Apoorva Safai | Neuroscience | Best Researcher Award

Published on by Global Academic Awards

Dr. Apoorva Safai | Neuroscience | Best Researcher Award 

Postdoctoral Research Associate, at University of Wisconsin-Madison, United States.

Dr. Apoorva Safai is a distinguished researcher specializing in neuroimaging, with a focus on deep learning applications in medical imaging and multimodal MRI analysis. She is currently a Postdoctoral Research Associate at the Integrating Diagnostics and Analytics (IDiA) Lab at the University of Wisconsin–Madison. Throughout her career, Dr. Safai has contributed significantly to understanding neurological disorders, particularly Parkinson’s disease and Alzheimer’s disease. Her research integrates advanced imaging techniques with machine learning to uncover intricate patterns in brain connectivity and structure. Dr. Safai’s work has been recognized through various awards and grants, underscoring her commitment to advancing medical imaging and neurodegenerative disease research. ​Idia Labs

Professional Profile

Scopus

ORCID

Google scholar

Education 🎓

Dr. Safai’s academic journey began with a Bachelor of Engineering in Electronics Engineering from P.V.P.I.T College, University of Pune, where she graduated with 65.4% marks in 2012. She pursued a Master of Technology in Biomedical Engineering at VIT University, Vellore, achieving a CGPA of 8.49 in 2015. Her passion for research led her to earn a PhD in Engineering from Symbiosis International University, Pune, between 2018 and 2023. Her doctoral research focused on developing a multimodal brain connectomic framework employing graph attention networks on structural and functional brain data, aiming to enhance the prediction and understanding of neurological disorders. ​Idia Labs

Experience 🧠

Dr. Safai’s professional experience is rich and diverse. Since April 2023, she has been serving as a Postdoctoral Research Associate at the IDiA Lab, University of Wisconsin–Madison, focusing on deep learning applications in optical coherence tomography and neuroimaging. Prior to this, she was a Senior Research Fellow and PhD Scholar at the Symbiosis Centre for Medical Image Analysis, Pune, from September 2021 to May 2022, where she worked on multimodal MRI analysis and deep learning models for neurological disorders. She also held the position of Technical Assistant in Imaging at the Department of Neuroimaging, NIMHANS, Bangalore, from May 2017 to August 2018, contributing to the Indo-UK project cVEDA, focusing on fMRI data acquisition and analysis. ​Idia Labs+1Google Scholar+1

Research Interests 🔬

Dr. Safai’s research interests lie at the intersection of neuroimaging and artificial intelligence. She specializes in multimodal MRI analysis, aiming to integrate various imaging modalities to provide a comprehensive understanding of brain structure and function. Her work in deep learning in medical imaging seeks to develop algorithms that can assist in the early detection and monitoring of neurological disorders such as Parkinson’s and Alzheimer’s diseases. By leveraging advanced computational techniques, Dr. Safai aims to uncover biomarkers and patterns that can lead to better diagnosis and treatment strategies for these conditions. ​

Awards 🏆

Dr. Safai’s contributions to neuroimaging and medical imaging have been recognized through several prestigious awards. She received the Alzheimer’s Association Research Fellowship to Promote Diversity (AARF-D) grant for 2025–2027, supporting her project titled “Multimodal AI-based Predictor of Alzheimer’s Disease (MAP-AD).” In 2020, she was awarded the ISMRM student research exchange grant for her proposal on high temporal resolution fMRI acquisition and advanced analysis for identifying reliable imaging markers for Parkinson’s disease. Additionally, she received a travel grant from the Movement Disorder Society for the MDS Conference in 2019 and an educational stipend from ISMRM for the same year’s conference, highlighting her active engagement and recognition in the scientific community. ​

Top Noted Publications 📚

  • Microstructural abnormalities of substantia nigra in Parkinson’s disease: A neuromelanin sensitive MRI atlas-based study

    • Year: 2020

    • Journal: Human Brain Mapping

    • Citations: 35 (PubMed)

    • Summary: This study investigates microstructural changes in the substantia nigra of Parkinson’s disease patients using neuromelanin-sensitive MRI, providing an atlas-based approach for assessing disease-related abnormalities.

