Rounak Raman | Information Technology | Research Excellence Award

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Mr. Rounak Raman | Information Technology | Research Excellence Award

Netaji Subhas University of Technology | India

Rounak Raman is a technology researcher and engineering innovator with a strong academic background in Information Technology and a multidisciplinary portfolio spanning artificial intelligence, machine learning, generative AI, computer vision, IoT systems, wireless sensor networks, and network security. He has gained significant research and development experience through contributions at DRDO-INMAS, where he worked on EEG-based cognitive analytics and neurofeedback systems, and at NSUT, where he designed advanced IoT protocols including energy-aware clustering, trust-based opportunistic communication, and secure hierarchical key-rotation mechanisms. His technical work extends into generative AI solutions, semantic search systems, real-time computer vision applications, and large-scale image and document intelligence models. He has led impactful projects such as PRAGATI smart parking, SyntheX document analysis framework, and QuickTag for AI-driven product taxonomy. His achievements include securing positions in national innovation challenges, hackathons, entrepreneurship competitions, and international fellowship programs. Alongside industry-recognized certifications in data science, system design, and cybersecurity, he has also held leadership roles in student organizations, mentoring teams, guiding open-source contributions, and facilitating research collaboration. His research interests include GenAI, NLP, IoT security, WSNs, cryptography, edge intelligence, and autonomous network optimization. He remains committed to creating scalable, socially impactful technological solutions.

Profiles: Google Scholar

Featured Publication

Raman, R., Yadav, A., Kukreja, D., & Sharma, D. K. (2025). CONTEXT-NET: A context-aware nexus-based aggregation protocol for opportunistic networks. Internet of Things, 101809.

Raman, R., Yadav, A., & Kukreja, D. (2025). ARMor-IoT: Aggregated reliable mechanism for optimized trust in IoT. In International Conference on Artificial Intelligence and Its Application (pp. 229–241).

Sivakamasundari | Computer Science | Best Researcher Award

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Ms. Sivakamasundari | Computer Science | Best Researcher Award

SRM Institute of Science and Technology | India

Ms. P. Sivakamasundari is a dedicated academic and researcher in Computer Science and Engineering, recognized for her contributions to deep learning-based medical image analysis. With qualifications spanning Diploma, Bachelor’s, and Master’s degrees in Computer Science and Engineering, she is currently pursuing her Ph.D. at SRM Institute of Science and Technology. She has extensive teaching experience as an Assistant Professor for more than a decade, during which she has guided students in core computing subjects including algorithms, computation theory, compiler design, and image classification. Her research focuses on advanced deep learning frameworks for healthcare applications, particularly diabetic retinopathy and diabetic foot ulcer detection, resulting in book chapters, conference publications, and journal manuscripts under review. She has published and filed patents related to medical imaging and automated disease detection systems, demonstrating her innovation-driven approach. Her scholarly presence includes 1 citation, 1 h-index, and 0 i10-index, indicating emerging research visibility. She has completed multiple professional certifications and participated in workshops, FDPs, and internships in machine learning, biometrics, accelerated computing, and high-performance healthcare analytics. Her work reflects strong commitment toward applying AI for societal benefit, and she continues to advance her expertise through active research and academic contributions.

Profile: Google Scholar

Featured Publications

Sivakamasundari, P., Anandhi, S., Kumaran, A. A., Vijayakumar, K., Birnica, Y. J., & others. (2024). Early detection of glaucoma utilizing retinal nerve fiber layer (RNFL) investigation. International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems.

Sivakamasundari, P., & Niranjana, G. (2025). An automatic detection and classification of diabetic foot ulcers using Chebyshev chaotic ladybug beetle optimized extended Swin Transformer–InceptionV3 model. Biomedical Signal Processing and Control, 110, 108268.

Gomathi, G., Sumathy, V., Sivakamasundari, P., & Deepa, R. (2024). A various approaches of machine learning algorithms for kidney disease prediction. International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems.

Sivakamasundari, P., & Niranjana, G. (2024). Diabetic foot ulcer classification using deep learning approach. International Conference on Computer, Communication and Signal Processing (ICCCSP).

