Chandrama Mukherjee | Neuroscience | Women Researcher Award

Published on by CAD Awards

Mrs. Chandrama Mukherjee | Neuroscience | Women Researcher Award

Graduate Student at Georgia State University | United States

Chandrama Mukherjee is a dedicated researcher in neuroimaging and neurophysics, with expertise in functional and structural brain analysis. Her work integrates advanced techniques such as fMRI, dynamic causal modeling, and connectivity analysis to explore complex neurological processes related to cognitive function, neurodegenerative diseases, and behavioral impacts of technology. She has demonstrated strong interdisciplinary knowledge by combining physics, neuroscience, and computational modeling in her studies.

Profile Verification

Google Scholar

Education Details

She holds a strong academic foundation in electronics, instrumentation, and neurophysics, advancing her knowledge from undergraduate engineering to doctoral research in neuroimaging and brain dynamics. Her academic journey reflects an interdisciplinary approach that bridges engineering principles with neuroscience, supported by rigorous training in advanced imaging, computational methods, and data analysis.

Professional Experience

Chandrama has gained experience across both industry and academia. She began her professional career as a systems engineer, focusing on application support, database management, and client-oriented solutions. Transitioning to research, she has served as a graduate research assistant, where she has designed and executed neuroimaging protocols, managed participant recruitment, and carried out advanced data analysis. Beyond her research, she contributes to the professional community as a co-chair of a women engineers’ society and as a mentor for young students in science and engineering fairs.

Research Interests

Her research interests span structural and functional neuroimaging, brain morphometry, and connectivity analysis. She is particularly focused on understanding sex-dependent structural changes in neurodegenerative disorders such as Alzheimer’s disease and mild cognitive impairment, as well as exploring the cognitive and structural effects of video gaming on the brain. Additionally, she investigates brain network dynamics during resting-state and task-based paradigms, integrating advanced statistical and computational tools for functional connectome analysis.

Awards and Honors

Chandrama has been recognized for her academic excellence and contributions to research through fellowships and departmental awards. These honors highlight her commitment to advancing knowledge in neuroimaging and her role as an emerging scholar in the field.

Publication Top Notes

Ultrasonic sensor based smart blind stick. 2018 International Conference on Current Trends Towards Converging Technologies, 100.

Action Video Gaming Enhances Brain Structure: Increased Cortical Thickness and White Matter Integrity in Occipital and Parietal Regions.

Conclusion

Through a combination of technical expertise, research innovation, and community involvement, Chandrama Mukherjee exemplifies the qualities of a forward-looking researcher. Her work bridges engineering and neuroscience, addressing critical questions in brain health and cognitive science while fostering professional development and inspiring the next generation of scientists.

Zahra Tabatabaei |Medical image|Best Researcher Award

Published on by CAD Awards

Dr.Zahra Tabatabaei |Medical image|Best Researcher Award

postdoc, Universitat Politècnica de València,Spain

Dr. Zahra Tabatabaei is a postdoctoral researcher at the Universitat Politècnica de València, Spain. She specializes in artificial intelligence, robotics, and intelligent control systems. Dr. Tabatabaei holds a Ph.D. in Computer Aided Design In Mechanical Engineering & Robotics (2013) from the University of Isfahan, Iran, where she also earned her M.Sc. in Computer Aided Design In Mechanical Engineering and B.S. in Computer Science & Engineering. With extensive experience in AI development, she has contributed to academia and industry through research, patents, and leadership roles, including heading RoboCup teams and co-founding Unitech. Her expertise bridges cutting-edge AI innovation and practical applications.

 

Professional Profiles:

Google  Scholar

🎓 Education :

Ph.D. in AI Technologies for Health and Wellbeing (2013–2017),Polytechnic University of Valencia, Valencia, Spain,Thesis: Strategies for Cloud-Based Histological Image Retrieval,Master’s Degree in Electronic Engineering,Bu-Ali Sina University, Hamedan, Iran,Thesis: Object-Based Feature Extraction Using Segmentation,Bachelor’s Degree in Electronic Engineering,Hamedan University of Technology, Hamedan, Iran

 

🏢 Experience:

