Rajib Kumar Jha | Machine Learning | Research Excellence Award

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Dr. Rajib Kumar Jha | Machine Learning | Research Excellence Award

IIT Patna, India

Author Profile

Early Academic Pursuits 📚

Rajib Kumar Jha’s academic journey is marked by a strong foundation in science and engineering, beginning with his secondary education at M. L. Academy, Bihar, where he excelled in core subjects like Science, Mathematics, Hindi, and English, scoring an impressive 76% in 1992. His passion for engineering continued through his higher secondary studies at C.M. Sc. College, Bihar, where he obtained 69% in 1993. Driven to excel in the field, he pursued his undergraduate degree in Electronics and Communication Engineering (ECE) at UIET Kanpur under CSJM University, graduating in 2001 with a commendable CPI of 8.4/10. His commitment to advancing in his field took him to IIT Kharagpur, where he earned both his M.Tech (2003) with a CPI of 7.6/10 and his Ph.D. (2010) with a specialization in Digital Image Processing. This period marked a significant phase of growth, as he deepened his understanding of Digital Image & Signal Processing, Medical Imaging, Machine Learning, and Pattern Recognition.

Professional Endeavors 💼

Dr. Rajib Kumar Jha’s professional career reflects a steady progression in academia, combining teaching with intensive research. Starting in 2006, he joined IIITDM Jabalpur as an Assistant Professor, dedicating over six years to teaching and research until December 2012. He then moved to IIT Ropar, where he continued his teaching journey until May 2013. His skills and expertise led him to IIT Patna, initially as an Assistant Professor from 2013 to 2018, after which he was promoted to Associate Professor. At IIT Patna, Dr. Jha has been actively involved in research, development, and mentorship, making substantial contributions to the field and to the growth of his students.

Contributions and Research Focus 🔬

Dr. Jha’s research interests focus on the field of Digital Image & Signal Processing, with an emphasis on Medical Imaging, Machine Learning, and Pattern Recognition. His work in Digital Image Processing, initiated during his Ph.D. at IIT Kharagpur, has extended to pioneering research in Medical Imaging. By integrating Machine Learning and advanced pattern recognition techniques, he has made advancements in data interpretation and diagnostics that could significantly improve medical imaging accuracy. His research output has contributed to enhancing signal processing methods, which are essential for both academic and practical applications. Through this specialized focus, he has enriched both his students and the academic community, providing insights into cutting-edge developments in image and signal processing.

Accolades and Recognition 🏆

Throughout his career, Dr. Jha has earned recognition for his academic rigor and dedication. His academic records and early success led to opportunities in prestigious institutions, starting with his Ph.D. and M.Tech from IIT Kharagpur and culminating in his role as an Associate Professor at IIT Patna. His contributions to research and education have been recognized at various levels, with honors reflecting his commitment to excellence in the engineering discipline. His significant contributions to medical imaging and digital signal processing have attracted appreciation from his peers and set a benchmark for upcoming researchers.

Impact and Influence 🌍

Dr. Rajib Kumar Jha’s influence extends beyond his research; as a teacher and mentor, he has guided numerous students through their academic and research journeys. His tenure at institutions like IIITDM Jabalpur, IIT Ropar, and IIT Patna has allowed him to impact a diverse group of students, encouraging them to think innovatively and apply their knowledge to real-world challenges. His focus on digital signal processing has also contributed to advancements in medical technology, benefiting practitioners and patients alike. Dr. Jha’s collaborations and guidance have helped shape the careers of future engineers and researchers, many of whom now contribute to the field independently.

Legacy and Future Contributions 🌟

As he continues his journey at IIT Patna, Dr. Jha is poised to leave a lasting legacy, both as an academic and a researcher. His current research efforts hold potential for groundbreaking advancements in medical imaging and pattern recognition, particularly in healthcare applications within developing regions. Dr. Jha’s dedication to teaching and research ensures that his influence will extend well beyond his immediate academic environment, as his work is likely to inspire future innovations in signal processing, machine learning, and digital image processing. Embracing new technologies and methodologies, Dr. Jha is committed to enhancing the impact of engineering research and shaping a generation of engineers who are ready to tackle tomorrow’s challenges.

