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PhD in Artificial Intelligence
I'm currently an AI consultant at S&P Global. Before, I was the co-founder and CTO of Covent, a startup backed by Founders Factory. A seasoned AI expert with a track record of academic and practical achievements, including research papers, patents, and contributions to product development in startup and corporate settings. I'm passionate about creating innovative solutions at the intersection of AI and technology. Before startup life, I was a Staff Research Scientist at Blue Prism AI Labs in London and a Principal Researcher (Machine Learning) at Bell Labs in Cambridge, UK.
University of Leeds
Doctor of Philosophy, Artificial Intelligence
April 1, 2008 – July 1, 2012
University of Hyderabad
Master of Technology, Artificial Intelligence
July 1, 2004 – July 1, 2006
University of Hyderabad
Master's Degree, Artificial Intelligence
January 1, 2004 – January 1, 2006
JNTU Hyderabad
Bachelor of Technology, Computer Engineering
July 1, 2000 – July 1, 2004
Jawaharlal Nehru Technological University
B.Tech, Computer Science & Engineering
January 1, 2000 – January 1, 2004
S&P Global
AI Consultant
June 1, 2026 – Present
S&P Global
AI Consultant
November 1, 2025 – Present
S&P Global
Artificial Intelligence Consultant
November 1, 2025 – Present
Covent
Scientific Advisor
November 1, 2025 – Present
Remote
Covent
CTO & Cofounder
July 1, 2024 – November 1, 2025
Remote
A2O AI
Co-Founder and CEO
May 1, 2023 – June 1, 2024
Greater London · Hybrid
Applied AI Ventures
Founder
May 1, 2022 – November 1, 2025
Jeevi AI
Co-Founder and CEO
May 1, 2022 – May 1, 2023
London, England, United Kingdom · Remote
Blue Prism
Staff Research Scientist
January 1, 2020 – April 1, 2022
Blue Prism
Senior Research Scientist
January 1, 2019 – January 1, 2020
Blue Prism
Research Development Lead
January 1, 2019 – April 1, 2022
Nokia Bell Labs
Principal Researcher (Machine Learning)
January 1, 2018 – December 1, 2018
Cambridge, United Kingdom
Advanced Research Lab, Nokia TECH
Principal Researcher (Machine Learning)
February 1, 2015 – December 1, 2017
Cambridge, United Kingdom · On-site
University of Leeds
Research Fellow
July 1, 2012 – January 1, 2015
Leeds, United Kingdom
D.E.Shaw & Co, India
Member, Information Technology
July 1, 2006 – March 1, 2008
Hyderabad, India
Spatio-Temporal Representation and Activities for Cognitive Control in Long-Term Scenarios
July 1, 2013 – December 1, 2014
The aim of this project is to produce intelligent mobile robots that are able to run for months in dynamic human environments by providing the robots with the longevity and behavioural robustness necessary to make them truly useful assistants in a wide range of domains. Developing machine learning framework based on graph kernels to consolidate and learn from data gathered using different sensors over a long time from a group of robots operating at different sites.
Robustness by Autonomous Competence Enhancement
January 1, 2012 – December 1, 2014
The overall aim of this project is to develop an artificial cognitive system, embodied by a service robot, able to build a high-level understanding of the world it acts in by storing and exploiting appropriate memories of its experiences. Developing machine learning framework to conceptualize robot experiences from different sources of inputs such as perception, language, textual description etc. using graph kernels and statistical relational learning. Responsibilities also include integration of Leeds' modules with other modules in the consortium, data handling, report writing etc.
Visual Intelligence Grounded In Learning (Mind's Eye Project: DARPA)
September 1, 2010 – February 1, 2012
The Mind's Eye program seeks to develop in machines the capability for visual intelligence: the capability to learn generally applicable and generative representations of action between objects in a scene directly from visual inputs, and then reason over those learned representations. Developed a supervised statistical relational learning framework to learn verb models from videos using Markov Logic Networks for event recognition task. Also developed a video visualization and annotation tool which is light and better in some aspects than the existing popular video annotation tool, VIPER. This tool is now being used by many of the consortia in the Mind's Eye project.
Cognitive and Flexible Learning System Operating Robust Interpretation of Extended Real Scenes by Multi-sensor Datafusion
April 1, 2008 – April 1, 2011
Co-FRIEND aims to design a framework for understanding human activities in real environments, through an artificial cognitive vision system, identifying objects and events, and extracting sense from scene observation. A heterogeneous sensor network, composed of wide angle and PTZ cameras and GPS vehicle monitoring was deployed in Toulouse airport. The scene understanding is assisted by machine learning, providing advanced reasoning capabilities. Developed a supervised relational learning framework to learn event models from real world videos for recognition of events in unseen videos. Responsibilities also include integration of Leeds' modules with other modules in the consortium, data handling, report writing etc. https://www.youtube.com/watch?v=mL88uhxRetw
MBA Essentials
The London School of Economics and Political Science (LSE)
June 24, 2026 – Present
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit for an innovative and fast-paced environment, particularly within AI/ML. Their history of founding and leading startups, coupled with research roles, suggests a proactive, experimental, and results-oriented mindset. The diversity of projects, from academic research in cognitive systems to commercial AI platforms for financial data and well-being, indicates adaptability and a broad interest in applying AI across different domains. The focus on building and deploying AI solutions aligns well with a product-driven culture.
Soft Skills & Operational Fit
The candidate's experience as a co-founder and CEO in multiple AI startups, along with leadership roles at Blue Prism, indicates strong leadership, project management, and strategic thinking. The descriptions suggest an ability to build and manage engineering teams, establish research processes, and drive product development from conception to deployment. The academic and research background also points to strong problem-solving and analytical capabilities. The candidate's involvement in various consortiums and integration tasks suggests good collaboration skills.