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

Milind Cherukuri | Artificial Intelligence | Young Researcher Award

Published-on by Indian Scientist

Mr. Milind Cherukuri | Artificial Intelligence | Young Researcher Award

University of North Texas, India

Author Profile

ORCID

GOOGLE SCHOLAR

🎓 EARLY ACADEMIC PURSUITS

Milind Cherukuri’s academic journey began with a Bachelor’s in Computer Science from SRM University, Chennai (2015–2019), where he built a strong foundation in software engineering and algorithmic problem-solving. His pursuit of advanced knowledge led him to the University of North Texas, Dallas, where he completed his Master’s in Computer Science (2021–2022) with a focus on artificial intelligence, machine learning, and data systems.

🏢 PROFESSIONAL ENDEAVORS

Milind’s professional trajectory spans a blend of engineering rigor, AI research, and enterprise system design:

  • Caris Life Sciences (2025–Present)
    Role: Salesforce Business Analyst & Administrator
    Spearheading automation and optimization of clinical and research workflows, Milind integrates complex data systems and aligns AI tools with healthcare outcomes.

  • Amazon (2022–2024)
    Role: Software Engineer
    Engineered scalable microservices, improved customer personalization using AI, and contributed to global backend infrastructure, earning accolades for reliability and innovation.

  • Infor (2019–2021)
    Role: Software Engineer
    Led backend automation initiatives and research into NLP applications, with early contributions in recommendation systems and sentiment analysis pipelines.

📚 CONTRIBUTIONS AND RESEARCH FOCUS ON ARTIFICIAL INTELLIGENCE

Milind’s AI research is grounded in both theoretical depth and applied innovation. His key research themes include:

  • Sentiment Analysis & Emotion Modeling

  • Safe and Responsible Development of Large Language Models (LLMs)

  • Image Segmentation and Validation Tools for Web Structures

  • Prompt Engineering for LLM Optimization

He has published five peer-reviewed research papers, presented at premier conferences such as IEEE AI Summit and EEET 2024, and contributed tools like WebChecker, which enhances web development quality control.

🏅 ACADEMIC CITES, ACCOLADES AND RECOGNITION

  • Elevated to Senior Member of IEEE (2025)

  • Peer reviewer for leading journals, including JOBARI

  • Citations across platforms including IEEE Xplore, ResearchGate, and arXiv

  • Recognized internally by Amazon and Caris Life Sciences for exemplary technical contributions

  • Invited speaker at international AI research forums

🌍 IMPACT AND INFLUENCE

Milind’s work bridges AI with healthcare, e-commerce, and cloud ecosystems, showing measurable improvements:

  • 30% efficiency gain in Salesforce workflows at Caris Life Sciences

  • Millions of fault-tolerant requests/day enabled by backend systems at Amazon

  • Influenced global discussions on AI safety through groundbreaking presentations

He continues to influence both industry and academia through tool development, peer-review contributions, and community engagement.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Milind aims to build a safer, smarter, and ethically grounded AI ecosystem. His future research plans focus on:

  • Explainable AI in healthcare diagnostics

  • Open-source tools for LLM safety benchmarking

  • Sustainable AI development aligning with ESG goals

He envisions fostering innovation at the crossroads of healthcare, AI, and policy, mentoring the next generation of AI practitioners and building intelligent systems that serve humanity.

 ✅CONCLUSION

Mr. Milind Cherukuri stands out as a technologist, researcher, and thought leader, bridging cutting-edge AI with practical impact. With a track record of academic brilliance, engineering excellence, and ethical AI advocacy, he continues to leave a mark on research, innovation, and global digital transformation.

 🔬NOTABLE PUBLICATION:

Title: Comparing Image Segmentation Algorithms

Author: M. Cherukuri
Journal/Conference: 2024 IEEE 4th International Conference on Data Science and Computer Applications (ICDSCA)
Year: 2024

Title: Cost, Complexity, and Efficacy of Prompt Engineering Techniques for Large Language Models

Author: M. Cherukuri
Journal/Conference: International Journal on Science and Technology
Year: 2025

Title: WebChecker: A Versatile EVL Plugin for Validating HTML Pages with Bootstrap Frameworks

Author: M. Cherukuri
Journal/Conference: arXiv preprint arXiv:2502.07479
Year: 2025

Title: Advancing AI Safely: Frameworks and Strategies for the Development of GPT-5 and Beyond

Author: M. Cherukuri
Journal/Conference: ResearchGate Preprint
Year: 2025

Title: Exploring Multi-Dimensional Sentiment Analysis: A Study on Emotion Representation Structures and Prediction Models

Author: M. Cherukuri
Journal/Conference: REST Journal on Data Analytics and Artificial Intelligence
Volume: 3, Pages 55–76
Year: 2024

Monika Goyal | Machine learning | Best Researcher Award

Published-on by Indian Scientist

Dr. Monika Goyal | Machine learning | Best Researcher Award

Dayananda Sagar University- India

Author Profile

📚Early Academic Pursuits

Dr. Monika Goyal’s academic journey began with a strong foundation in Electronics and Communication Engineering. She completed her B.Tech in Electronics & Communication Engineering from Jaipur Engineering College & Research Center, Jaipur, with a commendable 78.6%. Her enthusiasm for learning led her to pursue an M.Tech in Electronics & Communication Engineering at Malviya National Institute of Technology (MNIT), Jaipur, where she excelled with a CGPA of 8.5/10. Her quest for deeper knowledge continued as she embarked on a Ph.D. journey at G.D. Goenka University, Gurgaon, specializing in Medical Image Processing, Machine Learning, and Deep Learning. During her doctoral studies, Dr. Goyal made significant contributions to her field, including publishing two SCI-indexed papers and four Scopus-indexed papers.