Citations

A total of 1187 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations         1187
  • h-index           103
  • i10-index        18

Notable Publications 

  • Title: Ensemble learning using Gompertz function for leukemia classification
    Authors: Abhishek, A., Deb, S.D., Jha, R.K., Sinha, R., Jha, K.
    Journal: Biomedical Signal Processing and Control
    Year: 2025.
  • Title: Segmentation of pectoral muscle from mammograms using U-Net having densely connected convolutional layers
    Authors: Deb, S.D., Jha, R.K.
    Journal: Multimedia Tools and Applications
    Year: 2024.
  • Title: Severity estimation of Coffee leaf disease using U-Net and pixel counting mechanism
    Authors: Deb, S.D., Kashyap, R., Abhishek, A., Jha, R.K.
    Journal: ACM International Conference Proceeding Series
    Year: 2024.
  • Title: Breast cancer diagnosis using modified Xception and stacked generalization ensemble classifier
    Authors: Deb, S.D., Rahman, A., Jha, R.K.
    Journal: Research on Biomedical Engineering
    Year: 2023.
  • Title: Breast UltraSound Image classification using fuzzy-rank-based ensemble network
    Authors: Deb, S.D., Jha, R.K.
    Journal: Biomedical Signal Processing and Control
    Year: 2023.

Bhuvaneswari.S | Deep learning | Best Researcher Award

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Dr. Bhuvaneswari.S | Deep learning | Best Researcher Award

SASTRA Deemed University- India

Author Profile

Early Academic Pursuits

Dr. S. Bhuvaneswari embarked on her academic journey with a passion for computer science and engineering, setting a solid foundation for her future endeavors. She pursued her doctoral studies at SASTRA Deemed University, Thanjavur, India, where she focused on developing innovative solutions to real-world challenges. Her thesis, titled “An Intelligent Data-driven Prediction Model for Sustainable Cropping System using Deep Learning Techniques,” reflects her dedication to leveraging technology for agricultural sustainability. This early focus on deep learning techniques and precision agriculture positioned her as a thought leader in the intersection of technology and agriculture. 🌾

Professional Endeavors

Dr. Bhuvaneswari’s professional journey is marked by diverse roles that encompass both industry and academia. She began her career as a Quality Engineering Transformation (QET) Engineer at TATA Consultancy Services (TCS) in Chennai from June 2018 to January 2020. During her tenure at TCS, she was part of the Center of Excellence team in performance testing, where she honed her skills in quality assurance and software engineering.In January 2020, she transitioned to academia as a Junior Research Fellow at the School of Computing, SASTRA Deemed University, supported by the Indian Council of Social Science Research (ICSSR) under the IMPRESS Scheme. She later served as a Teaching Assistant and then a Research Assistant, contributing significantly to various projects until February 2024, when she was appointed as an Assistant Professor Research in the Department of Computer Science and Engineering at SASTRA Deemed University. Her journey reflects a commitment to both teaching and research, combining practical experience with academic rigor. 📚

Contributions and Research Focus

Dr. Bhuvaneswari’s research interests primarily revolve around Deep Learning Techniques, Recommender Systems, and Precision Agriculture. Her work emphasizes the development of intelligent systems that can analyze complex data sets and provide actionable insights for sustainable agricultural practices. One of her notable projects, “Design and Development of Decision-making Tool for Crop Selection in Precision Agriculture,” aims to aid farmers in making informed decisions, thereby improving crop yields and resource management. Additionally, her investigation into prediction models for physical activity recommender systems highlights her versatility and ability to apply her expertise across various domains.Her proficiency in programming languages like Java and Python, combined with her experience in Computer Vision and Recommender Systems, positions her as a valuable asset in the fields of data science and machine learning. 🖥️

Accolades and Recognition

Throughout her career, Dr. Bhuvaneswari has received recognition for her contributions to academia and research. Her work has been funded by reputable organizations, showcasing her ability to secure grants and support for her innovative projects. She has participated in numerous conferences, presenting her research findings and engaging with other experts in her field. This active involvement not only enhances her professional profile but also contributes to the advancement of knowledge in her areas of expertise.