  • Multimodal brain connectomics-based prediction of Parkinson’s disease using graph attention networks

    • Year: 2022

    • Journal: Frontiers in Neuroscience

    • Citations: 16 (Google Scholar)

    • Summary: The research utilizes graph attention networks (GATs) to analyze multimodal brain connectomics data for predicting Parkinson’s disease, demonstrating the effectiveness of deep learning in neurological disorder classification.

  • Disrupted structural connectome and neurocognitive functions in Duchenne muscular dystrophy: classifying and subtyping based on Dp140 dystrophin isoform

    • Year: 2022

    • Journal: Journal of Neurology

    • Citations: 11 (Loop)

    • Summary: This study explores the relationship between structural brain connectivity disruptions and neurocognitive deficits in Duchenne muscular dystrophy, with a focus on the Dp140 dystrophin isoform for patient subtyping.

  • Developing a radiomics signature for supratentorial extra-ventricular ependymoma using multimodal MR imaging

    • Year: 2021

    • Journal: Frontiers in Neurology

    • Citations: 5 (Google Scholar)

    • Summary: The research develops a radiomics-based approach using multimodal MRI to characterize supratentorial extra-ventricular ependymoma, enhancing tumor classification and diagnosis.

  • Quantifying Geographic Atrophy in Age-Related Macular Degeneration: A Comparative Analysis Across 12 Deep Learning Models

    • Year: 2024

    • Journal: Investigative Ophthalmology & Visual Science

    • Summary: This study compares the performance of 12 deep learning models in quantifying geographic atrophy in age-related macular degeneration, assessing their accuracy and reliability for clinical applications.

Conclusion

Apoorva Safai is a highly qualified candidate for the Best Researcher Award based on her strong academic background, impactful research, prestigious grants, and leadership in medical imaging and deep learning. Addressing minor improvements in authorship and funding scale would further elevate her profile. Overall, she is an excellent contender for the award.

Farimah Beheshti | Neuroscience | Best Researcher Award

Published on by Global Academic Awards

Assist. Prof. Dr. Farimah Beheshti | Neuroscience | Best Researcher Award

Assist. Prof. Dr. Farimah Beheshti, Torbat Heydriyeh University of Medical Sciiences, Iran

Dr. Farimah Beheshti is an Assistant Professor in Medical Physiology at Torbat Heydariyeh University of Medical Sciences, Iran. She holds a PhD in Medical Physiology from Mashhad University of Medical Sciences (2018). Her research focuses on learning and memory impairment, cognitive disorders, and brain developmental disorders. Dr. Beheshti has authored numerous publications and presented at various national and international conferences. She is a skilled neuroscientist with expertise in rodent behavioral assessments, stereotaxic surgery, and scientific writing. Among her honors are Top Researcher awards from Mashhad and Torbat Heydariyeh Universities. 🏆📚

 

Publication Profile

Google Scholar

Academic Background

Dr. Beheshti has a strong academic foundation in Medical Physiology, with an M.Sc. and PhD from Mashhad University of Medical Sciences. Her education, spanning from biological sciences to specialized neuroscience, underscores her deep knowledge in the field. Her research focuses on mechanisms of cognitive disorders, particularly in relation to learning and memory impairments, which is central to advancing neuroscience.

Research Skills

Dr. Beheshti’s practical experience in neuroscience is extensive, including advanced techniques like in vivo extracellular single unit recording, stereotaxic surgery, and behavioral assessments. These skills demonstrate her proficiency in experimental research and her ability to handle complex laboratory procedures, which significantly contribute to her research accomplishments.

