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Founder & CEO, xSpecies AI | Building Dexterous Intelligence for Humanoid Robots | Former Director of AI, Ola Electric | Robotics, Embodied AI & Autonomous Systems
I am the Founder and CEO of xSpecies AI, where we are building dexterous intelligence for robots operating in human-centric environments. Our work spans dexterous robotic hands, tactile and proprioceptive sensing, humanoid robotic platforms, teleoperation, and embodied AI models that enable robots to perceive, learn, manipulate objects, and interact safely with the physical world. Before founding xSpecies AI, I served as Director and Head of AI at Ola Electric, where I led teams working across autonomous driving, robotics, computer vision, machine learning, smart mobility, voice intelligence, and video analytics. Over more than two decades, I have worked at the intersection of systems engineering, data, artificial intelligence, and robotics. My career has evolved from building system software on UNIX platforms and architecting large-scale cloud and big-data systems to developing machine learning systems and leading applied AI and robotics programs. Earlier in my career, I worked with Apple as a Big Data Architect, contributing to Hadoop-based enterprise data platforms and large-scale data applications. My broader technical experience includes distributed systems, cloud computing, performance engineering, machine learning, deep learning, computer vision, autonomous systems, and robot intelligence. I am an inventor and researcher with more than 12 patent filings, including granted US patents, and publications in areas such as autonomous driving, computer vision, sim-to-real learning, and neural representations. My current interests include: • Dexterous robotic manipulation and tactile intelligence • Humanoid and mobile manipulation systems • Vision-language-action models and robot foundation models • Imitation learning, reinforcement learning, and sim-to-real transfer • Teleoperation and scalable robotic data collection • Autonomous driving and embodied
Stanford University
Robotics and Autonomous Systems Graduate Certificate, Principles of Robot Autonomy - I, II, Optimal and Learning-based Control
January 1, 2021 – January 1, 2023
Udacity
Nanodegree, Self Driving Car
January 1, 2017 – January 1, 2018
Indian School of Business
Executive Program, Business Analytics
January 1, 2016 – January 1, 2017
Stanford University
Linear Algebra
January 1, 2014 – January 1, 2014
BE Computer Science
Bachelor of Engineering (BE), Computer Science
January 1, 1995 – January 1, 1999
Udacity
Self Driving Car Nanodegree, Computer Vision, sensor fusion, control theory, path planning applied to Self Driving Car
N/A – Present
xSpecies AI
Founder
March 1, 2025 – Present
Bengaluru, Karnataka, India
Ola Electric
Director - Artificial Intelligence
September 1, 2022 – February 1, 2025
Ola Electric
Associate Director - Artificial Intelligence
August 1, 2020 – September 1, 2022
Ola (ANI Technologies Pvt. Ltd)
Research Engineer III - Computer Vision, Deep Learning
June 1, 2019 – August 1, 2020
Ola (ANI Technologies Pvt. Ltd)
Software Development Engineer III - Computer Vision, Deep Learning
February 1, 2018 – August 1, 2020
Happiest Minds Technologies
Principal Data Scientist
June 1, 2016 – January 1, 2018
Bengaluru, Karnataka, India
TechChefs Software Pvt Ltd
Data Scientist
August 1, 2015 – April 1, 2016
Greater Bengaluru Area
Infosys
Senior Technology Architect - Big Data, Data Science and Analytics
April 1, 2014 – July 1, 2015
Infosys
Technology Architect - Cloud Computing, Big Data Analytics
March 1, 2008 – April 1, 2014
IBM, IBM India Systems and Technologies Lab
Power Systems Technical Consultant (P-Series, AIX)
April 1, 2006 – March 1, 2008
Wipro Technologies
Module Lead, Wipro Technologies
January 1, 2000 – January 1, 2006
Microsoft Malware Classification Challenge
April 1, 2015 – Present
Classify malware into families based on file content and characteristics. In recent years, the malware industry has become a well organized market involving large amounts of money. Well funded, multi-player syndicates invest heavily in technologies and capabilities built to evade traditional protection, requiring anti-malware vendors to develop counter mechanisms for finding and deactivating them. In the meantime, they inflict real financial and emotional pain to users of computer systems. One of the major challenges that anti-malware faces today is the vast amounts of data and files which need to be evaluated for potential malicious intent. For example, Microsoft's real-time detection anti-malware products are present on over 160M computers worldwide and inspect over 700M computers monthly. This generates tens of millions of daily data points to be analyzed as potential malware. One of the main reasons for these high volumes of different files is the fact that, in order to evade detection, malware authors introduce polymorphism to the malicious components. This means that malicious files belonging to the same malware "family", with the same forms of malicious behavior, are constantly modified and/or obfuscated using various tactics, such that they look like many different files. In order to be effective in analyzing and classifying such large amounts of files, we need to be able to group them into groups and identify their respective families. In addition, such grouping criteria may be applied to new files encountered on computers in order to detect them as malicious and of a certain family. For this challenge, Microsoft is providing the data science community with an unprecedented malware dataset and encouraging open-source progress on effective techniques for grouping variants of malware files into their respective families.