Impact and Influence

Dr. Bhuvaneswari’s influence extends beyond her immediate academic environment. By integrating advanced computational techniques into agriculture, she addresses critical issues related to food security and sustainable farming practices. Her research empowers farmers with data-driven insights, helping them optimize their operations and adapt to changing environmental conditions. Through her teaching, she inspires the next generation of computer scientists, instilling in them a passion for innovation and problem-solving. 🌍

Legacy and Future Contributions

As Dr. Bhuvaneswari continues her journey at SASTRA Deemed University, her legacy is already taking shape through her impactful research and dedication to education. She envisions expanding her work in deep learning and precision agriculture, potentially collaborating with industry partners to implement her models in real-world agricultural settings. Her commitment to developing sustainable solutions is likely to inspire future researchers and practitioners in the field.In conclusion, Dr. S. Bhuvaneswari exemplifies the integration of technology and agriculture, with a strong foundation in research and teaching. Her contributions are paving the way for a more sustainable future, making her a prominent figure in her field. For inquiries, she can be reached at her email: sbhuvi95@gmail.com. With a promising trajectory ahead, Dr. Bhuvaneswari is poised to make significant advancements that will benefit both academia and the agricultural sector. 🌟

Citations

A total of 110 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations         110
  • h-index           16
  • i10-index        5

Notable Publications

  • Bhuvaneswari, S. & Subramaniyaswamy, V.
    “D2CNN: Double-staged Deep CNN for Stress Identification and Classification in Cropping System”
    Agricultural Systems, (2024), Vol. 216, 103886 [IF: 6.6]
  • Bhuvaneswari, S., Jagadeesh, M. & Subramaniyaswamy, V.
    “Multi-label Classification for Acoustic Bird Species Detection using Transfer Learning Approach”
    Ecological Informatics, (2024), Vol. 80, pp. 1-12, 102471 [IF: 5.1]
  • Bhuvaneswari, S., Saravanan, P. & Subramaniyaswamy, V.
    “Feature Fusion based Deep Neural Collaborative Filtering Model for Fertilizer Prediction”
    Expert Systems with Applications, (2023), Vol. 216, pp. 1-12 [IF: 8.665]
  • Bhuvaneswari, S., Saravanan, P. & Subramaniyaswamy, V.
    “Meta Learning-based Dynamic Ensemble Model for Crop Selection”
    Applied Artificial Intelligence, (2022), Vol. 36, pp. 1-36 [IF: 2.777]
  • Bhuvaneswari, S., Saravanan, P., Kotecha, K., Kumar, V. & Subramaniyaswamy, V.
    “IoT Driven Artificial Intelligence Technique for Fertilizer Recommendation Model”
    IEEE Consumer Electronics Magazine, (2022).

Aqil K H | Artificial intelligence | Best Researcher Award

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Mr. Aqil K H | Artificial intelligence | Best Researcher Award

Indian institute of technology Madras-India

Author Profile

Early Academic Pursuits 📚

Dr. Aqil K H’s passion for electrical engineering and innovation began at a young age in Kerala, India. His academic journey started at the Model Technical Higher Secondary School in Ernakulam, where he excelled in the state board exams, securing an impressive 98.33% in 2012 for his X standard and 95.58% in 2014 for his XII standard. These early achievements underscored his commitment to learning and laid the foundation for his future success. After completing his pre-university education, he pursued a Bachelor of Technology (B.Tech) degree in Electronics and Communication Engineering (ECE) from the prestigious Government Model Engineering College in Ernakulam, Kerala, where he graduated with a commendable CGPA of 8.36 in 2018. His strong academic foundation and technical skills positioned him for higher studies and research.