Early Stage Researcher in Marie-Curie Funded Project (H2020 Agreement ID: 860627), 2021–Present
Conducted research in the CLARIFY Project, focusing on Content-Based Medical Image Retrieval (CBMIR) for histopathological images. Developed Python algorithms for image processing and collaborated with international researchers and pathologists to advance CBMIR methodologies and improve image retrieval systems.,Software Developer, Tyris Software Company, 2020–Present,Specialized in histopathological image processing and analysis, implementing tailored solutions for medical imaging challenges using advanced techniques.,Research Fellow, University of Stavanger (UiS), Sep 2021–Dec 2021,Developed an unsupervised classification approach for histopathological cancer images, leveraging the largest pixel-wise annotated prostate cancer dataset. Designed a high-performance classifier for accurate cancer detection without relying on non-histopathological pre-trained models.,Research Fellow, University of Granada (UGR), Jun 2022–Jul 2022,Investigated the impact of color normalization on feature extraction and retrieval accuracy in CBMIR systems, focusing on histopathological image analysis.

 

Skills:

Programming & Tools,Proficient in Python (TensorFlow, OpenCV, matplotlib), MATLAB, VScode, Docker, FastAPI, Streamlit, and SQL.,Technical Expertise,Skilled in neural networks, convolutional neural networks (CNNs), deep learning architectures, image preprocessing, feature extraction, object detection, computer vision techniques, and machine learning.,Teaching & Content Creation,Experienced in academic writing and creating instructional content on Python, machine learning, and image processing platforms.

 

Research Focus :

Zahra Tabatabaei’s research emphasizes developing innovative techniques for medical image retrieval and analysis, particularly in histopathology. Her contributions include advancing unsupervised classification methods, enhancing retrieval accuracy through feature extraction and color normalization, and creating domain-specific classifiers. Through collaboration on international research projects, she has significantly improved CBMIR methodologies, showcasing expertise in artificial intelligence, deep learning, and image processing.

 

🔬Awards:

Awarded for achievements in state-of-the-art feature extraction methods at Hamedan University of Technology in 2018 and non-linear feature classification at Bu-Ali Sina University in 2018. Certified in deep learning for image processing (2022) and academic writing for research paper composition (2023).

 Publications:

  • Title: MRI and PET/SPECT image fusion at feature level using ant colony-based segmentation
    Authors: HR Shahdoosti, Z Tabatabaei
    Journal: Biomedical Signal Processing and Control
    Year: 2019
    Volume/Issue: 47, Pages 63-74
    Citations: 51

 

  • Title: Residual block Convolutional Auto Encoder in Content-Based Medical Image Retrieval
    Authors: Z Tabatabaei, A Colomer, K Engan, J Oliver, V Naranjo
    Conference: 2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop
    Year: 2022
    Citations: 17

 

  • Title: Deep learning for skin melanocytic tumors in whole-slide images: A systematic review
    Authors: A Mosquera-Zamudio, L Launet, Z Tabatabaei, R Parra-Medina, et al.
    Journal: Cancers
    Year: 2022
    Volume/Issue: 15 (1), Article 42
    Citations: 11

 

  • Title: Towards More Transparent and Accurate Cancer Diagnosis with an Unsupervised CAE Approach
    Authors: Z Tabatabaei, A Colomer, JO Moll, V Naranjo
    Conference/Journal: IEEE Explore
    Year: 2023
    DOI: 10.10363200
    Citations: 10

 

  • Title: Wwfedcbmir: World-wide federated content-based medical image retrieval
    Authors: Z Tabatabaei, Y Wang, A Colomer, J Oliver Moll, Z Zhao, V Naranjo
    Journal: Bioengineering
    Year: 2023
    Volume/Issue: 10 (10), Article 1144
    Citations: 9

 

  • Title: Object-based feature extraction for hyperspectral data using firefly algorithm
    Authors: HR Shahdoosti, Z Tabatabaei
    Journal: International Journal of Machine Learning and Cybernetics
    Year: 2020
    Volume/Issue: 11 (6), Pages 1277-1291
    Citations: 9

 

  • Title: Self-supervised learning of a tailored Convolutional Auto Encoder for histopathological prostate grading
    Authors: Z Tabatabaei, A Colomer, K Engan, J Oliver, V Naranjo
    Conference: EUSIPCO 2023
    Year: 2023
    DOI: 10.23919/EUSIPCO58844.2023.10289741
    Citations: 7

 

