Pradeep Shenoy

AI Researcher

Bengaluru, Karnataka, India18 yrs 2 mos experience

Highly Stable

Key Highlights

Expert in building robust ML systems.
Strong background in cognitive psychology and neuroscience.
Proven track record in large-scale data analysis.

Stackforce AI infers this person is a Machine Learning and Computational Neuroscience expert with a focus on SaaS applications.

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Skills

Core Skills

Machine LearningStatistical ModelingComputational NeuroscienceCognitive PsychologyDatabase Systems

Other Skills

discriminative algorithmsranking algorithmsrepresentation learninglanguage understandingdeep learningonline learningadaptive learningrecommender systemsstochastic control theoryreinforcement learningBayesian networkspsychophysical experimentationfunctional MRI analysisbrain-computer interface technologyimage categorization

About

I am interested in foundational ML/ deep learning, and its applications in building robust, efficient ML systems. I look forward to hearing from academics working on or interested in these areas of research, and phd students with a strong research record. Current work: concept drift, domain generalization, model uncertainty & calibration, spurious correlations, adversarial attacks, compute efficiency, etc., in the context of supervised learning, distillation, language models

Experience

18 yrs 2 mos

Total Experience

4 yrs

Average Tenure

1 yr 11 mos

Current Experience

Google deepmind

Researcher

Jun 2024 – Present · 1 yr 11 mos · Bengaluru, Karnataka, India

Google

Researcher

Mar 2020 – Jun 2024 · 4 yrs 3 mos · Greater Bengaluru Area

Microsoft india

ML Scientist Manager

Jan 2012 – Jan 2020 · 8 yrs · Bengaluru Area, India

I managed teams that built & deployed large-scale user behavior models in sponsored search -- click & conversion prediction, bidding agents, user preferences, query categorization, etc. We used discriminative & ranking algorithms; representation learning, language understanding, & deep learning; online & adaptive learning; recommender systems; among many other techniques.

University of california, san diego

Post-doc Researcher

Jan 2009 – Jan 2012 · 3 yrs · Greater San Diego Area

I developed theoretical & mathematical models for cognitive psychology, neuroscience, psychiatry. Techniques included stochastic control theory; reinforcement learning; Bayesian networks & inference; psychophysical experimentation; functional MRI analysis & modeling.
Published articles in J. Neuroscience, Frontiers in Neuroscience, NIPS, CogSci, etc.

Microsoft

Research Intern

Jan 2007 – Jan 2007 · 0 mo · Redmond

Human-aided computing. Used brain-computer interface technology & passive human responses to improve image categorization.
Published articles in ACM CHI & CVPR.

Fraunhofer-gesellschaft

Visiting Researcher

Jan 2005 – Jan 2005 · 0 mo · Berlin Area, Germany

I worked on adaptive brain-computer interfaces, modeling nonstationarity in human control using EEG signals.
Results published in J. Neural Engg.

Bell labs

Member of Technical Staff

Jan 1999 – Jan 2000 · 1 yr · Murray Hill, NJ

Database systems research. I worked on problems in semistructured data indexing; in-memory databases; on-demand navigational access to XML views; approximate query answering.
Published articles in VLDB & ICDE.