Professional Endeavors 🌍

Dr. Aqil’s career began as a Software Engineer at Kimball Electronics (India) Pvt. Ltd., where he contributed to various projects within the image processing domain. His role involved the development of computer vision frameworks and algorithm optimization for improving image quality. Working closely with clients in Vietnam, he demonstrated his adaptability and ability to manage real-world challenges, marking his early years of professional growth.In 2020, Dr. Aqil transitioned into research, joining the Healthcare Technology Innovation Centre (HTIC) at IIT Madras, one of the country’s leading research institutes. As a Research Associate, he worked on several impactful projects. One notable project was the X-ray angiography image enhancement initiative, where he collaborated with industry partners to enhance imaging technology. His work on precision medicine for chronic diseases, particularly Alzheimer’s, further expanded his contributions to healthcare innovations. This multi-modal time series forecasting system, aimed at predicting disease progression, utilized cutting-edge techniques like graph representation learning.Additionally, Dr. Aqil became associated with the Sudha Gopalakrishnan BRAIN Centre at IIT-M, where he contributed to groundbreaking research in fetal brain MRI segmentation and histopathology image segmentation. These projects highlighted his ability to apply machine learning and image processing techniques to critical medical fields.

Contributions and Research Focus 🔬

Dr. Aqil’s research primarily focuses on deep learning, machine learning, and image processing, with a particular interest in healthcare applications. His expertise lies in creating sophisticated algorithms and frameworks for medical imaging, including MRI segmentation, dental panoramic X-ray analysis, and time-series forecasting for clinical outcomes.

Some of his key projects include:

  • Learning to Atlas Register for Rapid Segmentation of Brain Structures in Fetal MRI: This innovative project addressed challenges in brain segmentation, focusing on multilabel atlas-based segmentation. By using the VoxelMorph’s CNN architecture, Dr. Aqil formulated registration as a deformation field that aligned neurotypical brain images for better diagnosis.
  • Time Series Forecasting of Clinical Factors and Outcomes: This project was geared toward Alzheimer’s disease prediction, using a graph representation learning approach. Dr. Aqil proposed a novel framework that operated on dynamic graphs, translating medical data into actionable insights for clinicians.
  • Accelerated MRI with Untrained Neural Networks: Addressing the problem of MRI reconstruction, this project leveraged untrained neural networks to solve issues related to undersampling, using innovative techniques like ConvDecoder.

His work on dental panoramic X-ray segmentation utilized deep learning techniques to enable the early diagnosis of dental disorders. Dr. Aqil’s fascination with machine learning also extended into areas of face recognition technology, where he developed a door access control system based on K-L transform for face recognition.

Accolades and Recognition 🏅

Throughout his career, Dr. Aqil has earned widespread recognition for his contributions to both research and industry. His academic achievements, such as a CGPA of 9.00 in his Master’s program at IIT-Madras, reflect his dedication to excellence. His research endeavors at IIT-Madras’s HTIC and BRAIN Centre have led to publications that have earned citations, indicating his growing influence in the field of medical image processing and machine learning.

Impact and Influence 🌟

Dr. Aqil’s research has had a profound impact on the field of medical imaging. His work on X-ray angiography and fetal brain MRI segmentation has improved diagnostic capabilities, helping doctors make more informed decisions. The time series forecasting systems he developed for Alzheimer’s disease prediction are poised to revolutionize how chronic diseases are managed and treated. His contributions to precision medicine are critical in an era where personalized treatment plans are becoming the norm.His research contributions extend beyond academic circles, as his image processing frameworks are being implemented in real-world medical settings, influencing the future of healthcare technology.

