NALINI ATCHAYARAM | Neuroscience | Best Research Award

Prof. Nalini Atchayaram | Neuroscience | Best Research Award

NATIONAL INSTITUTE OF MENTAL HEALTH AND NEUROSCIENCES, India

Author Profile

Early Academic Pursuits 📚🎓

Prof. Dr. (Mrs.) Atchayaram Nalini’s academic journey reflects a relentless pursuit of excellence in the medical field. Beginning her educational journey at the esteemed Bangalore Medical College, she graduated with an MBBS degree in 1988, achieving an impressive 89% and earning a Gold Medal for the highest aggregate marks in her final year. Her exceptional academic performance set the foundation for her future accomplishments.

Her commitment to neurology led her to pursue a DM in Neurology at Bangalore University, which she successfully completed in 1994. Once again, she was awarded a Gold Medal, cementing her reputation as a dedicated and brilliant scholar in the field of neurology.

Furthering her quest for knowledge, Prof. Nalini obtained a PhD from Maastricht University, The Netherlands, in 2020. This achievement underscored her passion for research and advanced understanding of neurological disorders. In 2021, she diversified her expertise by completing an MBA in Hospital Management from Madurai Kamaraj University, Tamil Nadu, equipping herself with leadership and administrative skills vital for healthcare management.


Professional Endeavors 🩺💼

Prof. Nalini serves as a Professor in the Department of Neurology at the prestigious National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, a hub of excellence in neurological research and education. Her clinical and academic leadership extends to her role as the Lead of the NIMHANS Advanced Center for Neuromuscular Disorders (NACNMD), an initiative under the Ministry of Health and Family Welfare.

In her illustrious career, Prof. Nalini has played a pivotal role in diagnosing and managing complex neuromuscular disorders. Her expertise has been instrumental in advancing patient care and setting new benchmarks in clinical practice.


Contributions and Research Focus 🔬📖

Prof. Nalini’s research is driven by a passion for understanding the complexities of neuromuscular disorders and their impact on patients’ lives. Her work encompasses various aspects of neurology, including:

  • Neuromuscular Disorders: Advancing diagnostic and therapeutic approaches to improve outcomes for patients.
  • Neurogenetics: Exploring the genetic underpinnings of neurological conditions to inform personalized medicine.
  • Healthcare Management: Integrating clinical insights with hospital management strategies for efficient and patient-centered care.

Her PhD work at Maastricht University focused on cutting-edge neurological research, which has contributed significantly to the global understanding of the field. Prof. Nalini’s dedication to research ensures that her findings translate into tangible benefits for both patients and the medical community.


Accolades and Recognition 🏅✨

Prof. Nalini’s remarkable achievements have been recognized through numerous accolades, including:

  • Gold Medal for Highest Aggregate Marks in Final MBBS (1988).
  • Gold Medal in Final DM Neurology (1994).
  • Recognition for her PhD in Neurology from Maastricht University (2020).
  • Leadership roles in pioneering initiatives at NIMHANS.

Her awards reflect not just academic brilliance but also her commitment to excellence in medical practice and research.


Impact and Influence 🌍🤝

As a mentor, researcher, and clinician, Prof. Nalini has significantly impacted the neurology community. Her role as the Lead of NACNMD has been transformative in establishing a specialized center that addresses the challenges of neuromuscular disorders in India.

Her influence extends beyond the clinical realm, as she actively contributes to the academic and professional growth of her students and peers. Through her teaching, she has inspired a generation of neurologists and healthcare professionals to pursue excellence and compassion in their work.


Legacy and Future Contributions 🌟📈

Prof. Nalini’s legacy lies in her unwavering commitment to patient care, academic excellence, and pioneering research. Her multidisciplinary expertise, encompassing neurology, neurogenetics, and hospital management, positions her as a thought leader in the evolving landscape of healthcare.

Looking ahead, Prof. Nalini aims to:

  1. Enhance Neurological Research: Expand understanding of neuromuscular and genetic disorders.
  2. Strengthen Healthcare Systems: Integrate hospital management insights to improve patient outcomes.
  3. Inspire Future Generations: Continue mentoring aspiring neurologists and researchers.

