Bhushan Chaudhari | Computer Science and Artificial Intelligence | Best Industrial Research Award

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Mr. Bhushan Chaudhari | Computer Science and Artificial Intelligence | Best Industrial Research Award

Technology Lead, Iris Software Inc, United States

Dr. Bhushan P. Chaudhari is a Senior Principal Scientist at CSIR-National Chemical Laboratory (NCL), Pune, India. With a Ph.D. from Marathwada Agricultural University, he has over two decades of experience in nanotechnology and nanomedicine. His research focuses on developing next-generation targeted drug delivery systems, nanobiosensors, and sustainable agricultural solutions. Dr. Chaudhari has supervised numerous Ph.D. students and has been instrumental in advancing the field of nanopharmacology.

Profile

Google Scholar

Education

Dr. Chaudhari completed his Bachelor of Engineering in Computer Science from North Maharashtra University, India. He later pursued a Ph.D. in Biological Sciences from CSIR-NCL, Pune, under the guidance of Dr. Bhushan P. Chaudhari. His doctoral research focused on the structure-function characterization of the tail-anchored protein translocation pathway in plants, contributing significantly to the understanding of protein transport mechanisms in plant cells.

Experience

Dr. Chaudhari’s professional journey includes roles at various organizations:

  • CSIR-NCL, Pune: As a Senior Principal Scientist, he leads research in nanopharmacology, focusing on targeted drug delivery systems and nanobiosensors. IJBio+6Google Sites+6NCL IRINS+6

  • Tech Mahindra Ltd.: He worked as a Member of Technical Staff, contributing to projects like EDD-ISA, where he developed solutions for enterprise document delivery systems.

  • Perennial System: As a Team Lead, he managed offshore teams and developed dynamic web applications for clients in the insurance sector.

  • BioAnalytical: In this role, he enhanced backend and UI components for web-based applications in the healthcare domain.

Research Focus

Dr. Chaudhari’s research is centered on nanotechnology applications in medicine and agriculture. His work includes the development of functionalized nanoparticles for disease detection, biosynthesis of nanoparticles using fungi, and the creation of stimuli-responsive drug delivery systems. He has also explored the use of nanomaterials in combating plant viral diseases and enhancing agricultural sustainability.

Publications

  1. Functionalized gold nanorods (GNRs) as a label for the detection of thyroid-stimulating hormone (TSH) through lateral flow assay (LFA)
    Emergent Materials, 2024
    This study presents the use of GNRs in lateral flow assays for the sensitive detection of TSH, aiding in thyroid function diagnostics.

  2. Chitosan nanoparticles for single and combinatorial delivery of 5-fluorouracil and ursolic acid for hepatocellular carcinoma
    Emergent Materials, 2024
    The research explores chitosan-based nanoparticles for co-delivery of chemotherapeutic agents, enhancing therapeutic efficacy against liver cancer.

  3. Understanding Critical Aspects of Liposomal Synthesis for Designing the Next Generation Targeted Drug Delivery Vehicle
    Chemistry Select, 2023
    This article delves into liposomal synthesis techniques, providing insights for developing advanced drug delivery systems.

  4. Robust Optimization and Characterization of MCM-41 Nanoparticle Synthesis using Modified Sol-Gel Method
    Chemistry Select, 2023
    The paper discusses the optimization of MCM-41 nanoparticle synthesis, focusing on structural and functional properties for various applications.

  5. Nanoparticles for the Delivery of Antiviral Phytotherapeutics
    Advances in Phytonanotechnology for Treatment of Various Diseases, CRC Press, 2023
    This book chapter examines the role of nanoparticles in enhancing the delivery of plant-based antiviral agents, offering new therapeutic avenues.

Conclusion

Bhushan B. Chaudhari is a strong candidate for the Best Industrial Researcher Award, particularly in the applied software engineering and AI-driven enterprise architecture domains. His ability to integrate modern research into scalable, real-time financial and telecom applications is both impressive and impactful. His work demonstrates a clear bridge between industrial challenges and technological innovation, with AI, microservices, and cloud-native design at its core. With more academic collaboration and broader community engagement, he could emerge as a leading figure not just in implementation, but also in shaping future software engineering practices.