  • Title: Intelligent vectorised architecture for performance enhancement of GNSS receivers in signal blocking situations
    Authors: A Tabatabaei, Z Koohi, MR Mosavi, Z Tabatabaei
    Journal: Survey Review
    Year: 2021
    Volume/Issue: 53 (381), Pages 513-527
    Citations: 2

 

  • Title: Advancing Content-Based Histopathological Image Retrieval Pre-Processing: A Comparative Analysis of the Effects of Color Normalization Techniques
    Authors: Z Tabatabaei, F Pérez Bueno, A Colomer, JO Moll, R Molina, V Naranjo
    Journal: Applied Sciences
    Year: 2024
    Volume/Issue: 14 (5), Article 2063
    Citations: 1

 

  • Title: Siamese Content-based Search Engine for a More Transparent Skin and Breast Cancer Diagnosis through Histological Imaging
    Authors: Z Tabatabaei, A Colomer, JAO Moll, V Naranjo
    Platform: arXiv Preprint
    Year: 2024
    DOI/URL: arXiv:2401.08272
    Citations: 1

 

  • Title: Deep learning strategies for histological image retrieval
    Authors: Z Tabatabaei, A Colomer, JO Moll, V Naranjo
    Institution: UPV
    Year: 2024

 

  • Title: A new object-based feature extraction method using segmentation for classification of hyperspectral images
    Authors: ZT Hamid Reza Shahdoosti
    Journal: Electronics Industries Quarterly
    Year: 2020
    Volume/Issue: 2 (11), Pages 109-128

 

 

Conclusion:

Dr. Tabatabaei is a highly suitable candidate for the Research for Best Researcher Award. Her strengths in technical expertise, impactful research, international collaboration, and knowledge dissemination make her a standout nominee. Addressing areas such as project leadership and interdisciplinary collaboration could further enhance her profile.

Mehran Emadi Andani |Noninvasive Brain|Best Researcher Award

Published on by CAD Awards

Dr.Mehran Emadi Andani |Noninvasive Brain|Best Researcher Award

Researcher and Scientific Consultant, University of Verona,Italy

Dr. Michaels Aibangbee is a PACFA-registered psychotherapist with extensive experience working with diverse populations, including families, couples, and groups. He employs a personalized approach, utilizing various therapeutic modalities such as Person-Centred Therapy, Cognitive Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Motivational Interviewing, Acceptance and Commitment Therapy (ACT), Solution-Focused Therapy, Family Systems Therapy, Couples Coaching, and Emotionally Focused Therapy. His practice is inclusive, addressing the unique needs of culturally and ethnically diverse clients in both individual and group settings

 

Professional Profiles:

Google  Scholar

🎓 Education :

Mehran Emadi Andani holds a Ph.D. in Biomedical Engineering from the Faculty of Electrical Engineering at the University of Tehran, Tehran, Iran (2003–2009). He earned an M.Sc. in Biomedical Engineering (1996–1999) and a B.Sc. in Electronics Engineering (1991–1996) from the same university and Isfahan University of Technology, respectively. His academic achievements are complemented by prestigious scholarships, including a Ph.D. scholarship from the Iranian Ministry of Science, Research and Technology and a B.Sc. scholarship from Isfahan University of Technology.

 

🏢 Experience:

Dr. Emadi Andani has extensive experience in academia, research, and industry. Since 2023, he has been a Scientific Consultant at both Brain Products Italia Srl. and the University of Verona. He served as a Research Fellow at the University of Verona from 2016 to 2023, with prior stints from 2011 to 2015. Earlier in his career, he was an Assistant Professor at the University of Isfahan’s Department of Biomedical Engineering (2009–2011 and 2013–2016). His industry experience includes roles as a Biomedical Engineer at ArminTeb Co. (2004–2009) and an Electronic Engineer at Nashiba EEG Co. (1999–2004). He has also gained international exposure as a Visiting Researcher at BioRob Lab, EPFL, Lausanne, Switzerland, in 2007, and through training at Corbett Research Co. in Sydney, Australia.