Prof. Dr. (Mrs.) Atchayaram Nalini stands as a beacon of inspiration in the field of neurology, embodying a rare blend of academic brilliance, clinical expertise, and compassionate leadership. Her contributions have left an indelible mark on the medical community, ensuring her legacy as a transformative force in healthcare. 🧠🌟

Citations

A total of 3,549 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations        3,549
  • h-index          264
  • i10-index       31

Notable Publications 

  • Title: Magnetic Resonance Imaging in Idiopathic Inflammatory Myopathies: Deciphering the Pattern of Muscle Involvement
    Authors: Sridhar, S., Nashi, S., Kulanthaivelu, K., Mahadevan, A., Nalini, A.
    Journal: Neuromuscular Disorders, 2025.
  • Title: Virtual Leadership Program for Adolescents with Muscular Dystrophy: A Process Evaluation
    Authors: Sadasivan, A., Warrier, M.G., Thomas, P.T., Vengalil, S., Nalini, A.
    Journal: Social Work with Groups, 2025.
  • Title: Telehealth Services for an Adolescent with Duchenne Muscular Dystrophy (DMD) During the COVID-19 Pandemic
    Authors: Sadasivan, A., Warrier, M.G., Vengalil, S., Thomas, P.T., Nalini, A.
    Journal: Australian Social Work, 2025.
  • Title: Inter-Speaker Acoustic Differences of Sustained Vowels at Varied Dysarthria Severities for Amyotrophic Lateral Sclerosis
    Authors: Bhattacharjee, T., Vengalil, S., Belur, Y., Atchayaram, N., Ghosh, P.K.
    Journal: JASA Express Letters, 2024.
  • Title: Autoantibody-Based Clinicoradiopathologic Phenotyping of Idiopathic Inflammatory Myopathies: An Indian Cohort
    Authors: Girija, M.S., Vengalil, S., Kulanthaivelu, K., Mahadevan, A., Nalini, A.
    Journal: Journal of Clinical Neuromuscular Disease, 2024.

RAVEENDRABABU VEMPATI | Neuroscience | Best Researcher Award

Mr. RAVEENDRABABU VEMPATI | Neuroscience | Best Researcher Award

VIT-AP UNIVERSITY-India

Author Profile

Early Academic Pursuits 🎓

Raveendrababu Vempati’s journey in academics began with his Bachelor’s in Electronics and Communication Engineering from Lakireddy Bali Reddy College of Engineering, Mylavaram, affiliated with JNTUH, Hyderabad. Graduating in 2008, he achieved a respectable 67.47%, which laid the foundation for his future pursuits in engineering. Following this, he furthered his academic credentials by earning a Master of Technology (M.Tech) in Systems and Signal Processing from the same institution, this time affiliated with JNTUK, Kakinada. During his M.Tech studies, he excelled, graduating with an impressive 80.02% and was awarded a Gold Medal 🏅 in 2011 for his exceptional academic performance. This period marked a significant milestone in Raveendrababu’s academic journey, as it provided him with a solid understanding of signal processing, a key area that would later play a pivotal role in his research career.

Professional Endeavors 🧑‍🏫

After completing his M.Tech, Raveendrababu embarked on a professional career as an Assistant Professor in the Department of Electronics and Communication at Vikas Group of Institutions, Vijayawada. From 2011 to 2021, he dedicated himself to teaching and mentoring students, focusing on areas such as signal processing, electronics, and communication engineering. His teaching experience not only enhanced his understanding of these subjects but also helped him stay current with technological advancements in the field. Additionally, Raveendrababu took on leadership roles at the institution, serving as an Internal Quality Assurance Cell (IQAC) member from 2019 to 2021 and as the College Academic Coordinator from 2013 to 2014. These roles allowed him to contribute significantly to the academic governance and quality improvement processes within the institution.In 2021, Raveendrababu took the next step in his academic journey by enrolling in a Doctor of Philosophy (Ph.D.) program at the School of Electronics Engineering, VIT-AP University, Amaravathi. His thesis, titled “Automated Emotion Recognition from EEG signals using Machine Learning Algorithms,” focuses on a cutting-edge area of research at the intersection of neuroscience and artificial intelligence, aiming to develop models for recognizing emotions from EEG signals. This research is highly relevant in fields such as cognitive neuroscience, human-computer interaction, and mental health applications.

Contributions and Research Focus 🧠

Raveendrababu’s research focuses on emotion recognition using EEG signals combined with machine learning algorithms. This area of research is vital for advancing technologies in brain-computer interfaces and cognitive load detection, with applications in healthcare, gaming, and human-computer interaction. His research explores innovative methods such as multivariate decomposition and ensemble learning to enhance cross-subject emotion recognition. Notable among his published works is his 2024 paper, Cross-subject emotion recognition from multichannel EEG signals using multivariate decomposition and ensemble learning, published in IEEE Transactions on Cognitive and Developmental Systems.In addition to emotion recognition, his research includes developing models for cognitive load detection, as evident in his co-authored work on Robust Time-Frequency Representation and Transfer Learning for Automated Cognitive Load Detection, which is currently under review in IEEE Transactions on Human-Machine Systems. He has also contributed significantly to the field of electrooculography (EOG) artifact removal from EEG signals, ensuring cleaner and more accurate EEG data for analysis.