Recognition

With an H-index of 30 on Scopus, Dr. Beheshti has published extensively in reputable journals. Her research contributions are backed by a significant amount of peer-reviewed work and substantial impact in the field, as evidenced by her Web of Science Researcher ID and contributions to over 24 peer reviews in journals like Scientific Reports and Brain Research Bulletin. Her ability to influence the scientific community through publications and peer reviews is notable.

Teaching

Dr. Beheshti’s involvement in teaching neuroscience at the MSc level reflects her commitment to advancing the next generation of researchers and healthcare professionals. Her MSc thesis and PhD dissertation titles indicate a keen interest in cognitive health, particularly in the context of neurodegenerative diseases.

Awards and Honors

Dr. Beheshti’s recognition as a Top Researcher at Torbat Heydariyeh University of Medical Sciences for multiple years (2020 and 2021) speaks volumes about her sustained excellence and contributions to the field. Such recognition further solidifies her standing as an impactful researcher.

Research Focus

Assist. Prof. Dr. Farimah Beheshti’s research primarily focuses on neuropharmacology, neuroinflammation, and memory impairment. She investigates the effects of various plant-based compounds, such as Nigella sativa (black seed) and thymoquinone, on brain health, particularly in relation to oxidative stress and neuroinflammation in animal models. Her studies often explore neuroprotective agents in conditions like hypothyroidism, lipopolysaccharide-induced memory deficits, and neurodegenerative diseases. Dr. Beheshti’s work also delves into oxidative stress, cytokine regulation, and learning and memory functions, making significant contributions to understanding neuroprotection and therapeutic strategies for cognitive dysfunction. 🧠🌿💡🔬

 

Conclusion

Dr. Farimah Beheshti’s exceptional research achievements, combined with her teaching contributions, awards, and peer-reviewed work, make her an excellent candidate for the Research for Best Researcher Award. Her cutting-edge research, extensive presentation history, and consistent academic performance demonstrate her dedication to advancing the field of neuroscience, particularly in memory and cognitive health.

 

Publication Top Notes

  • The effects of thymoquinone on hippocampal cytokine level, brain oxidative stress status, and memory deficits induced by lipopolysaccharide in rats – Cited by: 107, Year: 2017 🧠💊
  • The effects of Nigella sativa extract on hypothyroidism-associated learning and memory impairment during neonatal and juvenile growth in rats – Cited by: 89, Year: 2017 🌱🧠
  • Neuropharmacological effects of Nigella sativa – Cited by: 89, Year: 2016 🌿💊
  • Inducible nitric oxide inhibitor aminoguanidine ameliorates deleterious effects of lipopolysaccharide on memory and long term potentiation in rat – Cited by: 71, Year: 2016 ⚡🧠
  • Neuronal nitric oxide synthase has a role in the detrimental effects of lipopolysaccharide on spatial memory and synaptic plasticity in rats – Cited by: 62, Year: 2016 🧠💡
  • The Effect of Allium cepa Extract on Lung Oxidant, Antioxidant, and Immunological Biomarkers in Ovalbumin-Sensitized Rats – Cited by: 61, Year: 2018 🧄🌬️
  • Beneficial effects of Urtica dioica on scopolamine-induced memory impairment in rats: protection against acetylcholinesterase activity and neuronal oxidative damage – Cited by: 60, Year: 2019 🌿🧠
  • Aminoguanidine affects systemic and lung inflammation induced by lipopolysaccharide in rats – Cited by: 59, Year: 2019 💊🌬️
  • The effects of PPAR-γ agonist pioglitazone on hippocampal cytokines, brain-derived neurotrophic factor, memory impairment, and oxidative stress status in lipopolysaccharide – Cited by: 56, Year: 2019 💊🧠
  • Thymoquinone reverses learning and memory impairments and brain tissue oxidative damage in hypothyroid juvenile rats – Cited by: 55, Year: 2018 🧠💊