S.S.Subashka Ramesh | Medicinal Chemistry | Best Researcher Award-duplicate-1

Published-on by Indian Scientist

Dr. S.S. Subashka Ramesh | Data Science and Machine learning | Best Researcher Award

SRM Institute of Science and Technology india, India

Dr. S.S. Subashka Ramesh is an accomplished academic and researcher in Computer Science and Engineering with a strong foundation in advanced computing and data-driven technologies. Holding doctoral and postgraduate qualifications, she has extensive teaching and research experience, mentoring scholars and contributing to impactful innovations. Her research interests include machine learning, artificial intelligence, edge computing, and medical imaging. With notable publications, patents, and academic leadership, she has earned professional recognition and continues to advance knowledge through research, collaboration, and technology-driven solutions for real-world challenges.

Citation Metrics (Google Scholar)

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Featured Publications

Ayshika Kapoor | Computer Science | Women Researcher Award

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Dr. Ayshika Kapoor | Computer Science | Women Researcher Award

Indian Institute of Technology Roorkee,  India

Dr. Ayshika Kapoor is a researcher in Electronics and Communication Engineering with a Ph.D. specializing in privacy-preserving and communication-efficient federated learning. Her work focuses on secure AI, urban sensing systems, and domain-adaptive learning. She has experience as a research scientist, contributing to intelligent mobility and autonomous systems. With multiple high-impact publications, conference presentations, and a granted copyright, she has earned prestigious fellowships and research recognition. Her contributions advance scalable, secure, and efficient AI solutions for real-world applications.

Citation Metrics (Google Scholar)

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Featured Publications


A resource adaptive secure aggregation protocol for federated learning based urban sensing systems


– Joint International Conference on Data Science (Cited by 6 · Year: 2023)


Optimization of user resources in federated learning for urban sensing applications


– Federated Learning for Distributed Data Mining Workshop (Cited by 3 · Year: 2023)

Deepti Deshwal | Artificial Intelligence | Women Researcher Award

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Dr. Deepti Deshwal | Artificial Intelligence | Women Researcher Award

Maharaja Surajmal Institute of Technology New Delhi | India

Dr. Deepti Deshwal is an accomplished Assistant Professor in Electronics & Communication Engineering with extensive teaching experience and expertise in Artificial Intelligence, Machine Learning, speech processing, biomedical image analysis, and computer vision. She holds a Ph.D. in AI and has contributed significantly through SCI/SCIE publications, editorial roles, and funded research projects. Recognized with multiple research awards, she actively mentors Ph.D. students and fosters innovation through IPR initiatives, conferences, and technical workshops. Her work bridges academic excellence with practical AI applications, driving technology-driven societal impact.

Citation Metrics (Scopus)

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Citations
306

h-index
9

Documents
22

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Featured Publications


Economic analysis of lithium ion battery recycling in India


– Wireless Personal Communications · 64 citations · 2022


Feature extraction methods in language identification: a survey


– Wireless Personal Communications · 59 citations · 2019


Isolated word language identification system with hybrid features from a deep belief network


– International Journal of Communication Systems · 34 citations · 2023
Citation counts may vary across databases; links redirect to publisher pages or Google Scholar search results for accessibility.

Sunil Datt Sharma | Computer Science | Best Researcher Award

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Dr. Sunil Datt Sharma | Computer Science | Best Researcher Award

Central University of Jammu | India

Dr. Sunil Datt Sharma is a distinguished researcher in the fields of Digital Signal Processing, Adaptive Signal Processing, and Machine Learning Applications, recognized for his contributions across computational biology, biomedical signal analysis, and intelligent imaging systems. With 289 citations, an h-index of 9, and 9 indexed documents, his research is widely acknowledged for its technical depth and interdisciplinary impact. He has authored numerous journal articles, conference papers, and book chapters covering areas such as CpG island detection, promoter identification using deep learning, image de-noising, transfer learning for fault diagnosis, micro-Doppler signature analysis, anisotropic diffusion models, and advanced frequency-domain algorithms. His academic background encompasses strong training in electronics, computing, and signal processing, complemented by extensive experience in teaching, research, and scholarly reviewing for reputed international journals. His research interests span computational genomics, machine learning-based biomedical systems, pattern recognition, and intelligent signal analysis. He has been actively engaged in professional peer-review activities for more than twenty journals, reflecting his standing within the global research community. His work integrates innovative algorithms with real-world applications, contributing to both theoretical advancement and practical solutions. Dr. Sharma continues to advance cutting-edge research aimed at addressing complex challenges across science and engineering.