 

Skills:

Dr. Emadi Andani has over a decade of experience in signal processing, machine learning, artificial intelligence, and pattern recognition. He is proficient in tools like MATLAB, Simulink, R, SPSS, and LabChart. His expertise spans designing and implementing biomedical instrumentation, developing real-time electronic sensors, and conducting statistical analysis. His specialization in neurophysiological data analysis includes extensive work with TMS and tDCS applications. Additionally, he is skilled in human movement data acquisition and the repair and maintenance of biomedical instruments.

 

Research Focus :

His research interests lie at the intersection of biomedical engineering, neuroscience, and artificial intelligence. He has contributed to studies on neurophysiological signal analysis, motor control, and the development of non-invasive neuromodulation techniques. Notable research includes projects on emotional state recognition using physiological signals and motor planning based on tau theory.

 

🔬Awards:

Dr. Emadi Andani has received numerous accolades for his academic and professional contributions. His awards include the Best Paper Award at the CISCE 2024 International Conference in Guangzhou, China, and at the Iranian Conference on Biomedical Engineering in 2015. He was also the recipient of the prestigious Susanne Klein-Vogelbach 2015 prize and the Cooperint Grant from the University of Verona. Additionally, he has been recognized in competitive academic forums, such as ranking 2nd in the Iranian Mathematics Olympiad (1990) and achieving top rankings in national entrance exams and other competitions.

 Publications:

  • Placebo-induced changes in excitatory and inhibitory corticospinal circuits during motor performance
    • Authors: M Fiorio, M Emadi Andani, A Marotta, J Classen, M Tinazzi
    • Journal: The Journal of Neuroscience
    • Year: 2014
    • Citation Count: 80

 

  • The role of expectation and beliefs on the effects of non-invasive brain stimulation
    • Authors: M Braga, D Barbiani, M Emadi Andani, B Villa-Sánchez, M Tinazzi
    • Journal: Brain Sciences
    • Year: 2021
    • Citation Count: 42

 

  • Trajectory of human movement during sit to stand: a new modeling approach based on movement decomposition and multi-phase cost function
    • Authors: M Sadeghi, M Emadi Andani, F Bahrami, M Parnianpour
    • Journal: Experimental Brain Research
    • Year: 2013
    • Citation Count: 42

 

  • Changes in perception of treatment efficacy are associated to the magnitude of the nocebo effect and to personality traits
    • Authors: N Corsi, M Emadi Andani, M Tinazzi, M Fiorio
    • Journal: Scientific Reports
    • Year: 2016
    • Citation Count: 38

 

  • Modulation of inhibitory corticospinal circuits induced by a nocebo procedure in motor performance
    • Authors: M Emadi Andani, M Tinazzi, N Corsi, M Fiorio
    • Journal: PLoS One
    • Year: 2015
    • Citation Count: 37

 

  • When words hurt: verbal suggestion prevails over conditioning in inducing the motor nocebo effect
    • Authors: N Corsi, M Emadi Andani, D Sometti, M Tinazzi, M Fiorio
    • Journal: European Journal of Neuroscience
    • Year: 2019
    • Citation Count: 32

 

  • MODEM: a multi-agent hierarchical structure to model the human motor control system
    • Authors: M Emadi Andani, F Bahrami, PJ Maralani, AJ Ijspeert
    • Journal: Biological Cybernetics
    • Year: 2009
    • Citation Count: 27

 

  • COMAP: A new computational interpretation of human movement planning level based on coordinated minimum angle jerk policies and six universal movement elements
    • Authors: M Emadi Andani, F Bahrami
    • Journal: Human Movement Science
    • Year: 2012
    • Citation Count: 24

 

  • The placebo effect in the motor domain is differently modulated by the external and internal focus of attention
    • Authors: G Rossettini, M Emadi Andani, F Dalla Negra, M Testa, M Tinazzi
    • Journal: Scientific Reports
    • Year: 2018
    • Citation Count: 23

 

  • Design of robust adaptive controller and feedback error learning for rehabilitation in Parkinson’s disease: a simulation study
    • Authors: K Rouhollahi, M Emadi Andani, SM Karbassi, I Izadi
    • Journal: IET Systems Biology
    • Year: 2016
    • Citation Count: 20

 

Conclusion:

Dr. Emadi Andani is highly deserving of the Best Researcher Award due to his outstanding contributions to science and technology, particularly in biomedical engineering and neuroscience. Addressing the areas of improvement—such as securing more prominent grants and broadening high-impact publications—could further solidify his candidacy for such accolades.