Accolades and Recognition 🏅

Raveendrababu’s dedication to research has been recognized with multiple awards, highlighting his contributions to the academic community. In 2023 and 2024, he was honored with the Raman Research Award at VIT-AP University. Additionally, he received the Research Award for Publications during the 2023–24 academic year. His exemplary performance during his Master’s program was also recognized with a Gold Medal from Lakireddy Bali Reddy College of Engineering in 2011.Beyond these accolades, Raveendrababu has earned NPTEL certifications in Python for Data Science and Deep Learning for Computer Vision, underscoring his continuous learning and expertise in the field of machine learning and artificial intelligence. His dedication to research excellence is also evident through his frequent participation in conferences, such as the 2022 IEEE Conference on Information and Communication Technology, where he presented his work on eye blink artifact removal using multivariate variational mode decomposition and PCA.

Impact and Influence 🌟

Through his innovative research in EEG-based emotion recognition and machine learning, Raveendrababu has made significant contributions to both academia and industry. His work has the potential to revolutionize how emotions are understood and recognized through non-invasive means, which could have far-reaching implications in mental health, cognitive science, and human-computer interaction. His research on cognitive load detection could pave the way for more intuitive brain-computer interfaces that adapt to user needs based on real-time cognitive states.As a teacher and mentor, Raveendrababu has influenced many students, imparting knowledge and fostering a passion for research. His experience in academic governance, coupled with his commitment to quality education, has made a lasting impact on the institutions where he has taught.

Legacy and Future Contributions 🚀

Looking forward, Raveendrababu Vempati is poised to make lasting contributions to the fields of machine learning, signal processing, and cognitive neuroscience. His research on EEG-based emotion recognition is particularly relevant in an era where mental health monitoring and neurotechnology are gaining increased attention. His work not only advances the state of the art in these fields but also opens up new avenues for real-world applications in areas such as healthcare, neurofeedback systems, and personalized mental health interventions.As he continues to publish high-impact papers and contribute to cutting-edge research, Raveendrababu’s legacy will likely be defined by his pioneering work in integrating machine learning with neuroscience. He will also continue to inspire the next generation of researchers through his teaching, mentoring, and academic leadership. His achievements serve as a testament to the power of perseverance and dedication in pushing the boundaries of scientific knowledge.

Citations

A total of 39 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations        39
  • h-index           4
  • i10-index        3

Notable Publications 

  • Cross-Subject Emotion Recognition from Multichannel EEG Signals using Multivariate Decomposition and Ensemble Learning
    Authors: Raveendrababu Vempati, Lakhan Dev Sharma, Rajesh Kumar Tripathy
    Journal: IEEE Transactions on Cognitive and Developmental Systems, 2024.
  • EEG Rhythm Based Emotion Recognition using Multivariate Decomposition and Ensemble Machine Learning Classifier
    Authors: Raveendrababu Vempati, Lakhan Dev Sharma
    Journal: Journal of Neuroscience Methods, 2023.
  • A Systematic Review on Automated Human Emotion Recognition using Electroencephalogram Signals and Artificial Intelligence
    Authors: Raveendrababu Vempati, Lakhan Dev Sharma
    Journal: Results in Engineering, 2023.
  • EOG Eye Blink Artifact Removal using Multivariate Variational Mode Decomposition and PCA
    Authors: Raveendrababu Vempati, Lakhan Dev Sharma
    Journal: 2022 IEEE 6th Conference on Information and Communication Technology, CICT 2022.

Kasturi Barik | Biomedical | Best Researcher Award

Assist Prof Dr. Kasturi Barik | Biomedical | Best Researcher Award

JIS Institute of Advanced Studies & Research (JISIASR), India

Author Profile

Early Academic Pursuits 🎓

Kasturi Barik’s journey into the world of electronics and communication engineering began at West Bengal University of Technology, where she completed her B.Tech with a strong foundation in Electronics and Communication Engineering, earning an impressive CGPA of 8.99/10. Her passion for biomedical signal processing and cognitive neuroscience led her to pursue advanced studies at the prestigious Indian Institute of Technology Kharagpur (IIT Kharagpur). There, she completed her MS by Research in Electronics and Electrical Communication Engineering, specializing in Biomedical Signal Processing, with a stellar CGPA of 9.64/10. Her master’s thesis focused on the “Single-trial Classification of EEG Signals to Investigate the Influence of Prior Expectation in Face Pareidolia,” showcasing her early interest in understanding complex brain signal patterns.