Profile: Google Scholar

Featured Publications

Sharma, S. D., Shakya, K., & Sharma, S. N. (2011). Evaluation of DNA mapping schemes for exon detection. In 2011 International Conference on Computer, Communication and Electrical Technology (ICCCET). (Cited by: 42).

Sharma, S., Sharma, S. N., & Saxena, R. (2020). Identification of short exons disunited by a short intron in eukaryotic DNA regions. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17(5). (Cited by: 33).

Sharma, S. D., Saxena, R., & Sharma, S. N. (2015). Identification of microsatellites in DNA using adaptive S-transform. IEEE Journal of Biomedical and Health Informatics, 19(3), 1097–1105. (Cited by: 23).

Garg, P., & Sharma, S. (2020). Identification of CpG islands in DNA sequences using short-time Fourier transform. Interdisciplinary Sciences: Computational Life Sciences, 12(3), 355–367. (Cited by: 19).

Sharma, S. D., Saxena, R., Sharma, S. N., & Singh, A. K. (2015). Short tandem repeats detection in DNA sequences using modified S-transform. International Journal of Advances in Engineering and Technology, 8(2). (Cited by: 16).

Shanmugam S | Machine Learning | Best Researcher Award

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Dr. Shanmugam S | Machine Learning | Best Researcher Award

SRM Institute of Science and Technology | India

Dr. Shanmugam S is an academic and researcher in the field of computing technologies with a focus on Artificial Intelligence and Machine Learning. His scholarly portfolio reflects professional engagement with advanced areas including Soft Computing, Transfer Learning, and Quantum Computing. He has completed his doctoral research in Information and Communication, supported by previous postgraduate and undergraduate education in computer science and information technology disciplines. His publication record includes 24 research documents, with 342 citations received from 322 referencing documents, supported by an h-index of 8, highlighting the relevance and impact of his contributions in the research community. He has accumulated significant teaching and research experience, handling courses such as Data Structures, Object-Oriented Programming, Big Data for Machine Learning, Software Engineering, Business Computing, and Philosophy of Engineering. His efforts extend to guiding students, contributing to departmental academic activities, and participating in various scholarly workshops, seminars, and conferences. His research interests continue to explore emerging computational paradigms and their applications in solving real-world challenges. He has received recognition for academic and research contributions, reinforcing his professional standing. Overall, his work contributes to the advancement of intelligent systems and computational innovation.

Profile: Scopus

Featured Publications

Role of hydroxychloroquine in primary glomerular disease – a systematic review and meta-analysis of the current evidence. BMC Nephrology. (2025).

Exploring the ability of emerging large language models to detect cyberbullying in social posts through new prompt-based classification approaches. Information Processing and Management. (2025).

Kumar Rahul | Artificial Intelligence | Innovative Research Award

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Dr. Kumar Rahul | Artificial Intelligence | Innovative Research Award

NIFTEM | India

Dr. Kumar Rahul is an Assistant Professor in the Department of Interdisciplinary Sciences at the National Institute of Food Technology Entrepreneurship and Management (NIFTEM), Sonepat, combining his expertise in software engineering, big-data analytics and food-technology research. With a Ph.D. in Computer Science and Engineering focused on enhanced data cleaning and outlier-detection using hybrid meta-heuristics, and earlier degrees in software engineering (M.E.) and computer applications (BCA/MCA), his career spans roles in both academia and engineering. He has authored numerous peer-reviewed articles (including systematic reviews on big-data/AI, applications of AI and ML in food-industry and healthcare, hybrid meta-heuristic models, data-cleaning frameworks) and holds patents in sensor-network water-quality monitoring and deep–learning corner-detection algorithms. His Google Scholar h-index stands at 10 with over 500 citations, reflecting his growing research impact. His research interests include artificial intelligence and machine learning for food processing, big-data analytics and industrial systems, IoT/Edge–Fog–Cloud applications, and optimization/meta-heuristic techniques for outlier or anomaly detection. He has also contributed to applied projects such as mobile-app development for fruit-freshness checking and served as Co-PI on a funded initiative in the food-technology domain. His work has been recognised through awards including UGC-NET (LS) and strong GATE performance, and he actively participates in faculty development programs and serves as a resource-person on topics such as IoT in industries and agri-startups. In summary, Dr. Rahul brings a multidisciplinary blend of computer-science rigor and domain-specific application in food-technology, making him a valuable contributor to research and education in smart food systems and analytics.

