Students' Reading Group
Department of Electrical Engineering, IIT Bombay
  • Graphene: A modern material with unique physical and electrical properties.
  • Fri
    6
    Sep

    Time

    15:00
    • Presenter:
      Ales Tin, Post Doc Fellow
    • Venue: GG302
    • Abstract:
      Graphene is a sheet of two-dimensional materials with a very high electrical conductivity when exposed to an electric field. In a vacuum, it has a mobility that is up to 250 times that of a semiconductor such as Silicon. It also out conducts copper by a thousand times. This is made possible since the conducting quasiparticle (electron/hole) in graphene has a velocity which is relativistic (comparable to the speed of light). In the presentation, we will try to understand these properties of graphene from various perspectives such as the band structure (energy vs momentum). We will also discuss some substituent materials of graphene with more richer properties. In terms of taking graphene out of the lab, the current uses of graphene include batteries, capacitors, transistors
    • Session Coordinator: Radik Rammohan
    • Session Chair: Shashank Kurm
  • Processing and analyzing the biological signals
  • Fri
    30
    Aug

    Time

    11:30
    • Presenter:
      Deepak Berwal, Ph.D. Research Scholar
    • Venue: GG302
    • Abstract:
      In this modern era, health is the real wealth, but we actually don’t have time to think about our health due to daily lifestyle. Lack of exercise and unhealthy food create more problems in the society. There are many biological signals associated with particular body parts such as electrocardiogram (ECG) signal is related to heart and electromyogram (EMG) is related to the muscle contractions etc. These signals can tell us about the health issues related to our body. However, processing these signals are not so straight forward due to various body motion artifacts and external noises coming with these recorded signals. Here, signal processing plays the main role to remove these noises and process it further. Analyzing these signals can also help us to estimate various body parameters and to know more about our body.
    • Session Coordinator: Zeeshan Ali
    • Session Chair: Shashank Kurm
  • Making Machines Learn: Introduction to Deep Learning
  • Wed
    14
    Aug

    Time

    16:00
    • Presenter:
      Deepak Anand Ph.D. Scholar, EE, IITB
    • Venue: EEG 302, GG Bldng.
    • Abstract:
      Deep learning has evolved as a ubiquitous tool for the modern age with applications in the domain of computer vision, natural language processing, reinforcement learning, and advanced robotics. It has emerged to be a vast domain of research and applications. In this talk, we first review the learning problem formulation and its constituents. Next, we traverse through the space of deep learning, providing motivation, and an intuitive understanding of various classes of learning methodologies. We discuss techniques like -- supervised learning, unsupervised learning, transfer learning, self-supervised learning, and popular architectures used in deep learning. It is completely non-technical talk thus no pre-requisite for this talk.
    • Session Coordinator: Sumit Khalapure
    • Session Chair: Sumit Khalapure
    • Presentation Slides