Nisha Agrawal | Cell Structure Analysis | Best Researcher Award

Mrs. Nisha Agrawal | Cell Structure Analysis | Best Researcher Award

Mrs. Nisha Agrawal, Centre for Development of Advanced Computing (C-DAC), India

Dr. Nisha Agrawal is a seasoned HPC (High-Performance Computing) specialist and currently serves as Scientist E at the Centre for Development of Advanced Computing (C-DAC), Pune. With over 20 years of expertise, she specializes in GPGPU computing, parallel programming, and the optimization of scientific applications on heterogeneous supercomputers. A NVIDIA-Certified Mentor, she is a recognized leader in GPU-accelerated simulation and a frequent mentor at OpenHackathons worldwide. She is an accomplished speaker with 30+ invited talks at IITs, IISERs, and major scientific forums. Her portfolio includes numerous peer-reviewed publications and the Best Paper Award at IEEE TEMSMET 2021. Dr. Agrawal’s deep commitment to scientific research, HPC education, and her passion for innovation in parallel computing make her a standout candidate for the Best Researcher Award.

Publication Profile:Β 

Scopus

βœ… Strengths for the Award:

  1. Extensive Domain Expertise (20+ Years)
    Dr. Agrawal has over two decades of hands-on experience in High-Performance Computing (HPC), which showcases both her technical maturity and consistency in research.

  2. Specialized Skill Set in GPGPU & Scientific Computing
    She is highly proficient in CUDA, OpenACC, MPI, OpenMP, and has successfully ported and optimized complex applications like DFT, NAMD, ANUGA, and WRF on heterogeneous (CPU+GPU) systems.

  3. Mentorship and Knowledge Dissemination
    As an NVIDIA-Certified Mentor and participant in OpenHackathons, she contributes not only as a researcher but also as a mentor and educator, spreading HPC knowledge to broader communities.

  4. Recognized Publications & Awards
    With 12+ peer-reviewed papers, including a Best Paper Award at IEEE TEMSMET-2021, she has established a credible presence in the international research community.

  5. Invited Speaker & Thought Leader
    Having delivered 30+ invited talks at premier institutions (IITs, IISERs), her influence in promoting HPC education and innovation is notable.

  6. Cross-Disciplinary Impact
    Her research spans multiple domains such as molecular dynamics, weather modeling, and flood simulation, indicating interdisciplinary relevance and applicability.

⚠️ Areas for Improvement:

  1. Broader International Collaboration
    While her national contributions are significant, increased participation in international research collaborations or joint projects could amplify her global academic impact.

  2. Patents and Industry Innovation
    Though she has notable research publications, contributions in the form of patents, industry tech transfer, or commercialization could further strengthen her applied research portfolio.

  3. Exploration of AI-HPC Synergies
    Given the growing overlap between AI/ML and HPC, engaging in hybrid research areas could help future-proof her work and widen its application.

πŸŽ“ Education:

Dr. Nisha Agrawal holds a Master of Technology (M.Tech) in Computer and Information Technology from S.P. Pune University (2016–2018), where she graduated with an Outstanding grade. Her foundational technical background stems from a Bachelor of Engineering (B.E.) in Information Technology from the University of Rajasthan, completed in 2005. Her academic journey is marked by both excellence and consistency, having also cleared the GATE 2005 with an impressive All India Rank of 695 in IT. Throughout her education, she has built a robust foundation in programming, system architecture, and computational modeling, which became pivotal in shaping her research interests in HPC, GPU programming, and scientific computing. Her transition from academia to research has been marked by a clear focus on applying theory to practical, high-impact computational problems.