Profile: Scopus

Featured Publications

Rahul, K., & Banyal, R. K. (Erratum). Retraction Note: Firefly algorithm: an optimization solution in big data processing for the healthcare and engineering sector [Retraction note]. International Journal of Speech Technology, 24(3), 581–592. https://doi.org/10.1007/s10772-020-09783-y

Rahul, K., Arora, N., & Arora, S. (2025). Effectiveness of blockchain and IoT in horticulture crop supply chain. In B. Sharma, D.-T. Do, S. N. Sur, & C.-M. Liu (Eds.), Advances in Communication, Devices and Networking. Springer Nature.

Major Singh Goraya | Computer Science | Best Researcher Award

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Prof. Major Singh Goraya | Computer Science | Best Researcher Award

Sant Longowal Institute of Engineering and Technology | India

Dr. Major Singh Goraya is a Professor in the Department of Computer Science and Engineering at Sant Longowal Institute of Engineering and Technology (SLIET), Longowal. He holds a Ph.D. from Punjabi University, complemented by strong academic foundations in computer engineering. His primary research areas include cloud computing, resource management, green computing, fault tolerance, and load balancing. With 27 Scopus-indexed publications, 460 citations across 399 documents, and an h-index of 10, Dr. Goraya has made consistent scholarly contributions to high-performance and sustainable computing. His studies have explored dynamic resource allocation, energy-efficient scheduling frameworks, and deep learning-based optimization techniques. He has supervised several Ph.D. and M.Tech. research scholars and continues to guide emerging researchers in cloud resource efficiency and intelligent computation. His international exposure through conferences in the UK, Canada, and Malaysia reflects his active engagement in global research forums. In addition, he has successfully organized numerous academic workshops, conferences, and training programs. Dr. Goraya’s innovative contributions strengthen the integration of artificial intelligence and cloud technology, promoting scalable and eco-efficient computational solutions that advance modern computer engineering research.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Goyal, N., Singh, T., & Goraya, M. S. (2025). Deep convolutional neural networks vs. vision transformers for video-based human activity recognition. In Proceedings of Lecture Notes in Computer Science (pp. xx–xx). Springer.

Singh, J., & Goraya, M. S. (2023). An autonomous multi-agent framework using quality of service to prevent service level agreement violations in cloud environment. International Journal of Advanced Computer Science and Applications, 14(3).

Goyal, N., Goraya, M. S., & Singh, T. (2023). An axiomatic analysis for object detection and recognition using deep learning. In Smart Innovation, Systems and Technologies (pp. xx–xx). Springer.

Thakur, A., & Goraya, M. S. (2022). A workload and machine categorization-based resource allocation framework for load balancing and balanced resource utilization in the cloud. International Journal of Grid and High Performance Computing, 14(2).

Hasan, M., Goraya, M. S., & Garg, T. (2022). E-FFTF: An extended framework for flexible fault tolerance in cloud. In Lecture Notes in Networks and Systems (pp. xx–xx). Springer.

Pritam BIKRAM | Artificial Intelligence | Best Researcher Award

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Mr. Pritam BIKRAM | Artificial Intelligence | Best Researcher Award

Indian Institute of Engineering Science and Technology, Shibpur, India

Author Profile

SCOPUS

ORCID

GOOGLE SCHOLAR

🎓 EARLY ACADEMIC PURSUITS

Mr. Pritam Bikram began his academic journey with a B.Tech in Information Technology from the Government College of Engineering and Leather Technology, graduating in 2020. With a strong foundation in computational systems and programming, he advanced his studies by pursuing an M.Tech in Information Technology at the prestigious Indian Institute of Engineering Science and Technology (IIEST). His dedication and academic excellence earned him a GATE scholarship during this period. Currently, he is pursuing his Ph.D. at IIEST, where his research is focused on advanced applications of Artificial Intelligence (AI) in real-world domains.

🏢 PROFESSIONAL ENDEAVORS

Throughout his academic tenure, Mr. Bikram has remained consistently involved in cutting-edge research and collaborative scientific inquiry. Working under a result-oriented and interdisciplinary professional environment, he has contributed to the development of novel AI-based solutions in Intelligent Transportation Systems (ITS), remote sensing, environmental monitoring, and precision agriculture. His analytical mindset and logical problem-solving approach have enabled him to tackle multifaceted challenges across domains.

