Akanksha Dwivedi | Parallel Computing | Excellence in Research Award

Ms. Akanksha Dwivedi | Parallel Computing | Excellence in Research Award

Research Scholar | Indian Institute of Technology Jodhpur | India

Ms. Akanksha Dwivedi is a doctoral research scholar in Computer Science and Engineering at the Indian Institute of Technology Jodhpur, where she works under the guidance of Dr. Dip Sankar Banerjee at the Systems for Performance, Analysis, and Data Engineering Lab. She holds a Master of Technology in Mechatronics, Robotics, and Automation from the Center for Advanced Studies, Lucknow, and a Bachelor of Technology in Electronics and Communication Engineering from Dr. APJ Abdul Kalam Technical University, Lucknow. She has served as a Teaching Assistant at IIT Jodhpur and RSVS Lucknow, as well as a Project Associate at the National Institute of Technology Uttarakhand, contributing to projects in deep learning for speech decoding and precision health technologies. Her research interests include high-performance computing, scalable parallel algorithms, data analytics, artificial intelligence for healthcare applications, robotics, and sensor technologies. She has published in reputed venues such as Future Generation Computer Systems and IEEE High Performance Extreme Computing, with additional contributions in AI-driven healthcare sensors and sustainable materials. Akanksha has received prestigious fellowships including the Anusandhan National Research Foundation project fellowship and the Ministry of Education doctoral fellowship. She has been honored with awards for innovative ideas, international travel grants, and recognition in hackathons and debate competitions, as well as achievements in sports at the state level. Her research skills span programming in C, Python, and CUDA, parallel computing with OpenMP, data analysis, robotics systems, and advanced tools such as MATLAB and Docker, reflecting her strong technical foundation and multidisciplinary expertise.

Profiles: ORCID | ResearchGate | LinkedIn

Featured Publications

  1. Dwivedi, A., & Banerjee, D. S. (2024, December 4). MST in incremental graphs through tree contractions. In Proceedings of the 28th IEEE High Performance Extreme Computing Conference (HPEC), Boston, USA.

  2. Dwivedi, A., Sharma, S., & Banerjee, D. S. (2023, March 3). Efficient parallel algorithms for large tree contraction. In Proceedings of the Student Research Symposium, International Conference on High Performance Computing (HiPC).

Mr. Sanchit | Parallel Computing | Excellence in Research

Mr. Sanchit, Parallel Computing, Excellence in Research

Arzu Gezer at Indian Institute of Information Technology, India

Professional Profile

🌟 Summary:

Mr. Sanchit is a Research Scholar at the Indian Institute of Information Technology, Allahabad, where he is pursuing his PhD after completing his BTech and MTech at UPTU University and IIIT Allahabad, respectively. His research focuses on optimizing task scheduling and energy efficiency in computing systems.

🎓 Education:

  • PhD, Indian Institute of Information Technology, Allahabad
  • MTech, Indian Institute of Information Technology, Allahabad
  • BTech, UPTU University

💼 Professional Experience:

Research Scholar, Indian Institute of Information Technology, Allahabad

  • Conducts research in task scheduling, parallel computing, and distributed computing
  • Published 3 SCI papers, with additional work under revision or submitted
  • Achieved a 3-star rating on CodeChef for competitive coding

🔬 Research Interest:

  • Task Scheduling
  • Parallel Computing
  • Distributed Computing
  • Edge Computing

📖 Publications Top Noted:

Paper Title: Multiobjective approach to schedule DAG tasks on voltage frequency islands
  • Authors: Navjot Singh, Jagpreet Singh
  • Journal: IEEE Access
  • Year: 2023
  • Citations: 6
Paper Title: Energy Efficient Heuristics to Schedule Task Graphs on Heterogeneous Voltage-Frequency Islands
  • Authors: Sanchit, Anupam Jain, Jagpreet Singh, Navjot Singh
  • Journal: IETE Journal of Research
  • Year: 2024
  • Citations: 1