This Webinar Series is part of the Government of India "Azadi Ka Amrit Mahotsav" initiative to celebrate and commemorate 75 years of progressive India and the glorious history of it’s people, culture and achievements.
ERNET India is an autonomous scientific society under the Ministry of Electronics and Information Technology. ERNET India not only has made a significant contribution to the emergence of networking in the country, it brought internet to India and supports building up national capabilities in the areas of networking, especially in protocol software engineering and tools for collaboration. ERNET India has developed a great network over the years that provides numerous services to the education and research community.
ERNET India is establishing a Future Tech Learning and Skilling Centre (FTLSC) with a concept of Competency development and skilling of Manpower on future technologies starting with 5G, LiFi, IoT, Data Science, Security, etc. the concept will be an incessant and sustainable effort to cater to current and upcoming future technology skilling demand. The current webinar series will cover the data science and security topics while our earlier webinar was on 5G & Emerging technologies.
The webinar series will also feature a short introduction to a Post Graduate Programme on Data Science and Security (PGPDSS), that ERNET India is planning to launch tentatively in September 2021. The PGPDSS, conceptualised by researchers of Madras Fintech Services Pvt. Ltd (MFS), is a one-year programme for fresh graduates/ master's students/ corporate professionals/ Government officials. It caters to trainees as well as experienced professionals (as an upskilling / reskilling programme). The online training sessions will be conducted over weekends/evenings. Certificates will be issued by ERNET India.
Details of the Webinar Series:
Scheduled Date & Time: 18th - 20th August 2021, 11:30AM - 1:00PM
Webinar is free to attend, but registration is mandatory.
Attendees of this Webinar will have the opportunity to earn E-Certificate
Note: Limited Seats only! Meeting link will be shared to selected registered participants.
Session 1: Information Security Practices
Speaker: Dr Gautham Sekar
(18th August 2021, 11-30AM - 1:00PM IST)
Abstract: We live in a world where we face security and privacy threats on a day-to-day basis. Statistically, one third of all 4-digit credit card PINs lie within a small set of 61 combinations. According to a 2019 survey, 43% of smartphone owners in the USA believe that their device is stealthily recording their conversations. It is not unreasonable for you to fear that your PIN is one of the 61 codes or that your phone is secretly recording what you say. It is also not uncommon to experience password fatigue, having to remember a number of passwords for daily use applications. This talk shall attempt to address these and other similar security / privacy concerns that most of us have. A brief overview of cryptography is included.
The talk will also introduce the audience to Post Graduate Programme on Data Science and Security (PGPDSS), an industry-oriented programme conceptualised by Madras Fintech Services and planned to be launched soon by ERNET India.
Session 2: Machine Learning
Speaker: Dr G. Sivaramakumar
(19th August 2021, 11-30AM - 1:00PM IST)
Abstract: The data revolution of the past two decades has enabled rapid access to information, subject to security regulations. Thereby modern data science emerged and has opened up a tremendous amount of career opportunities. This talk will be presenting some of the basic ideas behind machine learning, which consitutes the core of modern data science. The evolution of various concepts of machine learning and how these are practically used in data science applications are discussed. The cognate discipline of artificial intelligence is also briefly introduced.
Session 3: High Performance, Cloud and Distributed Computing
Speaker: Dr Soumyadeep Bhattacharya
(20th August 2021, 11-30AM - 1:00PM IST)
Abstract: Modern day processors operate at nanosecond-long cycles. However, when processing data with billions of entries, the execution times can easily add up to hours or days. We will look at some processing algorithms which are limited either by data movement or by compute instructions, and how we can leverage cache friendly techniques and vectorisation to reduce execution time. Cloud service providers enable us to rent high performance servers for limited durations to execute such heavy but intermittent workloads. However, due to the shared nature of these cloud services, sensitive data being processed on such systems needs to be secured along its entire lifetime -- from the storage to the processor and back -- using methods in confidential computing. For cases where the data is too large or time consuming to run on a single server, we will look at some parallelisation techniques wherein the task or data is sliced up and distributed across multiple devices, processed in tandem and then gathered back, effectively reducing the execution time.
Dr. Gautham Sekar
Dr. Gautham Sekar is Founder & President of Madras Fintech Services Pvt. Ltd (MFS), Chennai. He holds a B.E.(Hons.) degree in Electronics & Instrumentation Engineering and an M.Sc.(Hons.) in Physics from the Birla Institute of Technology and Science (BITS), Pilani, and a PhD in the area of Cryptology from the KU Leuven, Belgium. He has worked in various capacities at leading academic institutions such as the National University of Singapore, the Indian Statistical Institute, the Institute of Mathematical Sciences (Chennai) and BITS Pilani (Off-Campus). Dr Sekar has (co-)authored 19 peer-reviewed publications, with several appearing in top venues such as Fast Software Encryption, CT-RSA, Information Security Conference, the Journal of Mathematical Cryptology and the Journal of Computer Security. He has served on the technical programme committee of Security Standardisation Research 2015. Aside from lecturing at intensive courses on Information Security, he has been involved in (co-)teaching courses in data science / information security at the Madras School of Economics, BITS Pilani, University of Madras and the Indian Statistical Institute. He is a recipient of the Dr. Ranjit Singh Chauhan Undergraduate Research Award. Dr Sekar has contributed to the security evaluation of the GOST block cipher for ISO/IEC. A secure implementation of a 3GPP encryption standard that he co-developed has been included in the LTE/4G wireless standards.
Dr. Soumyadeep Bhattacharya
Dr. Soumyadeep Bhattacharya is a Visiting Expert at Madras Fintech Services, and an Architect of High Performance Computing & Simulations Platform at SankhyaSutra Labs (subsidiary of Jio Platforms, Reliance Industries). He leads a team of engineers designing optimised software frameworks for massively parallel engineering and scientific simulations on petascale supercomputing infrastructure. He has collaborated with computing teams at Intel, AMD, Nvidia and HPE. He has worked on algorithms for particle detectors at the European Organization for Nuclear Research (CERN), on reliability analysis of hybrid electronic modules at Centum Electronics, on fabrication of thermoelectric nanomaterials at Indian Institute of Science (IISc), and has published his research on statistical physics, cryptography and logistics. In 2017, he collaborated with the Decision Sciences and Information Systems Group of IIM Bangalore and developed algorithms for stock index time-series prediction in automated trading using machine learning techniques. He holds a PhD in Theoretical Physics from the Institute of Mathematical Sciences, Chennai, and a dual degree with M.Sc.(Hons.) Physics and B.E.(Hons.) Electrical & Electronics Engineering from BITS Pilani.
Dr. Sivaramakumar Gopalasamudram
Dr. Gopalasamudram Sivaramakumar is a Senior Manager at Cognizant Technology Solutions (CTS). He holds a B.E. degree in Electronics and Communication Engineering from the College of Engineering, Guindy, an M.E. in Instrument Technology from the Madras Institute of Technology, and a PhD in the field of Adaptive Systems from the Indian Institute of Science. He has worked in the implementation and support of supply chain management systems and data analytics systems in various industrial domains such as paints, food processing, semiconductors, transportation logistics, automotive, health care, hospitality, retail and telecom at Siemens Information Systems, Sherwin-Williams Company and CTS. He has also worked briefly at the Centre for Artificial Intelligence and Robotics (CAIR-DRDO) in Bengaluru. His teaching experience includes courses on machine learning, supply chain modelling, optimisation methods, robust control and statistics. His research papers are in the areas of control theory, supply chain planning and optimisation, and he has served as a member of the editorial board of an international journal called ‘Smart and Sustainable Manufacturing Systems’.