Akhil Kumar Das | Machine Learning | Innovation Award

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Mr. Akhil Kumar Das | Machine Learning | Innovation Award

Gour Mahavidyalaya- India

Author Profile

🎓Early Academic Pursuits

Dr. Akhil Kumar Das began his academic journey with a focus on Computer Science and Engineering, laying a strong foundation for his future career. He pursued a B.Tech in Computer Science from a renowned institution, followed by an M.Tech, demonstrating his commitment to advancing his knowledge and skills in the field. Dr. Das further enhanced his academic credentials by passing the GATE and UGC-NET exams, which are crucial for pursuing higher education and academic positions in India. His early academic pursuits set the stage for a distinguished career in both teaching and research.

💼Professional Endeavors

Dr. Das’s professional career began at IMPS College of Engineering & Technology, where he served as an Assistant Professor in the Department of Computer Science and Engineering from 2007 to 2014. During this period, he was responsible for imparting knowledge to undergraduate students and contributing to various academic activities. His tenure at Uttar Banga Krishi Viswavidyalaya in Cooch Behar from 2014 to 2016 further solidified his role as an educator. There, he continued to shape the future of students while also engaging in research and development.In 2016, Dr. Das transitioned to Gour Mahavidyalaya, where he continues to work as an Assistant Professor in Computer Science. His role involves not only teaching but also mentoring students and contributing to the academic environment through various initiatives.

🔬Contributions and Research Focus

Dr. Das has made significant contributions to the field of Computer Science through his extensive research. His research interests are primarily centered around machine learning, artificial intelligence, and their applications in healthcare, specifically breast cancer prediction. Noteworthy publications include:

  1. “Hybrid Case Based Reasoning System by Cost Sensitive Neural Network for Classification” – This paper explores innovative approaches in hybrid case-based reasoning systems, published in Soft Computing (2017).
  2. “Machine Learning Based Intelligent System for Breast Cancer Prediction (MLISBCP)” – This recent work focuses on advanced machine learning techniques for predicting breast cancer, published in Expert Systems with Applications (2024).
  3. “BCPUML: Breast Cancer Prediction Using Machine Learning Approach—A Performance Analysis” – A comprehensive analysis of machine learning methods for breast cancer prediction, featured in SN Computer Science (2023).
  4. “Comprehensible and Transparent Rule Extraction Using Neural Network” – This publication addresses methods for improving the transparency of neural network models, published in Multimedia Tools and Applications (2024).
  5. “Development of a Problem Solving Support for an Intelligent Tutoring System” – A significant contribution to educational technology, published in International Journal of Innovations & Advancement in Computer Science (2015).

Dr. Das’s research has been pivotal in advancing the application of machine learning techniques to critical areas such as healthcare, thereby contributing to the broader scientific community.

🏆Accolades and Recognition

Dr. Das has been recognized for his contributions to both teaching and research. His work has been published in several high-impact journals, reflecting his commitment to advancing knowledge in computer science. Notably, his research on breast cancer prediction has been well-received, and he has been invited to present his findings at various international conferences.

🌍Impact and Influence

Dr. Das’s research and professional work have significantly impacted the field of computer science. His innovative approaches to machine learning and artificial intelligence have not only advanced academic understanding but also provided practical solutions for pressing issues such as breast cancer prediction. His contributions extend beyond academia, influencing both industry practices and healthcare advancements. By integrating cutting-edge technology with real-world applications, Dr. Das has demonstrated a profound ability to address complex challenges and improve quality of life.

🌟Legacy and Future Contributions

Dr. Akhil Kumar Das’s legacy is marked by his dedication to advancing the field of computer science through both teaching and research. His work has set a benchmark for integrating machine learning with healthcare solutions, paving the way for future innovations. As he continues to work at Gour Mahavidyalaya, his focus remains on furthering research in machine learning and its applications. Dr. Das’s future contributions are expected to drive new advancements in technology, potentially transforming various domains, particularly in healthcare. His commitment to education and research will continue to inspire and shape the future of computer science.Dr. Das’s career is a testament to the impact of dedicated research and teaching in the advancement of technology and science. His contributions will undoubtedly influence future generations of students and researchers, reinforcing the vital role of academic excellence in driving progress and innovation.

