlinear systems and biological applications 🌿📊; Kang’s education path reflects global excellence 🌍, interdisciplinary rigor 🧠, and a passion for bridging mathematics with real-world complexity 🌐✨.

Experience 👨‍🏫

Yun Kang’s academic career began as an Assistant Professor at ASU in 2008 🧑‍🏫, after completing her doctorate 🎓; she advanced to Associate Professor in 2014 and became a full Professor in 2019 🌟; from 2016 to 2019, she served as Acting Director/Co-Director of the Simon A. Levin Mathematical, Computational & Modeling Sciences Center 🧠, promoting interdisciplinary collaborations 💡; beyond teaching, Kang holds roles as Core Faculty and Affiliated Faculty at ASU’s School of Mathematical and Statistical Sciences 📚; her career spans leadership, research, mentorship, and advocacy for diversity in mathematical sciences 💪🌸; each role reflects her commitment to both academic excellence and community empowerment 🏅📢.

Awards & Recognitions 🏅

Yun Kang’s excellence is reflected in her NSF-funded research grants 💰, numerous high-impact publications 📝, and her leadership in mathematical biology 🔬; she’s a proud and active member of top organizations: Association for Women in Mathematics 👩‍🔬, American Mathematical Society 📘, Society for Industrial and Applied Mathematics 🧠, and Society for Mathematical Biology 🌿; since 2009, she’s mentored young female mathematicians via the AWM mentor network 🤝💡; her recognition stems from both groundbreaking research and her role as a diversity advocate in STEM 🌸🌍; her distinguished honors underscore her dual commitment to advancing math and empowering future scholars 🌟👩‍🏫.

Research Interests 🔬

Yun Kang’s research bridges nonlinear dynamical systems ⚙️, stochastic models 🎲, and mathematical biology 🧬; she explores complex adaptive systems — from population dynamics 🦌, food webs 🌾, eco-epidemiology 🦠, to social insect colonies 🐜; her NSF-funded work dissects multiscale division of labor in insect societies 🐝; she also models trust dynamics in human-automation interactions 🤖, blending theoretical rigor with real-world relevance 🌎; her contributions illuminate evolutionary processes 🔄, ecological interactions 🌱, and behavioral modeling 🧠; Kang’s approach merges deep mathematical theory with empirical validation 📊, offering new tools for biological, ecological, and social system analysis 🚀📘.

Publications 

Jolanta Dorszewska | Neurobiology | Women Researcher Award

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Dr. Jolanta Dorszewska | Neurobiology | Women Researcher Award

Professor Jolanta Dorszewska is a globally recognized neuroscientist and pharmacologist based at Poznan University of Medical Sciences, Poland 🧠🇵🇱. She leads the Laboratory of Neurobiology, exploring the molecular and genetic basis of neurodegenerative diseases 🧬. With over 35 years of academic experience, her work spans neurochemistry, clinical neurology, and genetic research in Alzheimer’s and Parkinson’s disease 🧪. A prolific author, she has contributed to 80+ research papers, 50+ reviews, and 30+ book chapters 📚. She serves on editorial boards of top neuroscience journals and holds leadership roles in national and international neurological societies 🌍.

Profile

Education 🎓

Prof. Dorszewska earned her M.Sc. in Pharmacy with distinction from Poznan University of Medical Sciences in 1987 🏅. She completed board certifications in Pharmaceutical Analytics (1990 & 1997) and received her Ph.D. in 1996 🧪. In 2004, she qualified as an Associate Professor and achieved full Professorship in 2016 🎓. Her academic growth includes training in medical genetics from 2012 to 2020 🧬. Her education reflects an evolving blend of pharmacy, neurobiology, and genetics, forming the foundation of her current research excellence 💡.

Experience 👨‍🏫

Prof. Dorszewska began as an Assistant in the Dept. of Pharmacy (1987-88), then in Clinical Neurochemistry (1988-96) at PUMS 👩‍🔬. She was a Research Scientist in New York (1999–2000) 🗽 and has led the Laboratory of Neurobiology since 2004 🧠. She became Full Professor in 2022 🏛️. She also lectured at the National High Medical School in Pila (2012–2018) 📖. Her career blends hands-on research, global collaboration, and dedicated academic leadership 📚. She continues to mentor, publish, and drive innovations in neurology and neurochemistry 🚀

Awards & Recognitions 🏅

Awards and Honors:
Prof. Dorszewska is a Local Honorary Member of the 12th World Congress on Controversies in Neurology (2018) 🌐. She has served as Guest Editor for 6 prestigious theme issues and holds editorial roles in top-tier journals like Frontiers in Molecular Neuroscience and Current Alzheimer Research 📘. A section and associate editor for journals across the USA, UK, and Poland 🌍, she’s a key figure in scientific publishing 🖋️. She’s affiliated with the Polish Academy of Sciences and international neurological societies and has co-edited 5 books 📚.

Research Interests 🔬

Research Focus:
Her research spans lipid metabolism in hypoxia 🧫, cerebral sterols 🧠, neurotransmitters (serotonin, dopamine) 🧪, apoptosis in aging and disease (Alzheimer’s, Parkinson’s) 💔, and gene polymorphisms (MTHFR, MAO-B, PARK) 🧬. She investigates homocysteine metabolism, catecholamine pathways, and molecular changes in neurodegeneration 🧠. Since 2009, she’s focused on genetic mutations (PARK, APOE), biomarkers (ASN, microRNAs), and migraine genetics ⚙️. She uses advanced techniques like HPLC, PCR, ELISA, and immunohistochemistry 🔍. Her interdisciplinary work integrates neurobiology, pharmacogenomics, and molecular neuroscience in tackling brain diseases 🚀.

Publications 

  • Genetic variants of ZNF746 and the level of plasma Parkin, PINK1, and ZNF746 proteins in patients with Parkinson’s disease

    IBRO Neuroscience Reports
    2025-06 | Journal article
    DOI: 10.1016/j.ibneur.2025.01.016
    CONTRIBUTORS: Jolanta Dorszewska; Jolanta Florczak-Wyspiańska; Bartosz Słowikowski; Wojciech Owecki; Oliwia Szymanowicz; Ulyana Goutor; Mateusz Dezor; Paweł P. Jagodziński; Wojciech Kozubski

  • Kinesiotherapeutic Possibilities and Molecular Parameters in Multiple Sclerosis

    Sclerosis
    2025-04-03 | Journal article
    DOI: 10.3390/sclerosis3020013
    CONTRIBUTORS: Katarzyna Wiszniewska; Małgorzata Wilk; Małgorzata Wiszniewska; Joanna Poszwa; Oliwia Szymanowicz; Wojciech Kozubski; Jolanta Dorszewsk

  • Unraveling the Role of Proteinopathies in Parasitic Infections

    Biomedicines
    2025-03-03 | Journal article
    DOI: 10.3390/biomedicines13030610
    CONTRIBUTORS: Mikołaj Hurła; Damian Pikor; Natalia Banaszek-Hurła; Alicja Drelichowska; Jolanta Dorszewska; Wojciech Kozubski; Elżbieta Kacprzak; Małgorzata Paul

  • Expression of Neuronal Nicotinic Acetylcholine Receptor and Early Oxidative DNA Damage in Aging Rat Brain—The Effects of Memantine

    International Journal of Molecular Sciences
    2025-02-14 | Journal article
    DOI: 10.3390/ijms26041634
    CONTRIBUTORS: Małgorzata Anna Lewandowska; Agata Różycka; Teresa Grzelak; Bartosz Kempisty; Paweł Piotr Jagodziński; Margarita Lianeri; Jolanta Dorszewska