Gandhinagar: Indian Institute of Technology Gandhinagar (IITGN) hosted the Association for Computing Machinery- India (ACM-India)’s annual event 2020 on February 15. The event saw an overwhelming participation of more than 1200 students, researchers, faculty members, and professionals of computer science and allied areas from all over the country. The prestigious event was graced by Prof Cherri Pancake, President of ACM; Prof Abhiram Ranade, President of ACM India; ACM Award winners as speakers; Shri Abhishek Singh (IAS), President & Chief Executive Officer of National e-Governance Division; and ACM-India Office Bearers.

ACM India organises this annual flagship event to discuss trends in science and technology, and to celebrate ACM’s spirit and India’s accomplishments in computing. At the outset of the event, Prof Harish P M, Dean, Students Affairs, IITGN, provided an overview of IITGN’s core values and culture and the innovative and inclusive environment it offers to its community and visitors.

Prof Cherri Pancake, President of ACM, presented ACM report and introduced participants with the various activities of ACM for computing professionals, researchers and educators, to advance computing as a science and a profession. Prof Abhiram Ranade, President of ACM India, presented ACM India report and highlighted ACM India Council’s various initiatives for research, education, continuing education for professionals, industry-academia linkages, gender issues, and so on. He also introduced ACM India’s CSPathshala, a Computational Thinking Curriculum for Std I to Std VIII, that has reached more than 3 lakh students, 1100 schools, 5400 teachers, in a bid to do their bit for localisation of the subject. On the occasion, ACM-India Doctoral Dissertation Awards 2020 and Best Chapter Awards 2020 were also presented to the winners.

This was followed by four engaging talks by eminent experts and ACM Turing Award winners. Prof Yann LeCun, a French-American computer scientist from the New York University, Chief AI Scientist at Facebook and 2018 ACM Turing Award Winner, who works primarily in the fields of machine learning, computer vision, mobile robotics and computational neuroscience, delivered a talk on ‘Self-Supervised Learning: the Next Step in AI’. He described the brain as the inspiration for initiation of earliest work in Deep Learning, a system innovation that has caused revolutions in computer perception, image synthesis, natural language understanding, and control. He went on to explain various models, aspects, and experiments of Convolutional Network (ConvNets) Architecture and its application to recognize multiple objects, faces and figures, including billions of photos uploaded on Facebook every day that go through a handful of ConvNets within seconds for segmentation.

Elaborating further Prof Yann LeCun said that 3D ConvNet can be used for medical image analysis, breast cancer detection, faster MRI, in Physics and in Astrophysics to predict the cosmological structure formation. He said that Supervised Deep Learning works well when you have data. He also gave examples of research experiments where Deep Learning can save lives, by deploying automated emergency braking systems, by detecting tumour in mammograms, and by filtering online content like hate speech, calls for violence, weapon sales etc. However, he went on to explain that in contrast to the humans and animals, who largely learn vast amounts of knowledge about the world quickly by mere observation and occasional actions, successes in Deep Learning techniques rely on supervised learning, where the machine is trained on a large number of examples augmented by human-provided interpretations. Prediction is the essence of intelligence, and so, Self-Supervised Learning (SSL) signifies to train a machine to predict missing information by generally ‘filling in the blanks’. For example, predicting missing words in a text, occulted parts of an image, future frames in a video. He also described a number of applications of self-supervised learning, including using a forward video prediction model to train autonomous cars to drive defensively by learning to predict how other cars around you will move.

Concluding his talk he said, “Self-Supervised Learning is the future of Artificial Intelligence (AI). Human intelligence is very very specialised and forward. Artificial General Intelligence is a misnomer, so let’s talk about human intelligence, it is a more interesting concept. Theory often follows inventions. We need to find out the theory behind intelligence, learning. Everything else is an inspiration from biology.”

Prof Susanne Albers, a German theoretical computer scientist from the Technische Universität München and a recipient of the Gottfried Wilhelm Leibniz Prize, talked about ‘Algorithms Beyond the Worst Case’. She explained various theories of worst-case analysis for algorithm performance, various aspects of online paging, and different analytical approaches and its applications in computer science.