Operations Analytics
Coursera Course Certificates
June 24, 2026 – Present
Introduction to Data Science
Coursera
June 24, 2026 – Present
Introduction to Mathematical Thinking
Coursera
June 24, 2026 – Present
Calculus One
Coursera
June 24, 2026 – Present
Calculus Two
Coursera
June 24, 2026 – Present
Analysis of a Complex Kind
Coursera Course Certificates
June 24, 2026 – Present
Computational Neuroscience
Coursera
June 24, 2026 – Present
Calculus: Single Variable
Coursera Course Certificates
June 24, 2026 – Present
5.01x, Linear Algebra - Foundations to Frontiers
edX
June 24, 2026 – Present
Cloudera Certified Developer for Apache Hadoop (CCDH)
Cloudera
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
IBM Certified Solution Advisor - Cloud Computing Architecture
IBM
June 24, 2026 – Present
edX Verified Certificate for Introduction to Big Data with Apache Spark
edX
June 24, 2026 – Present
edX Verified Certificate for Scalable Machine Learning
edX
June 24, 2026 – Present
Foundations of marketing analytics
Coursera Course Certificates
June 24, 2026 – Present
Control Systems Analysis: Modeling of Dynamic Systems
University of Colorado Boulder
June 24, 2026 – Present
Foundations of strategic business analytics
Coursera Course Certificates
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Robotics: Perception
Coursera
June 24, 2026 – Present
Introduction to battery-management systems
Coursera
June 24, 2026 – Present
AI for Medial Dignosis
Coursera
June 24, 2026 – Present
STAT110x: Introduction to Probability
edX
June 24, 2026 – Present
Fundamentals of Reinforcement Learning
Coursera
June 24, 2026 – Present
Robotics: Aerial Robotics
Coursera
June 24, 2026 – Present
Generative AI with Large Language Models
Coursera
June 24, 2026 – Present
Supply Chain Logistics
Rutgers the State University of New Jersey
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's career trajectory shows a strong inclination towards cutting-edge technologies like AI, Robotics, and Autonomous Systems. The project diversity, ranging from malware classification to self-driving cars and marketing analytics, indicates a broad interest and ability to adapt to different domains. The entrepreneurial venture (xSpecies AI) suggests a proactive and innovative mindset. However, the recent focus on robotics and autonomous systems might indicate a slight misalignment with a pure Data Analyst role, which typically focuses more on business intelligence, reporting, and statistical analysis rather than deep learning model deployment or hardware integration. The target role 'Data Analyst' seems to be a step down from their 'Director - Artificial Intelligence' role, which might indicate a mismatch in career aspirations or a desire to pivot.
Soft Skills & Operational Fit
The candidate's extensive experience in leading teams and projects, coupled with a history of filing patents, suggests strong problem-solving, innovation, and leadership skills. The diverse project experience indicates adaptability and a proactive approach to learning. However, without specific psychometric test results, a detailed assessment of work attitude, stress handling, and team collaboration is not possible.