Munesh Singh Chauhan

Munesh Singh Chauhan
Key terms
  • Parallel Computing
  • Deep Learning
  • Compilers
  • Man-Computer symbiosis
  • Machine intelligence
  • Machine Languages
  • Emotion perception in Machines
  • Mindfulness & Well Being
    BIO:

    Munesh is currently a faculty at College of Applied Sciences (CAS), Oman and carries over sixteen years of experience in teaching and research. He holds the position of Head of Software Major and coordinates over the curriculum development of Concurrent programming course in all CAS colleges across Oman. His areas of interest lay in Parallel Computing, GPU-based multicore computing, Large Graph Algorithms, Deep Learning and Compiler Design. Prior, to this, he was an Assistant Professor in Computer Science at Graphic Era University, India. He also served as an IT faculty in the rank of Assistant Professor at APIIT, Staffordshire University (India Center).

    Munesh holds a PhD in Computer Science from Pacific Paher University with his thesis focus on the use of Parallel Computing in Fractal Image Processing. He obtained both his Master in Computer Applications (MCA) and Bachelor in Science (BSc) from New Delhi, India. On the research front he was a Co-Investigator in Oman Government TRC-funded Research grant that investigated the role of parallel machines in accelerating legacy SSM (Storm Surge Model) weather application.

    In addition to teaching Munesh has served under various capacities in promoting community-college participation in the form of workshops, seminars & other allied events. He has been a keynote/ guest speaker at various IT Hackathon events in the domain of Smart Cities, Machine Learning & Parallel Computing.

    Beyond academics, Munesh is a travel enthusiast and has traveled across the length and breadth of the Himalayas.

    RESEARCH INTERESTS:

    Munesh research spans three broad domains related to parallel computing, image processing, and large graph algorithms. The primary focus of all his work pertains to accelerating applications using massively parallel machines. He has worked on the speed-up of diverse applications in the field of chartering drone flight route, fractal image compression, and weather modeling to name the few. Fractal image compression has been one such process which is not amenable for parallel processing because of the high level data-dependence when scouting for self-similarity within an image. His research on using dynamically pipelined GPUs to effectively partition the fractal images has been critically acknowledged.

    He has also written on the role of Artificial Intelligence and Cloud Computing in modern day economies. These technologies have greatly reduced the gestation period for setting up companies but at the same time exposing these firms to increased cyber risk.

    The prime agenda in his research work is to harness the phenomenal computing power of the multicores to solve time critical problems that otherwise would have taken days and weeks to execute. His research work has relevance in domains of Big data, large graph processing, deep learning and computer vision.

    His initial research forays were in the field of compiler optimizations for embedded media processors. Here he proposed register re-design for enhanced compilation of streaming media.

    Of late Munesh has shifted his focus on the machine (deep) learning arena, and is quite inquisitive about machine intelligence and the Man-computer symbiotic relationship. He intends to use his parallel skills to simulate neural networks more akin to the human way and understand the basic fabric of intelligence forward-and-store process.