Prof Shwetak Patel, an American computer scientist and entrepreneur from the University of Washington, with familial roots in Gujarat, and Winner of 2018 ACM Prize in Computing, best known for developing novel sensing solutions and global computing, spoke about ‘New Ways of Thinking of the Mobile Phone for Healthcare’. He described a collection of research projects conducted with his clinical collaborators that utilise different sensors on mobile devices (e.g. microphones, cameras, accelerometers, etc) in new ways to enable the screening, self-management and longitudinal study of various diseases. “Point of care diagnostics is one particular major revolution that happened in the healthcare field. There are several opportunities for diagnostics using mobile phones, including pulmonary, blood screening, cardiovascular, and disease-specific”, he said. He went on to introduce some of the apps and services invented by them using simple mobile phone sensors to measure lung function, detecting and studying cough, tuberculosis, newborn jaundice, osteoporosis, and so on. He underscored the potential advances in health and clinical science through the convergence of sensing, machine learning, and human-computer interaction. He advised students that this is an unprecedented time to work towards major global problems.

In the end, Prof M Balakrishnan, a Professor in the Department of Computer Science & Engineering at IIT Delhi, Founding Vice-Chancellor at Satya Bharti Institute of Technology and ACM Eugene L Lawler Award Winner, gave a talk about ‘Assistive Technology Solutions for Mobility & Education of Visually Impaired’. He presented the work of ASSISTECH, IIT Delhi in developing solutions, including a SmartCane, Bus Finding device ‘OnBoard’, Tactile Diagrams, and braille keyboard prototypes ‘Dot Book’, aimed at addressing challenges of independent mobility and education of visually impaired in India and other low-income countries. He stressed that assistive technology design for India needs to be user-centric, affordable and infrastructure-friendly. Further, he also talked about the challenges in translational research and its dissemination in this area.

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Gandhinagar: Indian Institute of Technology Gandhinagar (IITGN) organised the eighth Roddam Narasimha Distinguished Lecture on August 5, 2019, on the subject ‘Data Science: The Good, the Bad and the Ugly’. Prof Jayant R Haritsa, a data Scientist and Professor in the Department of Computational & Data Sciences at the Indian Institute of Science, Bangalore (IISc Bangalore), delivered the lecture and helped the audience decipher various aspects of data science.

During his talk, Prof Jayant R Haritsa gave background and various examples of use of data science by various sectors, government entities and corporate companies. Talking about the good aspects of data science first, Prof Haritsa talked about some of the sectors where companies are utilising the power of data science and analytics to understand their customer preferences and provide them better choices and advanced services. He gave an example of power sector where deployment of a condition monitoring and predictive analytics solutions helps the power company’s managers in taking informed maintenance decisions quickly and hence saves huge losses and also improves service delivery.

Explaining this, he said, “Data science is trying to look into the future. It proves to be a win-win situation for the customers as well as for the companies. Data science can play a very direct and positive role for the services in transport, consumer electronics, banking, power sectors etc. There is scope for data science to do a lot of public good and at the same time also help the corporate world in terms of better services and more projects.”

He then introduced the audience to some lesser known perils and realities of data science. He also informed that only a few enterprises really have curated big data, but many others claim to have it too because of the much created hype around it. Talking about some of the interesting methodological issues of data science, Prof Haritsa said, “Big data encourages to ask the wrong questions. People get big answers to such questions, but coming up with the right questions is more difficult than coming up with the right answers. Nowadays people tend to compare incomparable things because of the bid data available on the web.” The audience was amused with an example of one such big data analysis which claimed to calculate the age of a musician depending on the kind of music genre he/she plays, but the statistical and probability subtleties are being lost in the big picture.

He also gave some examples of the design errors in the implementations of big data systems and how it can lead to the breakdown of critical web infrastructure. Explaining the limitations of data science systems he said, “Everybody loves big data systems but you can not test them. So, many big data systems will be prone to failure by definition because they are too difficult to test due to the large scale of the data.”

Prof Haritsa also pointed out to its methodological misuse that, “Data science can be used to bend us to preconceived biases and reinforce them. The directed behaviour is being made possible because of data science, through news feed algorithms to selectively push an opinion, confuse the issues with fake news, and apply peer pressure on social media.”

In his concluding remarks Prof Haritsa emphasised the ideal way to use data science for the benefit of mankind and said, “It is very important to use data science, it should be a tool of last resort, not the first, to validate a hypothesis, and should be used as a support tool, not substitute, for domain expertise. Because data science, like nuclear power, has enormous potential for benefiting mankind, if used with care, otherwise it has equally destructive power for ruining the society.”

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