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN ARTIFICIAL INTELLIGENCE

Mr. Bikram’s core research lies in the realm of Artificial Intelligence, with specific focus areas including:

  • Trajectory prediction using graph neural networks

  • Missing spatio-temporal data imputation

  • Deep learning applications for traffic forecasting

  • AI-driven spectral analysis for crop disease monitoring

His work is characterized by graph-based encoder-decoder learning frameworks, attentive graph structure learning, and dynamic attention mechanisms, reflecting a deep command over neural architectures and real-world data-driven applications.

🏅 ACADEMIC CITATIONS, ACCOLADES AND RECOGNITION

Mr. Bikram is the first author of multiple high-impact peer-reviewed journal articles, including:

  • Expert Systems with Applications (Elsevier, 2025)

  • Neurocomputing (Elsevier, 2024)

  • Applied Intelligence (Springer, 2024)

  • Remote Sensing Applications: Society and Environment (Elsevier, 2025)

His research has begun gaining strong academic traction and citations, contributing to the broader scientific discourse in AI and its applications. He has also received:

  • 🎓 GATE Scholarship (2020)

  • 🧠 Ph.D. Institute Scholarship (2022)

🌍 IMPACT AND INFLUENCE

Mr. Bikram’s contributions have significant implications for smart city development, environmental sustainability, and agritech innovations. His models have demonstrated real-world applicability in enhancing urban mobility, early disease detection in agriculture, and data imputation for intelligent decision-making systems. By addressing societal challenges with AI, he continues to drive forward impactful and sustainable technological solutions.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Looking ahead, Mr. Bikram envisions integrating interdisciplinary AI methodologies with climate science, transportation modeling, and remote sensing technologies. His role as a reviewer for esteemed journals like Knowledge-Based Systems, Neurocomputing, Applied Intelligence, and IEEE Transactions on Intelligent Vehicles marks him as a thought leader shaping future research directions.

He is also preparing to become an IEEE Member (December 2025), aligning with a global network of innovators.

 ✅CONCLUSION

With a powerful combination of technical expertise, research depth, and real-world problem-solving focus, Mr. Pritam Bikram stands as an emerging scholar in the Artificial Intelligence community. His contributions are expected to influence diverse fields from urban mobility to climate-resilient agriculture, leaving a lasting legacy.

🔬NOTABLE PUBLICATION:

Effective message-passing scheme and aggregation technique embedded in graph-based encoder-decoder learning framework for trajectory prediction
Author(s): Pritam Bikram, Shubhajyoti Das, Arindam Biswas
Journal: Expert Systems with Applications
Year: 2025

Multilayer optimized deep learning model to analyze spectral indices for predicting the condition of rice blast disease
Author(s): Shubhajyoti Das, Pritam Bikram, Arindam Biswas, Vimalkumar C., Parimal Sinha
Journal: Remote Sensing Applications: Society and Environment
Year: 2025

Dynamic attention aggregated missing spatial–temporal data imputation for traffic speed prediction
Author(s): Pritam Bikram, Shubhajyoti Das, Arindam Biswas
Journal: Neurocomputing
Year: 2024

Attentive graph structure learning embedded in deep spatial-temporal graph neural network for traffic forecasting
Author(s): Pritam Bikram, Shubhajyoti Das, Arindam Biswas
Journal: Applied Intelligence
Year: 2024

V Sidda Reddy | Computer Science | Best Researcher Award

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Dr. V Sidda Reddy | Computer Science | Best Researcher Award

Stanley College of Engineering and Technology for Women, India

Author Profile

GOOGLE SCHOLAR

🎓 EARLY ACADEMIC PURSUITS

Dr. V. Sidda Reddy laid a strong educational foundation with a B.E. in Computer Science & Engineering from Bangalore University in 1995. Further deepening his expertise, he completed an M.Tech in Information Technology (2003) with distinction from Jawaharlal Nehru Technological University Hyderabad (JNTUH). Driven by a desire for innovation in data science, he pursued a Ph.D. in Computer Science & Engineering at JNTUH, which he was awarded in 2020 for his research titled “New Approaches for Mining Data Streams.”