Sivakamasundari, P., & Niranjana, G. (2023). A critique on deep learning methodologies employed for the identification of diabetic retinopathy using fundus images. Intelligent Computing and Control for Engineering and Business Systems (ICCEBS).

Tejinder Kaur | Computer Science | Best Researcher Award

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Dr. Tejinder Kaur | Computer Science | Best Researcher Award

MM Institute of Computer Technology & Business Management | India

Dr. Tejinder Kaur is an accomplished academic and researcher in Computer Science and Engineering, currently serving as an Associate Professor with extensive teaching and research experience in artificial intelligence, machine learning, big data, and software engineering. She holds a Ph.D. from Thapar University and an M.Tech from Chandigarh University, with postdoctoral research in progress from a reputed public university. Her work has earned significant scholarly recognition with over 54,815 citations, an h-index of 65, and an i10-index of 148, reflecting her impactful contributions to scientific research and innovation. Dr. Kaur has authored and reviewed numerous research papers and book chapters and has guided several postgraduate theses in areas like vehicular networks, routing protocols, and wireless sensor networks. Her research interests span artificial intelligence, IoT, cybersecurity, and advanced computing systems. She has published over 277 papers, filed and been granted multiple national and international patents, and received prestigious awards, including honors from IEEE, Infosys, and SAP. A committed educator and innovator, Dr. Kaur continues to inspire through academic excellence and research leadership. Her outstanding academic record, extensive publication portfolio, and technological innovations highlight her as a dynamic professional dedicated to advancing computing and intelligent systems.

Profiles: Google Scholar | Scopus

Featured Publications

Abbott, B. P., Abbott, R., Abbott, T. D., Abernathy, M. R., Acernese, F., Ackley, K., et al. (2016). Observation of gravitational waves from a binary black hole merger. Physical Review Letters, 116(6), 061102. https://doi.org/10.1103/PhysRevLett.116.061102

Aasi, J., Abbott, B. P., Abbott, R., Abbott, T., Abernathy, M. R., Ackley, K., Adams, C., et al. (2015). Advanced LIGO. Classical and Quantum Gravity, 32(7), 074001. https://doi.org/10.1088/0264-9381/32/7/074001

Abbott, B. P., Abbott, R., Abbott, T. D., Abernathy, M. R., Acernese, F., Ackley, K., et al. (2016). GW151226: Observation of gravitational waves from a 22-solar-mass binary black hole coalescence. Physical Review Letters, 116(24), 241103. https://doi.org/10.1103/PhysRevLett.116.241103

Abbott, R., Abbott, T. D., Acernese, F., Ackley, K., Adams, C., Adhikari, N., et al. (2023). GWTC-3: Compact binary coalescences observed by LIGO and Virgo during the second part of the third observing run. Physical Review X, 13(4), 041039. https://doi.org/10.1103/PhysRevX.13.041039

Abbott, B. P., Abbott, R., Abbott, T. D., Abernathy, M. R., Acernese, F., Ackley, K., et al. (2016). Tests of general relativity with GW150914. Physical Review Letters, 116(22), 221101. https://doi.org/10.1103/PhysRevLett.116.221101

Priyanka Dhaka | Computer Science | Best Researcher Award

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Dr. Priyanka Dhaka | Computer Science | Best Researcher Award

Maharaja Surajmal Institute | India

Dr. Priyanka Dhaka is an accomplished academician and researcher in Computer Science and Engineering, currently serving as an Assistant Professor at Maharaja Surajmal Institute. With strong expertise in software development, data analytics, machine learning, and big data technologies, she has made significant contributions to healthcare, cybercrime investigation, and IoT-based predictive modeling. Her work encompasses both theoretical and applied research, resulting in publications in reputed journals and conferences. She is also a patent holder and has been actively involved in innovative projects. Dr. Dhaka is dedicated to advancing technology through impactful teaching, research, and development in emerging computing fields.

