Raghav Chalapathy, PhD

I like to focus on Applied AI: Build.Ship.Scale Apps for the Agentic Economy

2022 - Current

I am a Staff Data Scientist at Walmart Global Tech (Walmart Labs), partnering with senior executives, product, and business teams to take ideas from research to production. Highlights of my work here:

Evaluating item-matching techniques and algorithms.
Building prototypes and proofs of concept in collaboration with leadership, product, and business stakeholders.
Developing safety-net algorithms to ensure adequate safety stock across Geo Locations (Walmart stores).
Contributing to the Next-Generation Geo-Demand Platform.

My current focus is on Applied AI — leveraging Generative AI and Agentic AI to build, deploy, and scale solutions that aid assortment placement and demand forecasting for new geographic locations.

2019 - 2022

Research Fellow at CSIRO's Data61 (Transport & Analytics Group, Data City Team). I built anomaly detection models for structural health monitoring and incident detection across transport networks (client: Sydney Harbour Bridge, NSW Transport), models for HVAC load and solar energy generation forecasting in regional hospitals, and supervised a PhD student on concept drift and anomaly detection in data streams.

2015 - 2019

Data Scientist / Research Officer at the NSW Ministry of Health. I applied data mining, machine learning and NLP to uncover service-usage patterns and investigate low-acuity care delivered by NSW Ambulance and Emergency departments. My analysis revealed ~17% of transported patients presented with low-risk back pain, highlighting the need for safer, cost-effective community models of care.

2015 - 2019

PhD, Computer Science at the University of Sydney. My research focused on deep learning for anomaly detection. Along the way I tutored Master of Data Science courses and was Project Manager / Examiner for the COMP5703 Capstone Projects course.

2011 - 2013

MS in Information Science & Security at the Illinois Institute of Technology, USA.

2006 - 2015

Senior Technical Leader at Huawei Technologies, Bangalore. I built ML classification models to identify software failures, conducted software security audits, and led a team of 5 to develop and automate tooling for software and security testing.

2000 - 2004

B.E. in Telecommunication Engineering at R.V. College of Engineering, Bangalore, India.

bio

Raghav Chalapathy is a Staff Data Scientist at Walmart Global Tech. His work focuses on deep learning for anomaly detection, natural language processing, and time-series forecasting. He earned his PhD from the University of Sydney and has worked across industry and research at CSIRO's Data61, the NSW Ministry of Health, and Huawei Technologies. He was part of the Walmart Applied AI team that won both the Edelman and INFORMS awards in 2023. He holds CISSP and Cloudera Certified Data Scientist certifications, and is passionate about teaching AI — running the Applied AI Fab community and a Substack.

featured videos

Hands-on tutorials from my YouTube channel. This is the KDD 2020 series — Robust Deep Learning Methods for Anomaly Detection (watch the full playlist).

KDD 2020 Tutorial — Part 1: Intro to Robust Deep Anomaly Detection

KDD 2020 Tutorial — Part 2: Deep Anomaly Detection Methods

KDD 2020 Tutorial — Part 3: Robust Autoencoders in Practice

KDD 2020 Tutorial — Part 4: Hands-On Code Walkthrough

from my substack

I write about Causal AI, decision intelligence, and agentic systems at the Applied AI Fab.

The Future of Decision-Making with Causal AI

Why Decision Intelligence Is the Next Frontier

Building a Community Around Causal Intelligence

Why Communities Matter in Emerging Fields

From Data to Decisions: How Causal Thinking Improves AI Systems

Why Better Data Alone Is Not Enough

The Rise of Causal AI: Why It Matters Now

Understanding the Shift from Correlation to Causation

Join the Applied AI Fab community

Learn, build, and ship AI & agentic systems with me. Subscribe for essays and join the community to go hands-on.

Read on Substack

Join on Skool

awards & achievements

Part of the Applied AI team at Walmart Global Tech winning both the Edelman and INFORMS awards (April 2023).
Bronze Medal, Academic Track Contributions — Global AI Challenge (Feb 2022).
Intelligent Transport System (ITS) Australia National Award (Dec 2020).
Certifications: CISSP (ISC²) and Cloudera Certified Data Scientist.

selected publications

Applied Machine Learning Methods for Time Series Forecasting

CIKM 2022

Linsey Pang, Wei Liu, Lingfei Wu, Kexin Xie, Stephen Guo, Raghav Chalapathy

Dual-Stage Bayesian Sequence to Sequence Embeddings for Energy Demand Forecasting

PAKDD 2021

Frances Cameron-Muller, Dilusha Weeraddana, Raghavendra Chalapathy, Nguyen Lu Dang Khoa

Robust Deep Anomaly Detection (Hands-On Workshop)

KDD 2020

Raghavendra Chalapathy, Nguyen Lu Dang Khoa, Sanjay Chawla

Deep Learning for Anomaly Detection: A Survey

arXiv:1901.03407 (2019)

Raghavendra Chalapathy, Sanjay Chawla

For more publications and citations, see my Google Scholar profile.

misc unsorted

I post AI walkthroughs on my YouTube channel — see this playlist.
I write at the Applied AI Fab Substack.
I run the Applied AI Fab community on Skool.
Code on GitHub, connect on LinkedIn.
Member of the AI & citizen science group at the Australian Citizen Science Association, and of Rational AI University — a non-profit teaching AI/ML skills to low-income and underserved kids in India.