🌟Professional Endeavors

Dr. Monika Goyal’s professional career spans over a decade, characterized by her role as an Assistant Professor in various esteemed institutions. She currently serves at Dayanand Sagar University, Bangalore, a position she has held since 2022. Her previous roles include serving as an Assistant Professor at Poornima University, Jaipur, and WCTM, where she significantly impacted the Electronics & Communication and Computer Science departments. Her career also includes tenure at Genba Sopanrao Moze College of Engineering, Pune, Swami Keshvanand Institute of Technology, Jaipur, and the Institute of Computer and Finance Executive (ICFE) Jaipur. Dr. Goyal’s diverse experience in teaching and administration has made her a valuable asset in the engineering education sector.

🔬Contributions and Research Focus

Dr. Goyal’s research interests lie primarily in the domains of Medical Image Processing, Machine Learning, and Deep Learning. Her work includes pioneering methods for tumor detection and contrast enhancement in medical imaging. Notable publications include her paper on “Optimum Contrast Enhancement for Tumour Detection” in the International Journal of Imaging System and Technology (SCI Indexed) and her contribution to “Deep learning for enhanced brain Tumor Detection and classification” published in Results in Engineering (Q1 SCI Indexed Journal). Her research on contrast enhancement techniques, such as the use of Range Limited Weighted Histogram Equalization, has been instrumental in advancing medical image analysis. Additionally, Dr. Goyal’s work on AI and machine learning applications reflects her commitment to pushing the boundaries of technology in healthcare.

🏆Accolades and Recognition

Dr. Goyal’s exceptional contributions to engineering education and research have earned her numerous accolades and recognition. Her academic achievements, including securing top ranks during her B.Tech, M.Tech, and Ph.D., highlight her dedication and excellence. Her research has been recognized through several prestigious publications and conference presentations. Dr. Goyal’s participation in faculty development programs and conferences further underscores her commitment to continuous learning and professional growth.

🌍Impact and Influence

Dr. Goyal’s impact extends beyond academia into practical applications in medical imaging and machine learning. Her research has contributed to improved diagnostic tools and methods, enhancing the quality of healthcare services. Her involvement in mentoring engineering students and guiding their career decisions reflects her influence on the next generation of professionals. By publishing in renowned journals and participating in international conferences, Dr. Goyal has established herself as a thought leader in her field, influencing both academic and industry practices.

🚀Legacy and Future Contributions

Looking forward, Dr. Monika Goyal aims to continue her contributions to the fields of Medical Image Processing and Artificial Intelligence. Her ongoing research and commitment to academic excellence position her as a key figure in advancing these areas. With a focus on innovative solutions and technological advancements, Dr. Goyal is set to leave a lasting legacy in both the academic and professional realms. Her future work promises to further enhance healthcare technologies and contribute to the broader scientific community. Her dedication to learning, teaching, and research ensures that she will remain a significant force in engineering education and scientific research.

Citations

A total of 128 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations         128
  • h-index           10
  • i10-index         4

Notable Publications 

  • Deep Learning for Enhanced Brain Tumor Detection and Classification
    Authors: Agarwal, M., Rani, G., Kumar, A., Manikandan, R., Gandomi, A.H.
    Journal: Results in Engineering
    Year: 2024
  • Contrast Enhancement of Medical Images Using Otsu’s Double Threshold
    Authors: Vinay, R., Agarwal, M., Rani, G., Sinha, A.
    Journal: Lecture Notes in Networks and Systems
    Year: 2024
  • Potential Exoplanet Detection Using Feature Selection, Multilayer Perceptron, and Supervised Machine Learning
    Authors: Sairam, K., Agarwal, M., Sinha, A., Pradeep, K.
    Journal: Lecture Notes in Networks and Systems
    Year: 2024
  • Security, Privacy, Trust, and Other Issues in Industries 4.0
    Authors: Kumar, A., Ramachandran, M., Manjula, M., Pooja, Köse, U.
    Book Title: Topics in Artificial Intelligence Applied to Industry 4.0
    Year: 2024
  • Classification of Brain Tumor Disease with Transfer Learning Using Modified Pre-trained Deep Convolutional Neural Network
    Authors: Agarwal, M., Rohan, R., Nikhil, C., Yathish, M., Mohith, K.
    Journal: Lecture Notes in Networks and Systems
    Year: 2024