Umar Islam | Computer Science | Best Researcher Award

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Mr. Umar Islam | Computer Science | Best Researcher Award

Senior Lecturer, IQRA National University Swat Campus, Pakistan

Mr. Umar Islam is a passionate and accomplished educator and researcher in the field of Computer Science, currently serving as a Lecturer at Iqra National University (INU) Swat Campus, Pakistan. With an impressive academic background spanning 18 years in Computer Science, Mr. Islam has become a recognized expert in AI, machine learning, blockchain security, IoT, bioinformatics, and financial analytics. His work has been published in over 15 research articles, including several in top-tier journals. A dedicated researcher, he focuses on real-time AI solutions, particularly in healthcare and cybersecurity. Mr. Islam is also a committed mentor, providing supervision and guidance to students in advanced topics such as Python programming, machine learning, and AI applications. His contributions to the academic community and his research endeavors demonstrate his commitment to pushing the boundaries of knowledge and solving real-world problems.

Profile

Education

Mr. Umar Islam has an extensive academic journey, earning 18 years of education in Computer Science. His academic path began with a Bachelor’s degree in Computer Science, followed by a Master’s degree, where he built the foundation of his knowledge in various aspects of computing. Mr. Islam’s thirst for knowledge and his passion for research led him to pursue advanced studies in areas like AI, machine learning, IoT, and cybersecurity, with a strong focus on applying these technologies to solve real-world challenges. His educational journey has equipped him with the skills to lead cutting-edge research projects and to innovate in fields like bioinformatics and financial analytics. Currently, he is working toward a PhD, which will further deepen his understanding and expertise in these areas. Through his education, Mr. Islam has gained a comprehensive understanding of theoretical and applied Computer Science, which he integrates into both his teaching and research.

Experience

With six years of teaching experience at the higher education level, Mr. Umar Islam has played a pivotal role in shaping the future of numerous students at Iqra National University (INU) Swat Campus. As a lecturer, he has delivered comprehensive lessons in Computer Science topics such as AI, machine learning, and cybersecurity. His commitment to academic excellence is reflected in his success as a supervisor, guiding students through complex topics like Python programming, e-learning analytics, and AI-driven applications. In addition to teaching, Mr. Islam has gained four years of extensive research experience, with a focus on AI applications in healthcare, cybersecurity, and blockchain security. He has led multiple research projects, producing groundbreaking results, and has contributed significantly to the academic community with over 15 published research articles. His academic experience extends beyond teaching, positioning him as a thought leader in his field.

Research Focus

Mr. Umar Islam’s research is deeply focused on the intersection of artificial intelligence (AI), cybersecurity, healthcare, and financial analytics. One of his key research areas includes AI-driven solutions in healthcare, particularly the development of federated learning-based intrusion detection systems and epileptic seizure prediction models. He is also actively exploring AI in cybersecurity, specifically in blockchain security, to mitigate data tampering risks. His work in financial analytics uses AI and machine learning to predict market trends, including cryptocurrency values, demonstrating his interdisciplinary approach to solving real-world problems. In addition to these topics, Mr. Islam is involved in pioneering research in IoT security and bioinformatics. His research aims to address key global challenges such as healthcare delivery, data security, and economic stability through cutting-edge AI applications. His innovative contributions to various fields have resulted in multiple published articles in prestigious journals, demonstrating the far-reaching impact of his work.

Publication Top Notes

  • Detection of distributed denial of service (DDoS) attacks in IoT-based monitoring system of banking sector using machine learning models 🌐🔐📊
  • IOTA-Based Mobile Crowd Sensing: Detection of Fake Sensing Using Logit-Boosted Machine Learning Algorithms 🤖📱💡
  • Real-time detection schemes for memory DoS (M-DoS) attacks on cloud computing applications ☁️💻🛡️
  • Detection of renal cell hydronephrosis in ultrasound kidney images: a study on the efficacy of deep convolutional neural networks 🏥🧠📸
  • A novel anomaly detection system on the internet of railways using extended neural networks 🚆🔍⚙️
  • NeuroHealth guardian: A novel hybrid approach for precision brain stroke prediction and healthcare analytics 🧠💓📈
  • An intelligent approach for preserving the privacy and security of a smart home based on IoT using LogitBoost techniques 🏠🔐💡
  • Enhancing Economic Stability with Innovative Crude Oil Price Prediction and Policy Uncertainty Mitigation in USD Energy Stock Markets 💰📊📉
  • Investigating the Effectiveness of Novel Support Vector Neural Network for Anomaly Detection in Digital Forensics Data 💾🔎👨‍💻
  • Empowering global ethereum price prediction with EtherVoyant: a state-of-the-art time series forecasting model ⛓️💹🔮