Citations

A total of 40 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations         40
  • h-index           11
  • i10-index        3

Notable Publications 

  • Title: Hybrid Case Based Reasoning System by Cost Sensitive Neural Network for Classification
    Authors: Saroj Kr. Biswas, Manomita Chakraborty, Heisnam Rohen Singh, Debashree Devi, Biswajit Purkayastha, Akhil Kr. Das
    Journal: Soft Computing
    Volume: 21
    Year: 2017
  • Title: Machine Learning Based Intelligent System for Breast Cancer Prediction (MLISBCP)
    Authors: Akhil Kumar Das, Saroj Kr. Biswas, Ardhendu Mandal, Abhishek Bhattacharya, Suman Sanyal
    Journal: Expert Systems with Applications
    Year: 2024
  • Title: BCPUML: Breast Cancer Prediction Using Machine Learning Approach—A Performance Analysis
    Authors: Rahul Karmakar, Shibashis Chatterjee, Akhil Kumar Das, Ardhendu Mandal
    Journal: SN Computer Science
    Article ID: 377
    Year: 2023
  • Title: Comprehensible and Transparent Rule Extraction Using Neural Network
    Authors: Saroj Kr. Biswas, Abhishek Bhattacharya, Anirban Duttachoudhury, Manomita Chakraborty, Akhil Kumar Das
    Journal: Multimedia Tools and Applications
    Year: 2024
  • Title: Development of a Problem Solving Support for an Intelligent Tutoring System
    Authors: Akhil Kumar Das, Debasis Mandal
    Journal: International Journal of Innovations & Advancement in Computer Science
    Volume: 4
    Year: 2015.

Jayashree | Deep learning | Best Researcher Award

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Mrs. Jayashree - Deep learning - Best Researcher Award 🏆 

Nitte meenakshi Institute of technology - India

Professional Profiles

Early Academic Pursuits

She embarked on her academic journey with a strong passion for science, particularly in the realm of data science, big data, and data mining. Her fascination with handling large volumes of high-dimensional data and employing various data mining techniques led her to pursue a Ph.D. in this field at VTU Belgaum. Her research endeavors are focused on processing and analyzing complex datasets, exploring innovative methodologies to extract meaningful insights.

Professional Endeavors

With a total experience of 9.5 years, she has made significant contributions to academia and industry. She has served as an Assistant Professor at prestigious institutions such as Nitte Meenakshi Institute of Technology, Vijaya Vittal Institute of Technology, and BIT Institute of Technology, among others. Her teaching tenure has been marked by a commitment to excellence, where she imparted knowledge and mentored students in the fields of computer science and engineering.

Deep learning is a subset of artificial intelligence (AI) and machine learning that involves training artificial neural networks to learn from vast amounts of data. Using sophisticated algorithms inspired by the structure and function of the human brain, deep learning models can automatically discover and extract intricate patterns and representations from complex datasets. Neural networks, the building blocks of deep learning, consist of interconnected layers of artificial neurons that process and transform input data to produce meaningful outputs. As a key component of data science, deep learning has revolutionized various fields such as computer vision, natural language processing, speech recognition, and autonomous systems. With its ability to handle unstructured data and perform feature learning automatically, deep learning continues to drive innovation and advancements in AI research and applications.

Contributions and Research Focus in Deep learning

Her research focuses on the intersection of deep learning, artificial intelligence, neural networks, machine learning, and data science. Her work delves into developing advanced algorithms and models to tackle complex problems in various domains such as computer vision, natural language processing, and autonomous systems. By leveraging cutting-edge technologies and methodologies, she strives to push the boundaries of knowledge and contribute to the advancement of these fields.

As a key component of data science, deep learning has revolutionized various fields such as computer vision, natural language processing, speech recognition, and autonomous systems. With its ability to handle unstructured data and perform feature learning automatically, deep learning continues to drive innovation and advancements in AI research and applications. The applications of deep learning span across various domains, revolutionizing fields such as computer vision, natural language processing, speech recognition, and autonomous systems.

Accolades and Recognition

Throughout her career, she has garnered recognition for her outstanding contributions. Her dedication to research and education has earned her accolades such as the Best Researcher Award. Her publications in reputed journals and her active participation in conferences and workshops have further solidified her reputation as a leading researcher in her field.

Impact and Influence

Her work has had a profound impact on the academic and scientific community. Her research findings and insights have contributed to advancements in deep learning, artificial intelligence, and data science, driving innovation and progress in these fields. Through her mentorship and guidance, she has inspired numerous students to pursue careers in research and academia, leaving a lasting legacy in the field.

Legacy and Future Contributions

As she continues her journey in research and education, her legacy is poised to grow even further. With her passion, expertise, and dedication, she will continue to make significant contributions to deep learning, artificial intelligence, neural networks, machine learning, and data science. Her future endeavors hold the promise of further breakthroughs and advancements, shaping the landscape of these fields for 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