V Sidda Reddy | Computer Science | Best Researcher Award

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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

Manish Kumar Chandan | Computer Science | Best Researcher Award

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Mr. Manish Kumar Chandan | Computer Science | Best Researcher Award

Guru Ghasidas Vishwavidyalaya, bilaspur c.g, India

Author Profile

GOOGLE SCHOLAR

🎓 EARLY ACADEMIC PURSUITS

Manish Kumar Chandan’s academic foundation was laid with a B.Sc. in Computer Science from Atal Bihari Vajpayee Vishwavidyalaya (ABVV), Bilaspur, completed in 2020. Driven by a deep interest in computational systems and intelligent algorithms, he pursued a Master of Computer Applications (M.C.A.) from Guru Ghasidas Vishwavidyalaya (GGV), a Central University, graduating in 2022. His academic excellence and curiosity in data-driven systems led him to enroll in Ph.D. in Computer Science and IT at the same university, marking the beginning of a promising research journey.

🏢 PROFESSIONAL ENDEAVORS

Currently serving as a Research Scholar at the Department of Computer Science and IT, GGV Bilaspur, Manish has been actively involved in academic research and machine learning application development. His professional projects include Gold Price Prediction and Air Pollution Forecasting, both developed using ML/DL models and real-time datasets from CPCB. He also holds certifications in advanced AI, data science, and deep learning, demonstrating a strong commitment to continual learning and innovation.

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN COMPUTER SCIENCE

Manish’s core research area revolves around Natural Language Processing (NLP), Multilingual Sentiment Analysis, and Hybrid Deep Learning Architectures. His Ph.D. research focuses on “Code-Mix Sentiment Analysis”, addressing the growing complexities of multilingual social media data. His contributions include:

  • A published survey paper on Sentiment Analysis Techniques, covering frameworks, challenges, and future directions.

  • Proposed an Attention-Augmented CNN–BiLSTM model for Hindi sentiment classification with a notable 92.81% accuracy.

  • Developed a hybrid Word2Vec + DistilBERT-based CNN–BiLSTM model, improving cross-domain sentiment classification on IMDb and Yelp datasets.

🌍 IMPACT AND INFLUENCE

Though in the early stage of his research career, Manish’s work already shows potential for real-world applications in social media monitoring, policy sentiment mapping, and digital language processing. His approaches aim to support multilingual populations, especially in India, by bridging the gap in code-mixed sentiment interpretation. With the rise of digital platforms, such research can aid governments, businesses, and healthcare sectors in public opinion analysis and customer behavior forecasting.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Manish aims to develop a comprehensive framework for Multilingual and Code-Mixed Sentiment Analysis capable of adapting to low-resource languages. Future contributions will target:

  • AI tools for regional languages

  • Emotion detection in conversational AI

  • Cross-lingual and domain adaptation methods

He also plans to mentor junior researchers, publish in top-tier journals (e.g., ACL, EMNLP, IEEE-TKDE), and contribute to open-source NLP models for Indian languages.

 ✅CONCLUSION

Manish Kumar Chandan is a promising young researcher in the field of Computer Science, making meaningful strides in AI, NLP, and Multilingual Sentiment Analysis. His academic rigor, innovative mindset, and socially impactful research make him a deserving candidate for recognition under the Indian Scientist Award. As he advances his research journey, Manish is poised to become a key contributor to India’s AI innovation ecosystem.

🔬NOTABLE PUBLICATION:

A comprehensive survey on sentiment analysis: Framework, techniques, and applications

Authors: M.K. Chandan, S. Mandal

Journal: Computer Science Review

Year: 2025

Nisha Agrawal | Computer Science | Best Researcher Award

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Nisha Agrawal | Computer Science | Best Researcher Award

Centre for Development of Advanced Computing, India

Author Profile

SCOPUS

🎓 EARLY ACADEMIC PURSUITS

Ms. Nisha Agrawal began her academic journey with a Bachelor of Engineering (B.E.) in Information Technology from the University of Rajasthan (2001–2005). Demonstrating exceptional academic excellence, she went on to pursue a Master of Technology (M.Tech) in Computer and Information Technology from Savitribai Phule Pune University (2016–2018), graduating with an Outstanding grade. Her early interest in computational systems and performance optimization laid the foundation for a career immersed in high-performance computing (HPC) and GPGPU technologies.

🏢 PROFESSIONAL ENDEAVORS

Ms. Agrawal has been associated with the Centre for Development of Advanced Computing (C-DAC), Pune since 2005, rising through the ranks to her current role as Scientist E. Over the past two decades, she has been instrumental in architecting, optimizing, and deploying scientific applications on India’s national supercomputing infrastructures. A NVIDIA-Certified Mentor, she actively mentors teams in global OpenHackathons, nurturing the next generation of HPC professionals.

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN COMPUTER SCIENCE

Her core research interests span:

  • GPGPU Computing: CUDA, OpenACC, OpenCL

  • Parallel Programming Models: MPI, OpenMP

  • Application Porting & Optimization: ANUGA (Flood modeling), WRF (Weather simulation), NAMD (Molecular dynamics), DFT (Density Functional Theory)

She has extensively worked on heterogeneous architectures (CPU+GPU), focusing on performance tuning and energy efficiency of HPC workloads. Her work contributes significantly to the computational sciences, particularly in areas demanding real-time and large-scale simulation capabilities.

🏅 ACCOLADES AND RECOGNITION

With over a dozen peer-reviewed publications, including those in IEEE, ACM, Springer, and SupercomputingAsia, Ms. Agrawal has established herself as a recognized voice in scientific computing. Some key contributions include:

  • Scalability Analysis of WRF on NVIDIA Ampere (2022)

  • Performance Evaluation of AMDKIIT for DFT (2025)

  • Memory Bandwidth Analysis: Xeon Phi vs Xeon (Women in HPC)
    Her work is increasingly cited in scientific literature addressing performance optimization, GPU utilization, and edge computing.

🌍 IMPACT AND INFLUENCE

A respected HPC specialist, Ms. Agrawal has delivered 30+ invited talks and tutorials at India’s top institutions such as IITs, IISERs, and international forums. She contributes to the HPC ecosystem not just through development, but also through education and mentorship, fostering innovation and skill-building among students and researchers.

Her participation in Women in HPC at ISC, Grace Hopper Conference (GHCI), and IEEE and ACM symposiums underscores her advocacy for diversity and excellence in computational sciences.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Ms. Agrawal’s legacy lies in shaping India’s HPC landscape, especially through:

  • Democratizing GPU-based computing

  • Promoting women in scientific computing

  • Championing energy-efficient simulations for societal applications like climate modeling and disaster prediction

Her future endeavors focus on enhancing AI-HPC convergence, cloud-native HPC architectures, and mentor-based innovation programs, ensuring a sustainable pipeline of research talent and technology integration.

 ✅CONCLUSION

Ms. Nisha Agrawal is not only a pioneer in HPC and GPGPU computing but also a dedicated mentor, educator, and researcher. Her two-decade journey from student to Scientist E at C-DAC exemplifies technical brilliance, scientific curiosity, and a vision for inclusive technological growth. Her contributions continue to empower research, education, and innovation across India and beyond.

 🔬NOTABLE PUBLICATION:

Experience with adapting to a software framework for a use-case in computational science

Authors: V.V. Shenoi, V. Venkatesh, Nisha Agrawal.
Journal: Journal of Parallel and Distributed Computing
Year: 2025