Legacy and Future Contributions 🚀

Dr. Aqil K H is set to leave a lasting legacy in the intersection of electrical engineering and healthcare technology. His groundbreaking work in image processing and deep learning promises to continue shaping the future of medical diagnostics. As a researcher, his contributions to accelerated MRI reconstruction and graph-based time-series forecasting have set new standards in medical imaging research. His passion for education, research, and technological advancement ensures that his work will inspire future engineers and researchers.In the coming years, Dr. Aqil aims to expand his research to include multi-modal medical data integration and AI-driven healthcare solutions, further pushing the boundaries of how technology can improve human health. His dedication to innovation, collaboration, and continuous learning will undoubtedly leave an enduring mark on the fields of deep learning and medical imaging.

Notable Publications 

  • Predictive Modeling of Alzheimer’s Disease Progression: Integrating Temporal Clinical Factors and Outcomes in Time Series Forecasting
    Authors: Aqil, K.H., Dumpuri, P., Ram, K., Sivaprakasam, M.
    Journal: Intelligence-Based Medicine, 2024.
  • Confounding Factors Mitigation in Brain Age Prediction Using MRI with Deformation Fields
    Authors: Aqil, K.H., Kulkarni, T., Jayakumar, J., Ram, K., Sivaprakasam, M.
    Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2023.
  • Learning to Atlas Register for Rapid Segmentation of Brain Structures in Fetal MRI
    Authors: Kulkarni, T., Aqil, K.H., Jayakumar, J., Ram, K., Sivaprakasam, M.
    Journal: Progress in Biomedical Optics and Imaging – Proceedings of SPIE, 2023.

Bhavna Bajpai | Database and Datamining | Women Researcher Award

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Dr. Bhavna Bajpai - Database and Datamining - Women Researcher Award 🏆

Dr. C. V. Raman University, Khandwa - India

Professional Profiles

Early Academic Pursuits

She began her academic journey with a Bachelor of Science in Computer Science from Poonam Chand Gupta Vocational College, Khandwa, affiliated with Devi Ahilya Govt. University, Indore (M.P.). She further pursued a Post Graduate Diploma in Computer Application (PGDCA) from the same institution, enhancing her skills in computer science applications. Her passion for learning led her to obtain a Master of Science in Information Technology from Guru Ghasidas University, Bilaspur (C.G.), followed by an M.Phil in Computer Science from Global Open University, Nagaland, and eventually a Ph.D. in Computer Science and Applications from AISECT University, Bhopal (M.P.).

Professional Endeavors

With over 18 years of experience in Information Technology and Computer Science Application departments, she has held various academic positions, starting as an Assistant Professor at IPS Academy, Indore, and later at Shri Dadaji Institute of Technology & Science, Khandwa, where she served for more than a decade. Currently, she holds the position of Associate Professor at Dr. C.V. Raman University, Khandwa, where she also serves as the Dean and IQAC Coordinator. Throughout her career, she has actively engaged in continued learning through conferences and professional research, aiming to stay updated with the latest advancements in her field.

Contributions and Research Focus in Database and Datamining

Her research interests primarily revolve around database management systems and data mining. Her expertise spans areas such as data analysis, machine learning, and pattern recognition. Through her scholarly contributions, Dr. Bajpai has explored innovative approaches to data management and mining, leveraging her insights to address real-world challenges. Her research has focused on enhancing the efficiency and effectiveness of database systems, optimizing data analysis techniques, and developing intelligent algorithms for pattern recognition and machine learning applications. Database and data mining are two interconnected fields crucial in the era of big data. A database is a structured collection of data organized for efficient retrieval, storage, and management.

Accolades and Recognition 

Her dedication and contributions to the field of database and data mining have earned her recognition and accolades. She has been acknowledged for her scholarly achievements through various platforms, including professional awards, citations, and academic affiliations. Her commitment to academic excellence and research innovation has been celebrated within the academic community, reflecting her significant impact on the field.