Professional Endeavors 🧠

After excelling in her master’s program, Kasturi continued her academic journey at IIT Kharagpur, where she pursued a Ph.D. in Neuro Signal Processing and Machine Learning. Her doctoral research centered on the “Machine Learning Approach for Autism Detection in Young Children using Magnetoencephalogram (MEG) Signals.” This work exemplifies her dedication to applying cutting-edge technology to healthcare, particularly in the early detection and understanding of autism. Currently, she serves as an Assistant Professor at the Centre for Data Science (CDS) at JIS Institute of Advanced Studies & Research (JISIASR), JIS University, Kolkata, India. Here, she imparts her extensive knowledge of neuro-signal processing and machine learning to the next generation of engineers and researchers.

Contributions and Research Focus 🔬

Kasturi’s research is deeply rooted in neuro-signal processing, with a particular focus on using machine learning to decipher complex biomedical signals. Her doctoral research made significant strides in autism detection by analyzing MEG signals. She proposed a novel phase-based spectral domain feature, which outperformed traditional power spectral density-based features in identifying autistic children. Her research also explored the fusion of power and phase-based features, leading to a more robust model for autism detection. Furthermore, she introduced a common spatial pattern (CSP) based machine learning approach to uncover the possible cortical spatial patterns associated with autism, providing new insights into the neurological underpinnings of the disorder.In addition to her work on autism, Kasturi has contributed to projects that explore the neural mechanisms of other mental health conditions, such as obsessive-compulsive disorder (OCD). She applied artificial neural network modeling to differentiate between low and high OCD participants using EEG signals, demonstrating her versatility in applying machine learning to various neurological conditions.

Accolades and Recognition 🏅

Kasturi’s academic achievements have been consistently recognized through her high grades and the successful completion of complex research projects. Her work at IIT Kharagpur, particularly her contributions to understanding brain signal processing and autism detection, has positioned her as a rising star in the field of neuro-signal processing and machine learning. Although her Ph.D. thesis is currently under review, her research has already garnered attention within the academic community, paving the way for future accolades and recognition.

Impact and Influence 🌟

Kasturi’s work has the potential to significantly impact the field of cognitive neuroscience, particularly in the early detection and understanding of neurological disorders like autism. By developing machine learning models that can accurately detect autism in young children, her research could lead to earlier interventions and better outcomes for those affected by the disorder. Moreover, her contributions to understanding the neural mechanisms underlying other mental health conditions, such as OCD, highlight her broader impact on the field of mental health research.

Legacy and Future Contributions 🚀

As Kasturi continues her career as an Assistant Professor, her influence is likely to expand beyond her research. Her commitment to teaching and mentoring the next generation of engineers and researchers will ensure that her knowledge and expertise are passed on to others. Looking forward, Kasturi is poised to make significant contributions to the field of artificial intelligence in healthcare, particularly in the areas of neuro-signal processing and cognitive neuroscience. Her future work will likely continue to push the boundaries of what is possible with machine learning in healthcare, making her a key figure in the intersection of technology and medicine.

Citations

A total of 36 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations         36
  • h-index           8
  • i10-index        4

Notable Publications 

  1. Title: A Fusion-Based Machine Learning Approach for Autism Detection in Young Children Using Magnetoencephalography Signals
    Authors: Barik, K., Watanabe, K., Bhattacharya, J., Saha, G.
    Journal: Journal of Autism and Developmental Disorders
    Year: 2023.
  2. Title: Functional Connectivity Based Machine Learning Approach for Autism Detection in Young Children Using MEG Signals
    Authors: Barik, K., Watanabe, K., Bhattacharya, J., Saha, G.
    Journal: Journal of Neural Engineering
    Year: 2023.
  3. Title: Fusion of Spectral and Connectivity Features to Detect Depressive Disorder using EEG Signals
    Authors: Saha, U., Barik, K., De, A.
    Journal: Proceedings of 2023 IEEE 3rd Applied Signal Processing Conference, ASPCON 2023
    Year: 2023.
  4. Title: Autism Detection in Children using Common Spatial Patterns of MEG Signals
    Authors: Barik, K., Watanabe, K., Hirosawa, T., Bhattacharya, J., Saha, G.
    Journal: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
    Year: 2023.
  5. Title: Classification of Autism in Young Children by Phase Angle Clustering in Magnetoencephalogram Signals
    Authors: Barik, K., Watanabe, K., Bhattacharya, J., Saha, G.
    Journal: 26th National Conference on Communications, NCC
    Year: 2020.