🏢 PROFESSIONAL ENDEAVORS

With over 25 years of experience—20 in academics and 5.5 years in the software industry—Dr. Reddy has held pivotal roles such as Professor, HOD, and Associate Professor at reputed institutions including:

  • Teegala Krishna Reddy Engineering College

  • CVR College of Engineering, Hyderabad

  • Sai Tirumala Engineering College, Narasaraopet

  • GMR Institute of Technology, Srikakulam

His industry experience includes serving as a Software Engineer at Reliance Systems Pvt. Ltd, Bangalore (1996–2001), contributing to software design and development.

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN COMPUTER SCIENCE

Dr. Reddy’s core research interests include:

  • Data Stream Mining

  • Frequent Itemset Mining

  • Machine Learning

  • Deep Learning

  • Human Action Recognition

His Ph.D. and publications emphasize innovative frameworks for closed frequent itemset mining, context-aware windowing, and real-time data analysis. He has contributed to algorithms, tree-based classification models, and CNN-based recognition systems, paving the way for real-world applications such as driver drowsiness detection and ATM security systems.

🏅 ACADEMIC CITATIONS, ACCOLADES AND RECOGNITION

Dr. Reddy’s contributions are recognized through:

  • Multiple Scopus and Web of Science indexed journal publications

  • Over 12+ peer-reviewed research papers

  • Best Teacher Award (2010) from Lions Club International

  • Prestigious certifications from Coursera, Brainbench, Microsoft, and DataCamp

He is frequently cited for his work on stream mining algorithms and hybrid models in machine learning.

🌍 IMPACT AND INFLUENCE

Dr. Reddy has mentored numerous students, organized technical paper presentations, faculty development programs, and industry-collaborated workshops on AI, cloud computing, Python, and mobile application development. His efforts extended to social impact by organizing blood donation camps in collaboration with Red Cross India and Lions Club.

He actively contributes to academic societies such as Computer Society of India (CSI) and is a member of the International Association of Engineers (IAENG).

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Dr. Reddy’s legacy lies in fostering an ecosystem of applied learning, cutting-edge research, and social responsibility. He continues to inspire the next generation through mentorship, active participation in technical societies, and curriculum development in AI and data mining. Future goals include:

  • Developing AI-driven educational platforms

  • Expanding data stream mining research

  • Collaborating on international research projects

 ✅CONCLUSION

Dr. V. Sidda Reddy stands out as a dedicated educator, innovator, and researcher. His journey reflects a commitment to excellence, technological progress, and societal betterment. With a balanced blend of academic rigor, industrial experience, and social service, he continues to enrich the field of Computer Science & Engineering with meaningful contributions and transformative leadership.

🔬NOTABLE PUBLICATION:

Data Mining Techniques for Data Streams Mining
Authors: V.S. Reddy, T.V. Rao, A. Govardhan
Journal: Review of Computer Engineering Studies, Vol. 4(1), pp. 31–35
Year: 2017

Mining Frequent Itemsets (MFI) Over Data Streams: Variable Window Size (VWS) By Context Variation Analysis (CVA) Of The Streaming Transactions
Authors: V.S. Reddy, D.T.V. Rao, D.A. Govardhan
Journal: arXiv preprint arXiv:1408.3175
Year: 2014

Smart Door Lock to Avoid Robberies in ATM
Authors: V.S. Reddy, S. Kalli, H. Gebregziabher, B.R. Babu
Journal: Journal of Physics: Conference Series, Vol. 1964(4), 042032
Year: 2021

CASW: Context Aware Sliding Window for Frequent Itemset Mining Over Data Streams
Authors: V.S. Reddy, T.V. Rao, A. Govardhan
Journal: International Journal of Computational Intelligence Research, Vol. 13(2), pp. 183–196
Year: 2017

Knowledge Discovery from Static Datasets to Evolving Data Streams and Challenges
Authors: V.S. Reddy, M. Narendra, K. Helini
Journal: International Journal of Computer Applications, Vol. 87(15)
Year: 2014

A Triple Band Square Shape Multi-slot Defective Ground Structure Patch Antenna for C-, X-, and Ku-band Applications
Authors: S. Kalli, S. Aouthu, Y. Srinivas, V.S. Reddy, R. Palla, M. Valathuru, N. Prasad
Journal: Sumy State University
Year: 2025