Impact and Influence

Her work has made a tangible impact on both academia and industry. Her research findings have contributed to advancements in database management systems, data analysis techniques, and machine learning algorithms. By bridging the gap between theory and practice, Dr. Bajpai has facilitated the adoption of data-driven strategies in diverse domains, empowering organizations to harness the power of data for informed decision-making and strategic planning.

Legacy and Future Contributions

As a dedicated educator and researcher, she continues to inspire and mentor future generations of scholars. Her legacy is defined by her passion for learning, her commitment to excellence, and her unwavering pursuit of knowledge. Moving forward, she aims to further her research endeavors, exploring new frontiers in database management systems and data mining. With her expertise and leadership, she remains poised to make significant contributions to the advancement of her field and the empowerment of aspiring researchers in the years to come.

Notable Publications

Nishi Parikh | Machine Learning for Material Science | Best Researcher Award

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Dr. Nishi Parikh - Machine Learning for Material Science - Best Researcher Award 🏆

Ola Battery Innovation Centre - India

Professional Profiles

Early Academic Pursuits

Her academic journey began with a Bachelor of Science in Chemistry from St. Xavier’s College, Ahmedabad, Gujarat, where she excelled academically and was awarded a Gold Medal. Her passion for chemistry led her to pursue a Master of Science in Organic Chemistry from Gujarat University, where she achieved a remarkable CGPA of 8.10 and received a Silver Medal. Subsequently, she embarked on her doctoral journey, earning a Ph.D. in Science from the Department of Chemistry at Pandit Deendayal Energy University, Gujarat. Her doctoral research focused on "Redefining the crystallization and characterization of halide perovskite by Machine Learning," showcasing her early engagement with machine learning techniques in material science.

Professional Endeavors

Her professional endeavors reflect her dedication to advancing the field of material science through interdisciplinary research and collaboration. She has contributed significantly to the Ola Battery Innovation Centre in Bangalore, India, leveraging her expertise in machine learning and materials science to drive innovation in battery technology. Her research endeavors have been supported by prestigious fellowships, including the PBEEE Merit Fellowship for research stay at INRS, Quebec, and the Swiss Government Excellence Research Fellowship at ZHAW, Zurich.

Contributions and Research Focus in Machine Learning for Material Science

Her research focuses on the intersection of machine learning and material science, with a particular emphasis on material property prediction, computational materials science, and data-driven materials design. Her doctoral research on halide perovskite crystallization and characterization exemplifies her pioneering work in applying machine learning techniques to address complex challenges in materials research. By harnessing the power of machine learning algorithms, Dr. Parikh aims to accelerate materials discovery processes, optimize material properties, and facilitate the design of novel materials for various applications.

Accolades and Recognition

Her contributions to material science and machine learning have been widely recognized through numerous awards and achievements. She has been awarded prestigious fellowships, including the PBEEE Merit Fellowship and the Swiss Government Excellence Research Fellowship, for her outstanding research contributions. Additionally, her research presentations at international conferences and symposiums have earned her accolades, including the Best Poster Award at the "3rd Gen PV in the developing world" conference organized by Newcastle University, UK.

Impact and Influence

Her research has made a significant impact on the field of material science and machine learning, advancing our understanding of materials behavior and enabling the design of innovative materials with tailored properties. Her interdisciplinary approach and collaborative efforts have led to advancements in battery technology, renewable energy, and sustainable materials. Through her research, Dr. Parikh continues to inspire future generations of scientists and engineers, driving innovation and progress in the field of material science.

Legacy and Future Contributions

As she continues her academic and research endeavors, her legacy is defined by her commitment to excellence, innovation, and interdisciplinary collaboration in material science and machine learning. Her future contributions hold the promise of further advancing our understanding of materials behavior, accelerating materials discovery processes, and revolutionizing various industries through the development of advanced materials with tailored properties. Dr. Parikh's pioneering research serves as a catalyst for transformative change in material science and machine learning, shaping the future of technology and sustainability.

Citations

  • Citations               328
  • h-index                  11
  • i10-index               11

Notable Publications