 

 

 

Sanyogita Manu | Engineering and Technology | Best Researcher Award

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Ms. Sanyogita Manu | Engineering and Technology | Best Researcher Award

PhD Candidate, The University of British Columbia, Canada

Publication Profile

Google scholar

Strengths for the Award

  1. Innovative Research Focus: Sanyogita’s work addresses a significant issue—indoor environmental quality during a time when many transitioned to remote work due to the pandemic. Her systematic study has the potential to inform guidelines and policies related to home office setups, highlighting its relevance in current public health discussions.
  2. Methodological Rigor: The research employs a robust methodology, utilizing continuous monitoring of various IEQ parameters alongside subjective assessments from participants. This comprehensive approach enhances the reliability of her findings.
  3. Professional Affiliations and Contributions: Sanyogita is actively engaged in professional organizations related to her field, serving on committees and reviewing journals. Her involvement in international conferences signifies her commitment to advancing research in IEQ and energy-efficient design.
  4. Publication Record: With multiple peer-reviewed publications and conference proceedings, Sanyogita demonstrates a solid track record in disseminating her research findings, contributing to the academic community’s understanding of indoor environments.
  5. Awards and Recognition: Her prior achievements and recognitions, including scholarships and awards, underscore her dedication and excellence in research.

Areas for Improvement

  1. Broader Impact Assessment: While her research is focused on WFH settings, there may be an opportunity to expand her study to include diverse populations and different geographical locations to enhance the generalizability of her findings.
  2. Interdisciplinary Collaboration: Collaborating with professionals from related fields such as psychology, sociology, or occupational health could enrich her research and offer a more holistic understanding of the WFH experience.
  3. Public Engagement: Engaging in public outreach or workshops to share her findings with broader audiences, including policymakers and the general public, could enhance the impact of her work and foster practical applications of her research.

Education

Sanyogita holds a Master’s degree in Interior Architecture and Design, specializing in Energy and Sustainability from CEPT University, India, where her dissertation focused on optimizing window performance in commercial buildings. She also earned her Bachelor’s degree in Interior Design from the same institution, with a dissertation exploring the thermal effects of furniture in interior environments. 🎓

Experience

With extensive experience in academia and research, Sanyogita has contributed to various projects assessing indoor environmental conditions and energy efficiency in buildings. She has served on several scientific committees and has been actively involved in peer review for reputable journals, reflecting her expertise in the field. 🏢

Research Focus

Her research primarily focuses on indoor environmental quality (IEQ) and its impact on occupant well-being and productivity, particularly in work-from-home settings. Sanyogita employs a systematic approach to evaluate both perceived and observed IEQ, utilizing a variety of environmental monitoring tools. 🔍

Awards and Honours

Sanyogita is a member of multiple prestigious organizations, including the International Society of Indoor Air Quality and Climate (ISIAQ) and the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). She has been recognized for her contributions to building performance simulation and energy conservation, reflecting her commitment to sustainable practices. 🏆

Publication Top Notes

Manu, S., & Rysanek, A. (under review). A novel dataset of indoor environmental conditions in work-from-home settings. Building and Environment.

Manu, S., & Rysanek, A. (2024). A Co-Location Study of 87 Low-Cost Environmental Monitors: Assessing Outliers, Variability, and Uncertainty. Buildings, 14(9), Article 9. Link

Manu, S., et al. (2024). A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings. Building and Environment, 111652. Link

Doctor-Pingel, M., et al. (2019). A study of indoor thermal parameters for naturally ventilated occupied buildings in the warm-humid climate of southern India. Building and Environment, 151, 1-14. Link

Manu, S., et al. (2019). Performance evaluation of climate responsive buildings in India – Case studies from cooling dominated climate zones. Building and Environment, 148, 136-156. Link

Gupta, R., et al. (2019). Customized performance evaluation approach for Indian green buildings. Building Research & Information, 47(1), 56–74. Link

Conclusion

Sanyogita Manu’s research on indoor environmental quality in work-from-home settings is both timely and significant. Her methodological rigor, publication record, and active participation in professional communities demonstrate her dedication to advancing knowledge in her field. While there are areas for improvement, her strengths strongly position her as a worthy candidate for the Best Researcher Award. Her work has the potential to influence policy and improve well-being in residential work environments, making her contributions invaluable in today’s context.

