Past Events
Past Events
Embedded Files
- Technical session on GNSS
Title: Remote Sensing of Ionospheric Perturbations Induced by Earthquakes and Tsunamis Using GNSS
Speaker: Dr. Sithartha Muthu Vijayan, senior scientist, CSIR Fourth Paradigm Institute.
Date: Apr 8,2022
Mode: Online
Abstract: It is well-known that acoustic and gravity waves generated by earthquakes and tsunamis grow in amplitude during their vertical propagation in the atmosphere and perturb the ionospheric plasma. However, there were limitations in observing such perturbations using conventional observational techniques. The advent of Global Navigation Satellite Systems (GNSS) changed the scenario. The number of dual-frequency GNSS receivers established – both in space and ground – for various scientific and navigational purposes, and the massive earthquakes and tsunamis that shook the Earth in the last two decades provided an unprecedented opportunity to detect and study the coseismic and tsunamigenic ionospheric perturbations. Eventually, these studies opened up a new area of research called ionospheric seismology. Being in its infancy, ionospheric seismology demands improvements in both theoretical as well as observational research to obtain maturity. Upon its maturity, ionospheric seismology will make the remote sensing of earthquakes and other planetary quakes possible in addition to filling the crucial gaps in conventional seismology. Further, this multidisciplinary research field is opening up many research opportunities in the domains of ionospheric physics, geodesy, and geophysics. This talk covers the fundamentals and current status of ionospheric seismology including ionosphere-based tsunami early warning, methods for detecting ionospheric perturbations using GNSS, emerging opportunities, and challenges ahead.
- 1-day MATLAB workshop on Deep Learning by Mathworks
Title: 1-day MATLAB workshop on Deep Learning by Mathworks
Conducted by: Mathworks
Date: May 5, 2022, Thursday (10:00 AM to 4:30 PM)
Mode: Offline
Highlights: IEEE SB IITI along with IEEE GRSS conducted a 1-day MATLAB workshop on Deep Learning by Mathworks-IEEE IITI (May 5, 2022). The event garnered a huge response, but the seats were limited to 30 teams to provide cloud access, thus we limited the registrations to only 50 members.
IEEE student Branch IIT Indore was glad to announce the 1-day online workshop on MATLAB conducted by MATHWORKS at IIT Indore. The schedule of the workshop was as follows,
⦁ Introduction to MATLAB,
⦁ Image processing with MATLAB
⦁ Deep learning with MATLAB
The resources for GPU were provided for the registered participants. IEEE SB IITI Certificates were also provided for the participants.
- IEEE IITI celebrates World Nature Conservation Day
Title: IEEE IITI celebrates World Nature Conservation Day
Date: Aug 4, 2022
Mode: Offline
Highlights: IEEE Student branch IITI, Ap-S chapter, and GRSS chapter IITI celebrated world nature conservation day on Aug 4 2022 with a digital image contest and quiz competition open to all students. The quiz took place offline, there were quite good interactive teams and it was fun conducting quizzes with pressing buzzers to answer questions each time. The quiz had 2 rounds, round 1 and round 2, and the best scorer was selected as the winner. We presented IEEE goodies to all participants.
- Webinar on "Applications of Calcutta University Active Phased Array for Diverse Research Activities"
Speaker Bio: P. Nandakumar is currently a Project Engineer at the University of Calcutta ST Radar Facility. He completed his Master of Technology course in Signal Processing at Sri Venkateswara University, Tirupati, Andhra Pradesh in 2015 and joined the National Atmospheric Research Laboratory (NARL), Gadanki, Titupati as a Technical Assistant in 2016. Later he joined the RGM College of Engineering and Technology, Nandyal, Andhra Pradesh as an Assistant Professor during the period 2016-18. His current research interests are design, development and validation of Radar systems and subsystems, active phased array Radars, VHF phased array antennas, RF systems, Radar signal Processing and atmospheric data processing. He is an active IEEE member.
Title: Applications of Calcutta University Active Phased Array for Diverse Research Activities
Date: Aug 30, 2022 (15:00 IST)
Mode: Online
Abstract: The session covers mainly the technical details of the University of Calcutta ST Radar Project at Ionosphere Field Station, Haringhata. The uniqueness of the Radar in terms of its location, operating frequency and other system specifications will be highlighted, this being the only such radar in the entire eastern and north-eastern India as well as the South-East Asian longitude sector. The process of setting up this major research facility along with the strong scientific motivations will be outlined. Some of the initial observations with this VHF active phased ST Radar during Indian summer monsoon, periods of atmospheric turbulence like the cyclone Amphan as well as studies on boundary layer and ionosphere will be presented. Finally, the potential of this radar to develop an ecosystem wherein researchers from varying fields like Astronomy, Antennas, Solid State Devices and Digital Signal Processing, to name a few, could converge and contribute will be indicated.
- Tech Talks- 2nd edition of Annual webinar series
Speaker Bio: Dr. Zachary Labe is a postdoc at NOAA’s Geophysical Fluid Dynamics Laboratory and the Atmospheric and Oceanic Sciences Program at Princeton University. His current research interests explore the intersection of climate variability, extreme events, decadal prediction, and explainable machine learning methods. In addition to academic research, he is very passionate about improving science communication, accessibility, and outreach through engaging climate change visualizations.
Title: Machine learning for evaluating climate model projections
Date: Dec 7, 2022, 6:30 pm | (UTC+05:30) Chennai, Kolkata, Mumbai, New Delhi
Mode: Online
Abstract: The popularity of machine learning methods, such as neural networks, is rapidly expanding in nearly all areas of science. The interest in these tools also coincides with a growing influx of big data and the need for high efficiency in solving predication problems. However, there is also some hesitancy in adopting the use of neural networks due to concerns about their reliability, reproducibility, and interpretability.
In climate science, we often consider signal-to-noise problems to help disentangle human- caused climate change from natural variability. These applications typically involve complicated relationships between different feedbacks at play in the ocean, cryosphere, land, and atmosphere. Recent work has shown that neural networks can be a promising tool for solving these types of statistical problems when combined with explainability techniques developed by the fields of computer science and image processing. Interestingly, these methods have revealed that neural networks often leverage regional patterns of climate change in order to make their predictions. In this webinar, I will share examples from climate science that use a few of these visualization methods peer into the “black box” of neural networks, which help us to better understand their decision-making process while also learning new science. The same machine learning visualization methods can be easily adapted for a wide variety of applications and other scientific fields of study.
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