Hi, I'm Gautham
Manuru Prabhu.
Building agentic AI systems that autonomously resolve 20% of supply chain cases at Cisco. ML Researcher at MiCoSys Lab, SJSU. Six peer-reviewed publications.
Engineer. Researcher. Builder.
I design and ship AI systems that move real operational metrics — and publish the science behind them.
Currently
Software Engineer 2, Cisco Systems
Research
MiCoSys Lab, SJSU — TGNNs & GraphML
Based in
Bengaluru, India
Recognition
2× Promoted · SE2 in 18 months
I'm Gautham Manuru Prabhu, a software engineer on Cisco's AI Acceleration team inside Supply Chain Operations. Over 18 months I was double-promoted from intern to SE2 while building agentic AI systems that autonomously handle 20% of incoming cases, cut case volume by 35%, and save roughly 5,000 engineer-hours every quarter.
In parallel, I'm a Research Associate at MiCoSys Lab, San Jose State University, working on efficient training of Temporal Graph Neural Networks over dynamic graphs with millions of edges. Prior research spans quantum ML for cardiovascular disease, retinal-image segmentation, and transformer-based NLP — six peer-reviewed publications across IEEE Access, Springer, Procedia CS, and IOP.
I graduated from Manipal Institute of Technology (B.Tech CSE, 8.91/10, Top 15%) with a minor in Big Data Analytics. I gravitate toward problems that sit between systems engineering, machine learning, and measurable business impact.
FOCUS AREAS
Where I've worked and what I've built.
Intern to SE2 at Cisco in 18 months · Research across 3 institutions · 5 research positions.
Software Engineer 2 — AI Acceleration
CurrentCisco Systems Inc.
- Built agentic AI systems (case resolution, knowledge-base indexing, proactive alerts) that autonomously handle 20% of incoming cases, cut case volume 35%, reduced MTTR 40%, and save ~5,000 engineer-hours per quarter.
- Designed failure analysis and predictive maintenance agents under the Quality Transformation Program, improving upstream defect detection across global manufacturing sites.
- Identified coverage gaps in Paladin edge connectors across 10+ production lines; integrated SplunkAI observability into legacy systems for real-time alerting.
- Leading the research-to-production pipeline for LLM-backed agents — retrieval quality, evaluation, and guardrails end-to-end.
Software Engineer 1 — Supply Chain Ops
Cisco Systems Inc.
- Promoted SE1 → SE2 within 12 months — second promotion on the same team in under 18 months.
- Re-architected legacy failure-analysis workflows into event-driven microservices on Kubernetes using FastAPI, Cassandra, and Redis.
- Built ML anomaly-detection pipelines over manufacturing telemetry with SLA dashboards and alerting (Prometheus + Grafana).
- Hardened the data ingestion and serving layer that the current agentic AI systems run on top of.
SE Intern — Supply Chain Organisation
Cisco Systems Inc.
- Fast-tracked intern → SE1 in 6 months into a full-time role on the AI Acceleration team.
- Automated CI/CD with Jenkins, Docker, and Kubernetes — cut deployment time by 99.45% (6 hours → 2 minutes).
- Won 2nd Runner-Up, Cisco Intern Case Study Competition: NLP-based supplier name standardisation pipeline improving consistency across 50,000+ records (100+ entries).
Selected work and research projects.
Spanning agentic AI, quantum machine learning, disaster response, and data engineering.
SplitSense
Intelligent Splitwise analytics platform
Splitwise provides no deep analytics — users can't see spending patterns, anomalies, or forecasts across shared expenses.
Built a full-stack analytics platform with OAuth 2.0, real-time dashboards, AI-powered balance prediction, anomaly detection, and PDF report generation.
Production deployment on Render with secure OAuth flow, responsive dashboards, and automated insights.
QuCardio
Quantum ML for cardiovascular disease detection
Classical ML models plateau on ECG classification; healthcare needs more accurate, robust diagnostic tools.
Implemented QSVC, Pegasos QSVC, and quanvolution-based QNNs on ECG image datasets — first quantum ML application in this clinical domain.
97% accuracy — 10–14% above classical baselines. MeitY + AWS funded. Published in IEEE Access (Q1), 50+ citations.
VIKAS
Multimodal disaster response system
During disasters, first responders and victims lack a unified, real-time communication layer that handles multiple data modalities simultaneously.
Led a team of 6 to build a real-time platform linking NDRF responders with victims, integrating NLP triage, computer vision, and live geolocation.
