Abhinav Ganesan

AI Researcher

Bengaluru, Karnataka, India16 yrs 2 mos experience

Highly Stable

Key Highlights

Led ML initiatives delivering significant business impact.
Proven track record in collaboration with cross-functional teams.
Published 20+ papers in peer-reviewed conferences.

Stackforce AI infers this person is a Machine Learning expert in Food Delivery and Telecommunications industries.

Contact

Skills

Core Skills

Machine LearningDeep LearningSolution Architecture

Other Skills

AlgorithmsApache SparkCoding TheoryData AnalysisInformation TheoryLTELaTeXMIMOML OpsMatlabNetwork CodingProduct ManagementPyTorchPythonSignal Processing

About

Experienced leader in Applied Machine Learning with ∼15 years of industry and academic experience. At Swiggy, I lead the Applied Science efforts for Location Intelligence, Relevance & Personalization for the storefronts of Food Delivery and Dineout business lines. I built and lead a high-performing team of Applied Scientists, and own ML/DL models on the cloud, delivering an incremental gross order value of USD X M annually. These are among the highest throughput and lowest latency systems in the Swiggy ecosystem. I am equally at ease developing research-backed foundational ML solutions and leveraging off-the-shelf models to drive business value. I have a proven track record in collaborating with Business leaders, Product Managers, Data Analysts, Software Engineers, and aligning machine learning strategies with key business objectives. In the past, I worked on ADAS systems leveraging Computer Vision on the edge devices for building high definition (HD) maps and driver assistance alerts at Netradyne Inc. I also productionized statistically robust algorithms for noisy wireless channels working at -15dB signal-to-noise ratios (SNR) at Qualcomm Inc. I was AIR 2 in GATE ’09 leading to a PhD in Applied Statistics from IISc, Bangalore, and postdoc from Chinese University of Hong Kong. I have 20+ papers published in peer-reviewed international conferences on Machine Learning and Applied Statistics. See here: https://dblp.org/pid/46/10835.html

Experience

Adobe

Senior ML Engineer

May 2025 – Present · 10 mos · Bengaluru, Karnataka, India

Ads portfolio optimisation

Swiggy

Senior Manager - Applied Science

Dec 2019 – May 2025 · 5 yrs 5 mos · Greater Bengaluru Area

Spearheaded zero-to-one foundational ML initiatives for Swiggy Maps, improving two-wheeler distance and address accuracy by training models on billions of GPS traces, millions of Open Street Map (OSM) road segments, and addresses data. These led to a combined impact of USD X M travel cost savings, multifold increase in operational efficiency, and Y % reduction in incorrect location-related cancellations.
Architected the roadmap and execution of real-time personalized ranking models for restaurant and menu-item ranking, driving operational excellence and resulting in GOV of USD X M annually across Food Delivery and Dineout business lines. I introduced advanced algorithms, including bandit-based and Pareto-optimal approaches to drive relevance improvements solving for user preferences, all leading to significant business impact.
Led the development of a Payments Routing Platform, optimizing payment-gateway routing based on success rates and Merchant Discount Rates using Bandit algorithms. This led to incremental GMV of USD X M and payment-gateway cost savings of USD Y K annually for Food, Grocery Delivery, and Dineout business lines.
Publications: https://dblp.org/pid/46/10835.html

Deep LearningMachine LearningSolution ArchitectureProduct ManagementML OpsApache Spark

Netradyne

Staff Research Engineer

Apr 2018 – Dec 2019 · 1 yr 8 mos · Greater Bengaluru Area

I architected and productionized several foundational ML/DL components of Advanced Driver Assis-
tance System (ADAS) on the edge devices at Netradyne Inc leading to significant improvements in
coverage/precision of unsafe driving behaviour and accuracy of HD maps.

Deep Learning

Qualcomm

Senior Systems Engineer

Jul 2015 – Mar 2018 · 2 yrs 8 mos · Bengaluru Area, India

Designed & implemented memory-efficient base-station synchronization algorithm with error-rate guarantees for time and frequency synchronization for -15 dB SNR operation of 5G modems.

The chinese university of hong kong

Post Doctoral Fellow

May 2014 – Jun 2015 · 1 yr 1 mo · Hong Kong SAR

Conducted research in statistically optimal algorithms for mining sparse information from big data leading to 2 Tier-1 conference and a journal publication in Information Theory.

Indian institute of science

2 roles

Research Associate

Feb 2014 – Apr 2014 · 2 mos

Ph.D Scholar

Aug 2009 – Jan 2014 · 4 yrs 5 mos

My doctoral thesis titled, "Precoding for Interference Management in Wireless and Wireline Networks," dealt with precoding in interference networks with some practical constraints imposed by the use of finite input constellations, propagation delays, multipath, and channel state availability at the transmitters. Different configurations of interference networks like Gaussian interference channels, wireless X-networks and wireline interference channels were analyzed with the above mentioned practical constraints. I used tools from information theory, MIMO wireless communication, and network coding in my doctoral research.