πŸ’Ό Professional Experience:

Dr. Agrawal has been with C-DAC Pune since May 2005, rising through the ranks to her current role as Scientist E. Over the years, she has led and contributed to critical national-level HPC projects, focusing on the GPU acceleration of computational simulations like DFT, Molecular Dynamics (MD), ANUGA, and WRF. She actively mentors participants at NVIDIA/OpenACC Hackathons, fostering GPU adoption across disciplines. Her projects typically involve complex parallel and distributed programming tasks, using CUDA, OpenACC, OpenMP, and MPI. She also plays a strategic role in tuning applications for GPU+CPU clusters, especially on Ampere GPU architecture. Her professional growth has been characterized by her ability to bridge cutting-edge theory with real-world computational applications in science and engineering domains.

πŸ† Awards & Honors:

Dr. Nisha Agrawal’s research and mentoring excellence have been acknowledged through numerous accolades. She won the Best Paper Award at IEEE TEMSMET 2021, recognizing her pioneering work in GPU-based parallel computing. As a NVIDIA/OpenACC Certified HPC Mentor (2023), she contributes significantly to India’s HPC knowledge ecosystem. In 2017, she received the ACM Scholarship to attend the prestigious Grace Hopper Celebration India (GHCI), a testament to her commitment to women in technology. Earlier, she was conferred the GARGI Puraskar by the Government of Rajasthan in 1999 for academic excellence. Her qualifying performance in GATE 2005 (AIR 695) further highlighted her strong academic and analytical foundation. These honors collectively reflect a career marked by consistency, innovation, and community impact in the field of high-performance and scientific computing.

πŸ”¬ Research Focus:

Dr. Agrawal’s research revolves around the acceleration and optimization of scientific applications using GPU-centric architectures. Her core domains include molecular dynamics, weather forecasting, and flood modeling, where she leverages tools such as CUDA, OpenACC, OpenCL, and MPI to port and tune code for parallel execution on HPC clusters. A key area of her focus lies in the performance analysis of simulation software across different hardware platforms like NVIDIA GPUs and Intel Xeon processors. Through her work on multi-GPU scaling, memory bandwidth analysis, and hardware counters, she has contributed to making scientific simulations more efficient and scalable. Her interdisciplinary collaborations enable domain scientists to harness the power of heterogeneous computing architectures for complex simulations. As an educator and mentor, she also drives HPC awareness, especially in academic and R&D circles, reinforcing her dual mission of innovation and education.

πŸ“š Publication Top Notes:

  1. πŸ§ͺ Experience with Adapting to a Software Framework for a Use-Case in Computational Science – Journal of Parallel and Distributed Computing, May 2025

  2. πŸš€ GPU Implementation and Performance Evaluation of AMDKIIT for DFT – SupercomputingAsia (SCA), Mar 2025

  3. πŸ“Š Hardware Counter Based Performance Analysis of ANUGA – IC3 (ACM), Sep 2023

  4. 🌩 Scalability Analysis of WRF on NVIDIA Ampere – IC3SIS, Dec 2022

  5. πŸ”¬ NAMD Simulation on Dense GPU Supercomputer – ICTCS (Springer), Oct 2022

  6. πŸ–₯ Highly Portable C++ Simulator with Dual Parallelism – IEEE, Aug 2022

  7. πŸ† Single Instruction Stream for Massively Parallel Ops – Best Paper, IEEE TEMSMET, May 2022

  8. πŸ’‘ Multi-GPU MD Simulation on Ampere Infrastructure – Springer LNNS, Aug 2021

  9. πŸ“ˆ Performance Analysis of ANUGA on Modern Architectures – IC3 (ACM), Aug 2021

  10. βš™οΈ Memory Bandwidth Analysis: Xeon Phi vs Xeon – Women in HPC at ISC, Jun 2017

🧾 Conclusion:

Dr. Nisha Agrawal is an exceptionally qualified and highly deserving candidate for the Best Researcher Award. Her robust combination of long-term experience, technical depth in GPU-based parallel computing, impactful publications, active mentoring, and commitment to HPC education position her as a leader in the field. While expanding global collaborations and venturing into AI-HPC convergence could further enhance her profile, her existing contributions already make a strong and compelling case for recognition.