Grand Finalist — Smart India Hackathon 2022. Top team from 1,000+ national entries. Published in Springer CCIS.
SatelTensor
Satellite data exploration via tensor decomposition
Satellite telemetry data is high-dimensional; standard ML pipelines struggle to extract meaningful spatial-temporal features efficiently.
Applied Tucker and CP tensor decomposition to satellite image stacks, reducing dimensionality while preserving spatial-temporal structure.
Presented at the TCML Workshop, IISc Bengaluru 2023.
Tools of the trade.
Languages, frameworks, and infrastructure I work with day-to-day — from agentic AI stacks to production microservices.
AI / ML
Languages
Backend & APIs
Data & Storage
DevOps & Cloud
CORE PROFICIENCY
Peer-reviewed research.
Six publications spanning quantum ML, medical imaging, disaster response, and NLP — across IEEE Access, Springer, Procedia CS, and IOP.
Google Scholar profileQuCardio: Application of Quantum Machine Learning for Detection of Cardiovascular Diseases
S. Prabhu, S. Gupta, G. M. Prabhu, A. V. Dhanuka, K. V. Bhat
IEEE Access (Q1) · IEEE Access, vol. 11, pp. 136122–136135, 2023
Addressing Vaccine Misinformation on Social Media by Leveraging Transformers and User Association Dynamics
Rao, C., Prabhu, G.M., Kumar, A.R., Gupta, S., Shetty, N.P.
Procedia Computer Science · Procedia CS, vol. 235, pp. 1803–1813, 2024 (ICMLDE 2023)
VIKAS: A Multimodal Framework to Aid in Effective Disaster Management
Prabhu, G.M., Gupta, T., Srujan, M.V., Soumya, A.R., Palorkar, A., Chowdhury, A.
Springer CCIS · ATIS 2022 — Springer CCIS, vol. 1804, 2023
EyeEncrypt: A Cyber-Secured Framework for Retinal Image Segmentation
Hegde, G., Gupta, S., Prabhu, G.M., Bhandary, S.V.
Springer CCIS · ATIS 2022 — Springer CCIS, vol. 1804, 2023
A Systematic Review of Deep Learning Approaches for Vessel Segmentation in Retinal Fundus Images
Hegde, G., Prabhu, S., Gupta, S., Prabhu, G.M., et al.
IOP J. Physics: Conference Series · IOP J. Physics: Conf. Ser., vol. 2571, pp. 012021, 2023
SatelTensor: Satellite Data Exploration via Tensor Decomposition
Prabhu, G.M., Gupta, S.
TCML Workshop, IISc · Tensor Computation & ML Workshop — IISc Bengaluru, 2023
Recognition, leadership & honours.
Awards spanning national competitions, research recognition, and professional milestones.
Awards & Recognition
2nd Runner-Up — Cisco Intern Case Study Competition
NLP-based Supplier Name Standardisation pipeline across 50,000+ records. 100+ entries.
Thayil Lonappan George Memorial Endowment Award
3rd rank in All India Senior School Certificate Examination (AISSCE) 2020.
Mr. G. Chenthamarakshan Endowment Award
Best Project in Computer Science.
NTSE State Scholar
National Talent Search Examination — Rank 21 out of 151,000+ participants.
Hackathons & Competitions
Grand Finalist — Global Quantum Science & Technology Hackathon
Top 16 teams from 1,600+ entries across 25+ countries — quantum ML track.
Grand Finalist — Smart India Hackathon
Led a team of 6 to build VIKAS, a multimodal disaster-response platform. Top team from 1,000+ national entries.
Leadership
Co-founder & Technical Head — Project Kalpana
Secured $13,000 grant; led 8-person team building an affordable radio-astronomy platform for undergraduates.
General Secretary & Treasurer — ACM Student Chapter, Manipal
Organised 12+ workshops and hackathons; grew chapter participation by 35%.
Technical Head — Astronomy Club of Manipal
Led 5+ technical projects; ran outreach sessions reaching 200+ students.
Schools & Programmes
ACM Winter School on Optimization for ML & OR
Selected participant — IIT Goa.
Summer School on Dynamic Resource Allocation
Center for Networked Intelligence — IISc Bengaluru.
Digital Health Symposium
Selected presentation — IIT Kharagpur.
Let's build something
together.
Open to collaborations on agentic AI, graph ML, systems research, and applied ML. The fastest way to reach me is email.
Say hello© 2026 Gautham Manuru Prabhu
Bengaluru, India