Professional Profile

Google Scholar

Education

Dr. Priyanka Dhaka holds a Ph.D. in Computer Science and Engineering, supported by prior academic qualifications in M.Tech in Information Technology and B.Tech in Computer Science and Engineering. Her education has provided a solid foundation in programming, data analysis, software development, and machine learning. She has also undertaken specialized certifications in advanced technologies, including MATLAB for machine learning. Her academic journey reflects a consistent focus on emerging computing domains, enabling her to develop advanced problem-solving capabilities. The blend of her technical education and research-oriented mindset equips her to contribute effectively to both academia and the software industry.

Professional Experience

Dr. Priyanka Dhaka has served as an Assistant Professor at reputed academic institutions, including Maharaja Surajmal Institute and Maharaja Surajmal Institute of Technology, where she has contributed to teaching, research, and curriculum development. Her professional journey includes delivering guest lectures, coordinating academic events, and mentoring students in technical projects. She has also been involved in industry-oriented training, applying her expertise in programming, big data analytics, and software engineering. In addition to academia, she has practical experience in developing software solutions, handling data-driven projects, and collaborating with multidisciplinary teams to address real-world technological challenges.

Awards and Recognition

Dr. Priyanka Dhaka has been recognized for her academic and research contributions through publications in reputed international journals and IEEE-sponsored conferences. She holds a granted patent for an innovative Braille display device, highlighting her commitment to impactful technological solutions. She has participated in and coordinated various academic and technical events, earning recognition for her contributions. Additionally, she has been a runner-up in a software development competition and invited to deliver expert lectures on big data analytics. Her involvement in workshops on advanced computing fields further reflects her continuous pursuit of professional excellence and contribution to the academic community.

Research Skills

Dr. Priyanka Dhaka possesses extensive research expertise in machine learning, deep learning, big data analytics, and IoT-based healthcare applications. Her work has addressed critical areas such as heart disease prediction, healthcare data management, and cybercrime investigation through innovative computational models. She is proficient in data handling using tools like Hadoop, MongoDB, and advanced programming languages. Her research outcomes include multiple high-quality publications, book chapters, and collaborative projects with interdisciplinary teams. She applies analytical and experimental approaches to develop intelligent systems, integrating domain knowledge with modern computational techniques to solve real-world problems effectively and efficiently.

Notable Publications

Big data application: Study and archival of mental health data, using MongoDB
Author: P Dhaka, R Johari
Journal: 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)
Year: 2016
Citations: 24

WoM-based deep BiLSTM: smart disease prediction model using WoM-based deep BiLSTM classifier
Author: P Dhaka, B Nagpal
Journal: Multimedia Tools and Applications 82 (16), 25061-25082
Year: 2023
Citations: 23

CRIB: Cyber crime investigation, data archival and analysis using big data tool
Author: P Dhaka, R Johari
Journal: 2016 International Conference on Computing, Communication and Automation (ICCCA)
Year: 2016
Citations: 14

HCAB: HealthCare analysis and data archival using big data tool
Author: P Dhaka, R Johari
Journal: 2016 1st India International Conference on Information Processing (IICIP), 1-6
Year: 2016
Citations: 8

An Innovative Approach to Cardiovascular Disease Prediction: A Hybrid Deep Learning Model
Author: P Dhaka, R Sehrawat, P Bhutani
Journal: Engineering, Technology & Applied Science Research 13 (6), 12396-12403
Year: 2023
Citations: 6

Adaptive Ensembled Fusion Based Deep CNN-Bilstm Model For Heart Disease Prediction In IoT
Author: P Dhaka, R Sehrawat
Journal: Fusion: Practice & Applications 14 (1)
Year: 2024
Citations: 2

Conclusion

Dr. Priyanka Dhaka stands out as a dedicated educator, skilled researcher, and technology innovator. Her academic qualifications, teaching experience, and research contributions reflect a deep commitment to advancing computer science and engineering. She bridges the gap between theory and practice through her involvement in cutting-edge projects, impactful publications, and industry-relevant training. With expertise spanning programming, big data, AI, and IoT, she continues to inspire students and contribute to technological innovation. Her career demonstrates a strong balance between academic excellence and practical application, positioning her as a valuable contributor to the advancement of modern computing solutions.