Alexandra Radushinskaya | The Impact Of Technology On The Economy | Women Researcher Award

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Dr.Alexandra Radushinskaya | The Impact Of Technology On The Economy | Women Researcher Award

Docent at St. Petersburg State University , Russia

Аlexandra Radushinsky is an accomplished academic and researcher based at Saint-Petersburg State University in Russia. With over 20 years of experience in research and teaching, she holds the title of Associate Professor and a Candidate of Sciences degree. Alexandra has authored more than 50 scholarly articles, contributing significantly to her field. She also has a rich background in media, having worked in television and received a nomination for the national business award “Media Manager of Russia” in 2012. Passionate about community service, she has been involved in charitable organizations since her teens. Her diverse experiences enrich her academic pursuits, making her a well-rounded and impactful scholar.

Profile:

Scopus Profile

Education:

Аlexandra Radushinsky holds an academic degree of Candidate of Sciences, which is equivalent to a Ph.D., awarded by Saint-Petersburg State University, where she also serves as an Associate Professor in the Russian Policy Department. Her educational journey has been marked by rigorous training in research methodologies and policy analysis, equipping her with the skills to address complex societal issues. Throughout her academic career, she has engaged in various professional development programs, workshops, and conferences, further enhancing her expertise. This commitment to lifelong learning is reflected in her numerous publications and presentations, showcasing her dedication to advancing knowledge in her field. Alexandra’s educational background is not only a foundation for her teaching and research but also a catalyst for her active participation in public discourse on policy matters.

Experience:

With over 20 years in academia, Аlexandra Radushinsky has cultivated a rich professional background in research and teaching. She has held various roles at Saint-Petersburg State University, where she has shaped the minds of future scholars in the Russian Policy Department. Her extensive experience includes supervising graduate and doctoral students, leading research projects, and developing curriculum. In addition to her academic work, Alexandra has spent many years in television, contributing to media projects that bridge academia and public discourse. Her nomination for the national business award “Media Manager of Russia” in 2012 highlights her effectiveness in this role. Furthermore, her long-standing commitment to charitable organizations since age 15 demonstrates her dedication to social responsibility and community service. This multifaceted experience informs her research, enhancing her ability to address complex issues at the intersection of media, policy, and society.

Research Focus:

Аlexandra Radushinsky’s research focus encompasses a wide array of topics within the realm of Russian policy, media influence, and economic development. She investigates the interplay between technology and economic growth, with particular attention to environmental and energy transition agendas. Her work explores how economic factors influence transportation and infrastructure projects, notably in the context of the Northern Sea Route and cruise transport development in Russia. Additionally, she examines political activity trends among Russians and the media’s role in shaping public opinion. Her numerous publications reflect a commitment to understanding and addressing contemporary challenges through interdisciplinary approaches. By integrating theoretical insights with practical applications, Alexandra aims to contribute meaningful solutions to pressing societal issues, fostering a deeper understanding of the complex dynamics at play in Russian policy and global economic contexts.

Publication Top Notes:

  1. The approaches for assessing the quality of scientific research at St. Petersburg Mining University 📚
  2. Improving the quality of implementation of the container transportation project along the NSR based on the environmental and energy transition agenda 🌊
  3. The influence of economic factors on the development of the project for the development of cruise transport in Russia 🚢
  4. Investment priorities and investment potential of various infrastructure facilities of the city 🏙️
  5. Innovations in redevelopment projects 🏗️
  6. Political activity of Russians: Current trends and resources of media influence 📰

Conclusion:

Alexandra Radushinsky is a highly qualified candidate for the Research for Best Researcher Award, given her extensive academic background, substantial contributions to research, and commitment to social causes. While there are areas for potential growth, her track record suggests she would be a deserving recipient of this recognition.

