Joy Bose

Hi and welcome to my home page.
I am Joy Bose. I am a Data Scientist currently working at Ericsson, Bangalore.
I graduated in 2007 with a Ph.D in the APT research group at the Department of Computer Science in the University of Manchester, UK. My supervisors were Steve Furber and Jon Shapiro. Magnus Rattray was my advisor. During my Phd I was working as part of a project to build hardware and software models of scalable neural network architectures and investigate their properties and potential applications. I am involved mainly with the software aspects of the same. The aim of my PhD research is to understand how reliable systems can be built out of unreliable spiking neural components, by taking the example of sequence learning. I graduated with my PhD on 11 December 2007.
Since my PhD graduation I have been working in industry, most recently at Ericsson, previously at Embibe, Microsoft, Samsung R&D in Bangalore and DAI Limited in Stockport. My recent work has concentrated on various areas related to ML models and Generative AI in telecom domain. My Samsung work was about web browsers and improving the user experience when browsing the web, as well as understanding the user based on various parameters, building a user profile and recommending relevant services to the user.
My career began with algorithms and code, but it has taken me far beyond, into classrooms, counselling, and contemplative spaces. With a PhD in Computer Science and over 15 years of experience in the tech industry, I’ve spent much of my professional life navigating the evolving frontiers of software engineering, machine learning, and artificial intelligence.
During my PhD in Computer Science in Manchester, I contributed to spiking neural networks theory and how to build more complex systems using spiking neuronms as building blocks. This foundation led to roles across the UK and India, where I evolved from a hands-on software engineer to a research-driven technologist. Whether at Microsoft building machine learning tools for browsers, at Samsung developing EEG detected emotion sensitive web features and bias-detecting news systems, or now at Ericsson pioneering LLM-based tools for telecom automation, my focus has remained on building intelligent systems that matter. I have always had a strong research bias.
Throughout my career, I have worked on over a dozen machine learning projects, from educational analytics to radio inefficiency detection, financial variance classification, and automated code review generation with LLMs. I have authored research papers across global conferences and contributed to innovations recognized by patent offices in the US, Europe and India.
But somewhere along the way, I also began to question the limits of technology alone. I saw how AI could scale human decisions, but also scale human biases. I realized that while we were engineering intelligence, we were often neglecting the motivations behind decision making. This questioning drew me toward a different kind of learning, one that led to an MSc in Psychology and Neuroscience of Mental Health from King’s College London. This was also partly inspired by themes in Computer Science such as reinforcement learning and memory models.
What began as curiosity became a personal transformation. I now integrate insights from psychology, ethics, and contemplative traditions like meditation into my thinking about AI, fairness, and the future of work. I've written about the psychology of mental health, where we are going in tech, ethics of AI and the deeper questions around automation, identity, and meaning. I also explore how systems, technological or societal, shape our sense of agency.
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