Chaitanya Kulkarni | Computer Science | Outstanding Educator Award

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Dr. Chaitanya Kulkarni | Computer Science | Outstanding Educator Award

Vidya Pratishthan’s Kamalnayan Bajaj Institute of Engineering and Technology, Baramati | India

Dr. Chaitanya Shrikant Kulkarni is a distinguished academician and Head of the Department of Artificial Intelligence and Data Science at Vidya Pratishthan’s Kamalnayan Bajaj Institute of Engineering & Technology, Baramati. With extensive experience in undergraduate and postgraduate teaching, he has contributed significantly to curriculum development, research, and innovation in AI, machine learning, and data-driven technologies. His research portfolio spans AI-powered mental health monitoring, predictive maintenance, and financial forecasting. He has authored research papers in reputed indexed journals, published books, and filed multiple patents. His role as an editor and reviewer reflects his active engagement in the academic and research community.

Professional Profile

Scopus

Education

Dr. Chaitanya Kulkarni earned his Bachelor’s degree in Computer Engineering from Shivaji University and a Master of Technology in Computer Engineering from Bharati Vidyapeeth, Pune. He later completed his doctoral studies in Computer Engineering, focusing on advancements in artificial intelligence and machine learning applications. His academic journey has been enriched through participation in various short-term training programs, quality improvement programs, and faculty development initiatives sponsored by recognized educational and professional bodies. These academic achievements have built a strong foundation for his teaching, research, and leadership in emerging technologies, allowing him to mentor students and guide research projects effectively across diverse domains.

Professional Experience

Dr. Chaitanya Kulkarni has a rich career in academia, beginning as a lecturer and advancing to senior faculty and departmental leadership roles. He has served in reputed engineering institutions, contributing to teaching at both undergraduate and postgraduate levels. His responsibilities have included curriculum design, thesis review, and mentoring research initiatives. As a Principal Investigator, he has successfully executed projects in sonar sediment classification and automated silkworm egg counting using image processing. His consultancy work with industry stakeholders has provided practical applications for academic research. Additionally, he has been actively involved in organizing academic programs and fostering interdisciplinary collaboration.

Awards and Recognition

Dr. Chaitanya Kulkarni has received recognition for his scholarly contributions, academic leadership, and innovative research. His work has been published in prominent indexed journals, and he has authored a book with an ISBN registration. He has published and filed several patents, reflecting his focus on translating research into practical solutions. His appointment as an editor for a multidisciplinary research journal and as a reviewer for prestigious international publications, including IEEE Access, highlights his expertise and professional standing. He is also a member of professional bodies, which enables him to stay connected with the broader research and technology community.

Research Skills

Dr. Chaitanya Kulkarni possesses strong research skills in artificial intelligence, machine learning, and data science, with applications in healthcare, industrial maintenance, and financial analytics. His expertise includes developing predictive models, designing intelligent systems, and applying image processing techniques for problem-solving. He has led projects that bridge the gap between theoretical research and industry requirements, ensuring practical applicability of solutions. His publications in Scopus-indexed journals and his patents demonstrate his ability to contribute original and impactful work. He is also adept at supervising postgraduate research, reviewing scholarly articles, and maintaining high standards of academic integrity in his research endeavors.

Notable Publication

Enhanced ubiquitous system architecture for securing healthcare IoT using efficient authentication and encryption
Journal: International Journal of Data Science and Analytics
Year: 2025
Citations: 2

Conclusion

Dr. Chaitanya Kulkarni’s career reflects a blend of academic excellence, research innovation, and leadership in emerging technologies. His commitment to integrating advanced AI and machine learning techniques into practical solutions has led to meaningful contributions in diverse sectors. With his extensive teaching experience, strong research background, and industry collaborations, he continues to mentor the next generation of engineers and researchers. His published works, patents, and editorial roles demonstrate his dedication to knowledge dissemination and scholarly engagement. Dr. Kulkarni remains focused on advancing technological research, fostering academic growth, and contributing to the evolving landscape of artificial intelligence and data science.

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

Published-on by Indian Scientist

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