About Me
Machine Learning Researcher with 4 years of hands-on experience in AI development, focused on computer vision applications and model optimisation. Combining technical expertise with a strategic approach to deliver high-performance state-of-the-art ML solutions that bridge the gap between research innovations and practical implementations.
Computer Vision
90%High Performance Computing
85%Cloud Computing
80%Services
AI/ML Consultation
Helping start ups perform feasibility study and design end-to-end state of the art Machine Learning solutions.
Cloud Computing
Helping small scale businesses and individuals set-up custom cloud based solutions at an affordable pricing.
Design Thinking Workshop
Helping teams and individuals understand and utilise design thinking to create user-centric solutions.
Looking for a custom job? Click here to contact me! 👋
Experience
Researcher, Fujitsu Researcher of Europe, UK
• Architected an end-to-end agentic AI reasoning system using LangGraph and
LangChain, enabling auditable, step-by-step explainability for Graph Neural
Network predictions; adopted as the foundational framework for agentic AI
initiatives across 3 research labs, 5 teams, and 40+ researchers.
• Accelerated a computational pathology pipeline for breast cancer subtyping by
50×, reducing whole-slide image processing time from 60–100 hours to 1–2 hours
on NVIDIA A100/H100 GPUs.
• Conducted systematic GPU and CPU profiling with NVIDIA Nsight Systems,
improving GPU utilisation from 40% to 74% and optimising CPU-side graph
construction from H&E-stained whole-slide images; estimated to save £100K+ in
compute per breast cancer dataset.
• Led optimisation of a technology currently under evaluation for collaboration
with a leading international cancer research centre, supporting scalable
AI-driven pathology research.
• Designed and executed experimental frameworks for Out-of-Distribution
detection on synthetic water-body datasets, improving mean IoU from 0.824 to
0.835 and pixel accuracy from 0.934 to 0.939 across 9 segmentation
architectures.
• Published co-author research in Nature Scientific Data based on synthetic
dataset generation and segmentation benchmarking for water-body detection.
• Developed cancer and healthy tissue detection modules for an end-to-end breast
cancer classification pipeline, improving patch-level detection accuracy on H&E
whole-slide images.
• Collaborated across 4 research labs and 5+ cross-functional teams to deliver
machine learning solutions across medical imaging, graph-based AI, and agentic
systems.
• Maintained and upgraded shared AI infrastructure, including GPU clusters,
development tooling, and runtime environments, supporting research teams across
multiple AI initiatives.
Analyst, DSCI Hyderabad
• Led the efforts in building state of the art cybersecurity research centre in
Hyderabad.
• Drafted the India's National Cybersecurity Strategy 2020 recommandations for
the Gov. of Telengana.
• Organised over 15 large scale workshops and seminars.
• Presented on utilisation of AI in Cybersecurity to over 200 industry
leaders.
Undergraduate Intern, Intel Bangalore
• Worked on optimising ResNeXt algorithm for Xe HPC Graphics Architecture.
• Improved performance by 40% by utilising Accelerated linear algebra and
optimising memory footprint by computing the best path.
MSc. Computer Vision, Robotics and Machine Learning
University of Surrey, Guildford, UK.
Course: Computer Vision and Pattern Recognition, Image processing and Deep
Learning, Robotics, AI and AI Programming, Internet of Things, Satellite Remote
Sensing, Speech & Audio Processing & Recognition.
B.Tech. Computer Science
Mahindra École Centrale, Hyderabad, India.
Course: Introduction to Computer Science, Data Structures and Algo, Design
Thinking, Computer Arcitecture, Microprocessors, Embedded Systems, Artificial
Intelligence, Cloud computing.
Intermediate(CBSE)
Sri Chaitanya CT, Bangalore, India.
Get In Touch
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