Deepika | Machine Learning | Best Researcher Award

Published-on by Indian Scientist

Ms. Deepika | Machine Learning | Best Researcher Award

The NorthCap University, India

Author Profile

ORCID

🎓 EARLY ACADEMIC PURSUITS

Ms. Deepika has consistently demonstrated academic excellence throughout her education. She holds a B.Tech in Computer Science Engineering from YMCA Institute of Engineering, where she ranked among the top three students in her batch. She went on to complete her M.Tech in Computer Science from Lingaya’s University, securing the second rank. She is currently pursuing a Ph.D. in Computer Science & Engineering at The NorthCap University, specializing in medical imaging and deep learning

🏢 PROFESSIONAL ENDEAVORS

Ms. Deepika brings over 5 years of corporate R&D experience from Ericsson Global India, where she worked as a Senior Solution Integrator. Her projects focused on telecom fault management, Netcool-based automation, and alarm handling systems. Her contributions in automating trouble ticketing and fault detection workflows earned her the Power Award and performance-based cash rewards. She displayed leadership in system integration, scripting, testing, and production support, translating technical expertise into tangible organizational benefits.

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN MACHINE LEARNING

Ms. Deepika’s doctoral research lies at the convergence of machine learning, deep learning, and functional brain imaging for the diagnosis of neuropsychiatric disorders, particularly ADHD. Her contributions include:

  • Kolmogorov-Arnold Network (KAN) for parameter-efficient ADHD diagnosis

  • Hybrid metaheuristic–fuzzy logic systems for multi-disease classification

  • Multimodal neuroimaging frameworks utilizing fMRI, EEG, and structural MRI

  • Explainable AI (XAI) methods promoting interpretability and trust in medical AI

She is well-versed in cutting-edge tools like TensorFlow, PyTorch, Nilearn, FSL, SPM, and leverages advanced statistical and optimization techniques for robust model development.

🏅 ACADEMIC CITATIONS, ACCOLADES AND RECOGNITION

  • UGC-NET Qualified (Computer Science, 2018)

  • HTET Qualified (2016)

  • Awarded UGC Research Fellowship

  • Best Paper Awards at national and international conferences

  • Top Rank Holder in both undergraduate and postgraduate programs

  • Power Award and cash incentives from Ericsson for outstanding contributions

🌍 IMPACT AND INFLUENCE

Her research contributes significantly to the field of AI-driven healthcare diagnostics, focusing on low-parameter models and cross-platform compatibility for deployment in resource-constrained environments. Her work emphasizes biomarker discovery, data fusion, and interdisciplinary collaboration between AI and clinical neuroscience. She promotes standardization and reproducibility in neuroimaging-based machine learning, ensuring her models are accessible and implementable in real-world clinical settings.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Ms. Deepika aims to develop real-time, interpretable diagnostic tools integrating multi-modal brain data with scalable AI architectures. Her future research envisions:

  • Cross-disorder AI frameworks (e.g., ADHD, autism, depression)

  • Deployment-ready solutions for rural healthcare centers

  • Contribution to open-access neuroimaging repositories

  • Ethical and explainable AI models aligned with global health guidelines

She is committed to mentorship, capacity-building in AI for healthcare, and inclusive research practices.

 ✅CONCLUSION

Ms. Deepika represents a powerful blend of academic brilliance, industrial innovation, and societal impact. Her work bridges gaps between machine learning and medicine, offering transformative solutions for mental health diagnostics. With a clear vision and deep technical foundation, she is well-positioned to become a leading figure in neuro-AI research.

🔬NOTABLE PUBLICATION:

A Hybrid Metaheuristic–Fuzzy Logic-Based Framework for Robust ADHD and Multi-Disease Classification
Author(s): Deepika; Arora, S.; Sharma, M.
Journal: Iran Journal of Computer Science
Year: 2025

Multimodality Model Investigating the Impact of Brain Atlases, Connectivity Measures, and Dimensionality Reduction Techniques on Attention Deficit Hyperactivity Disorder Diagnosis Using Resting State Functional Connectivity
Author(s): Deepika; Sharma, M.; Arora, S.
Journal: Journal of Medical Imaging
Year: 2024

Machine Learning Advances in Diagnosing Attention Deficit and Hyperactivity Disorder
Author(s): Deepika; Sharma, M.; Arora, S.
Journal: 14th International Conference on Advances in Computing, Control, and Telecommunication Technologies (ACT 2023)
Year: 2023

Neuroimaging Based Automated Diagnosis of Attention Deficit and Hyperactivity Disorder Using Machine Learning Techniques
Author(s): Deepika
Journal: Hinweis Science and Engineering
Year: 2023