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TCS Research & Innovation: Ideas of the Future

 
May 18, 2020

It is common knowledge that technologies like AI, Big Data, Cloud, Data Science and Machine Learning are the buzzwords that dominate the world of information technology today. The technology fraternity is on a relentless quest for advancements in these areas. It is this quest that makes the future of IT research and innovation look brighter than ever before. Findings from our surveys indicate that readers are curious about the happenings in the world of trending technologies, especially on the future scope of data science. Shedding light on this is Ramesh Balaji, Senior Data Scientist at TCS Research and Innovation (R&I). In this Q&A, Ramesh shares his views on TCS’ role in the world of IT research and innovation, with an emphasis on Data Science.

Q: Hi Ramesh. It is always a pleasure talking to you. Let us begin by asking, how is this lockdown treating you?

A: Hi, it’s good connecting with you too. Yes, the lockdown has brought about a paradigm shift in my way of working. But now, with some time having passed, it seems to be normal. I am able to leverage technology to the fullest extent in terms of communication and collaboration. Earlier, there were a few challenges but these have now been resolved. The TCS infrastructure team has worked very hard and has done a commendable job to enable remote working for me and my team. Another challenge that I faced initially with this lockdown was demarcating work and family time. But the situation has improved and currently things are a lot better. I hope we can come out of this lockdown as soon as possible.

Q: You have worn multiple hats as part of various roles at TCS. Could you briefly take us through these and tell us more about your current role?

A: It’s been a great experience working in various roles such as pharmacy SME (subject matter expert), Solution Architect and currently, as a Senior Data Scientist with the TCS Research and Innovation team. My present role is both interesting and challenging as the projects I work on are research-driven and involve looking at technology challenges in meeting business needs. This is a more holistic perspective. My core responsibility is to look at data emerging from various sources, especially from IoT apps that include room sensors, video, smart watch as also conventional data sources. I then determine useful patterns like movement and activity recognition using Machine Learning (ML)/Deep Learning and statistical methodologies.

Q: Among trending technologies, you seem to have researched ML the most. Is that your passion? Also, could you share some instances of ML, especially within a TCS context?

A: Data Science is my passion. Of course, my role also entails predicting and exploring data for which ML is certainly a necessity. It is an exciting area that has come up in the last few years and has greatly changed the whole paradigm of programming. In a typical programming ecosystem, the logic is framed by programmers based on data inputs, and output data is derived. In the ML era, the input and output data are given to the ML algorithm, post which, a model is created based on both inputs and outputs. This model eventually contains the necessary rules/logic.  I am highlighting the example of supervised learning in this instance, where the input data and output labels are given. Of course, the other kind of learning that has improvised a lot is unsupervised learning. Here, you just need to give the input without any output. The ML algorithm learns the patterns from this.

From the application standpoint, one would have seen or heard that ML is pursued in many areas. For example, machine vision challenges such as image processing in terms of object detection, object classification, and object localization, especially in aspects like determining disease types such as cancer. You can also see the application of ML in sequence data such as human translation, sentiment classification, and speech recognition. And finally, in specific use cases like credit card fraud, housing price determination, and so on.

TCS uses ML for its customers as well as for internal projects. I would like to highlight a research project we are working on through our academic partner, Singapore Management University (SMU), for the Singapore government. In this project, we track the movement of elderly people through sensors unobtrusively. We then determine any anomalies in their movements and inform the caretakers/volunteers concerned who swing into action for reaching out to such elderly residents. We analyze the sensor data through ML algorithms in terms of anomalies.

(Read more at: https://www.tcs.com/reimagining-research/the-digital-citizen)

Q: The TCS R&I unit is globally renowned, what are the key factors that make it one of the best?

A: TCS R&I has a well-defined ecosystem in terms of research areas, research programs and the TCS Co-innovation Network (COIN™). It has made significant investments in research areas that are futuristic, and the application of these research areas stem from well-defined research programs. It has got many patents in the areas of AI, infrastructure, data, image processing, big data analytics, e-commerce and so on. TCS R&I works closely with business units in quickly taking a specific solution to the market based on customer requirements. TCS uses the COIN system to harness the innovation taking place within the startup ecosystem, including venture capitalists and academia, which has prestigious institutes like the IITs, UC Berkeley, Carnegie Mellon, Cornell Tech, MIT Media Labs and Singapore Management University (SMU).

Q: What kind of training facilities does TCS have for associates keen on making a mark in trending technologies?

A:  We have state-of-the-art training centers across India. It is important to note that learning is not only classroom-specific, as there are a lot of virtual training programs in online modes. We have also tied up with training institutions like Safari Learning for specific courses.

Q: How does TCS ensure the industry-readiness of its associates about such technologies?

A: TCS has a well-defined and industry-specific domain training programs in areas such as retail, consumer packaged goods (CPG), transportation, and manufacturing. This equips a TCSer with the necessary industry skills to further their upskilling.

Q: On a concluding note, do you have a message for our readers keen on exploring trending technologies?

A: Look out for the best ecosystems in terms of research labs, training programs, skilled mentors, customers or research specific challenges, and innovation partners. These aspects are crucial for innovation and research to thrive. TCS, for one, surely has this ecosystem where TCSers are provided the necessary means, a lively culture, and a conducive set up to nurture their innovative side. This empowers them to further their research-related pursuits.

Ramesh Balaji, is a senior data scientist with a keen focus on smart cities. He loves to understand the interesting patterns of smart people through machine learning techniques. Ramesh has played a key role in assisted living by interpreting the activity patterns of the elderly through data and image recognition forms. He holds a master's degree in computer engineering from California National University for Advanced Studies, USA.