Shreshth Tuli

Room 407, Huxley Building

180 Queen's Gate

South Kensington

Imperial College London

London, SW7 2AZ

Hits

I am a President's Ph.D. scholar at the Department of Computing, Imperial College London under the supervision of Giuliano Casale and Nick Jennings. My main research areas are Deep Learning, Fog Computing, Internet of Things and Blockchain. Prior to this I was an undergraduate student at the Department of Computer Science and Engineering at Indian Institute of Technology - Delhi, India. I am also a co-founder of Qubit Inc. company which works on providing next generation solutions for industrial problems. I am a national level Kishore Vaigyanik Protsahan Yojana (KVPY) scholarship holder for excellence in science and innovation. I have worked as a visiting researcher at the Cloud Computing and Distributed Systems (CLOUDS) Laboratory, Department of Computing and Information Systems, the University of Melbourne, Australia.

Read more about my research projects here. My publications can be seen here. I have also reviewed papers in several conferences related to parallel and distributed computing like IEEE IM, ICDCS, CCGrid and IPDPS. I have also reviewed for top journals including IEEE IoT, Acess, TCC, TII, TDSC, and am a top reviewer for the Wiley SPE journal. View my CV here.

selected publications

  1. SimTune: Bridging the Simulator Reality Gap for Resource Management in Edge-Cloud Computing
    Tuli, Shreshth, Casale, Giuliano, and Jennings, Nicholas R
    Nature Scientific Reports 2022
  2. SplitPlace: AI Augmented Splitting and Placement of Large-Scale Neural Networks in Mobile Edge Environments
    Tuli, Shreshth, Casale, Giuliano, and Jennings, Nicholas R
    IEEE Transactions on Mobile Computing 2022
  3. CAROL: Confidence-Aware Resilience Model for Edge Federations
    Tuli, Shreshth, Casale, Giuliano, and Jennings, Nicholas R
    IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) (Best Paper Award) 2022
  4. TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data
    Tuli, Shreshth, Casale, Giuliano, and Jennings, Nicholas R
    Proceedings of Very Large Data Bases (VLDB) 2022
  5. PreGAN: Preemptive Migration Prediction Network for Proactive Fault-Tolerant Edge Computing
    Tuli, Shreshth, Casale, Giuliano, and Jennings, Nicholas R
    IEEE INFOCOM (Best Paper Award) 2022
  6. Generative Optimization Networks for Memory Efficient Data Generation
    Tuli, Shreshth, Tuli, Shikhar, Casale, Giuliano, and Jennings, Nicholas R
    NeurIPS 2021 - Workshop on ML for Systems 2021
  7. COSCO: Container Orchestration using Co-Simulation and Gradient Based Optimization for Fog Computing Environments
    Tuli, Shreshth, Poojara, Shivananda, Srirama, Satish, Casale, Giuliano, and Jennings, Nicholas R
    IEEE Transactions on Parallel and Distributed Systems 2021
  8. Predicting the Growth and Trend of COVID-19 Pandemic using Machine Learning and Cloud Computing
    Tuli, Shreshth, Tuli, Shikhar, Tuli, Rakesh, and Gill, Sukhpal Singh
    Internet of Things 2020
  9. Healthfog: An ensemble deep learning based smart healthcare system for automatic diagnosis of heart diseases in integrated iot and fog computing environments
    Tuli, Shreshth, Basumatary, Nipam, Gill, Sukhpal Singh, Kahani, Mohsen, Arya, Rajesh Chand, Wander, Gurpreet Singh, and Buyya, Rajkumar
    Future Generation Computer Systems 2020
  10. Fogbus: A blockchain-based lightweight framework for edge and fog computing
    Tuli, Shreshth, Mahmud, Redowan, Tuli, Shikhar, and Buyya, Rajkumar
    Journal of Systems and Software 2019