Sunil Datt Sharma | Computer Science | Best Researcher Award

Posted on by Indian Scientist

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

Posted on by Indian Scientist

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

Posted on by Indian Scientist

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

Posted on by Indian Scientist

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

Posted on by Indian Scientist

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

Posted on by Indian Scientist

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

Posted 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

Posted 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

Posted 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