Qi Liang | Pattern Recognition | Excellence in Research

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Mr Qi Liang | Pattern Recognition | Excellence in Research

Master in Tongji University at China

Qi Liang is a dedicated researcher and master’s student at Tongji University, PR China, specializing in mechanical engineering. With a strong foundation in industrial engineering from Jiangsu University of Science and Technology, Qi has a keen interest in advancing technology through innovative research. Recognized for introducing self-supervised learning methods in semiconductor applications, Qi’s work aims to solve complex challenges in pattern recognition. Their publication in Engineering Applications of Artificial Intelligence reflects a commitment to high-impact research. With multiple ongoing projects and a focus on practical applications, Qi is paving the way for efficient solutions in the semiconductor industry.

Profile

Google Scholar

Strengths for the Award

  1. Innovative Research: Qi Liang has introduced a self-supervised learning method for few-shot learning in semiconductor applications, demonstrating originality and a significant contribution to the field.
  2. Publication Record: The recent publication in Engineering Applications of Artificial Intelligence showcases a commitment to high-quality research, adding to the credibility of the work.
  3. Diverse Research Interests: With a focus on computer vision, multi-modal learning, and fault diagnosis, Qi’s work spans multiple cutting-edge areas, which increases the potential impact of the research.
  4. Practical Applications: The research addresses real-world challenges in the semiconductor industry, offering low-cost, efficient methods that have immediate applicability.
  5. Academic Engagement: Qi’s active involvement in ongoing projects and industry collaborations indicates a robust engagement with both academic and practical aspects of research.

Areas for Improvement

  1. Broader Collaboration: Expanding collaborations with international researchers could enhance the research’s visibility and applicability on a global scale.
  2. Increased Publication Volume: While the current publication is commendable, a more extensive publication record could further establish Qi’s expertise and leadership in the field.
  3. Outreach and Communication: Engaging in more outreach activities, such as conferences and seminars, could help disseminate findings and foster connections within the research community.

Education 

Qi Liang graduated with a Bachelor’s degree in Industrial Engineering from Jiangsu University of Science and Technology, where foundational principles of engineering and technology were mastered. Currently, Qi is pursuing a Master’s degree in Mechanical Engineering at Tongji University, one of China’s prestigious institutions, now in their third year of the program. This advanced education has allowed Qi to engage deeply with cutting-edge topics, particularly in computer vision and machine learning. Through rigorous coursework and research, Qi has developed expertise in areas such as pattern recognition, self-supervised learning, and fault diagnosis, equipping them with the skills necessary to tackle complex engineering problems and contribute significantly to both academic and industrial advancements.

Experience

Qi Liang has gained substantial experience through multiple research projects, totaling five completed or ongoing initiatives that emphasize practical applications of machine learning in semiconductor manufacturing. In addition to academic research, Qi has participated in three consultancy and industry-sponsored projects, bridging the gap between theoretical knowledge and real-world applications. Their collaborative efforts in research have led to valuable partnerships and a broader understanding of the industry’s challenges and needs. As the first to implement self-supervised learning techniques in few-shot learning tasks related to wafer map pattern recognition, Qi has showcased exceptional innovation. This unique approach has opened new avenues for cost-effective and efficient solutions within the semiconductor sector, positioning Qi as an emerging leader in their field.

Research Focus 

Qi Liang’s research focuses on the intersection of computer vision and machine learning, with a strong emphasis on pattern recognition, keypoint detection, and image retrieval. Specializing in self-supervised and multi-modal learning, Qi aims to develop innovative methodologies that minimize the reliance on labeled data while maximizing efficiency and applicability in industrial contexts. Current research projects explore dynamic adaptation mechanisms for few-shot learning, specifically tailored for wafer map pattern recognition in the semiconductor industry. Qi is also interested in signal processing and fault diagnosis, seeking to improve reliability and performance in manufacturing processes. This research direction not only contributes to the academic community but also addresses pressing industry challenges, promoting advancements in automation and smart manufacturing.

Publication Top Notes

  • Masked Autoencoder with Dynamic Multi-Loss Adaptation Mechanism for Few Shot Wafer Map Pattern Recognition 📄

Conclusion

Qi Liang’s innovative contributions to the field of mechanical engineering and computer vision make a strong case for the Excellence in Research award. The unique approach to self-supervised learning in few-shot learning for wafer map pattern recognition signifies both a breakthrough in methodology and practical application in the semiconductor industry. With a few strategic improvements, Qi has the potential to further amplify the impact of their research and cement their status as a leading researcher in their field.