Adhish Prasoon

Product Manager

Bengaluru, Karnataka, India17 yrs 9 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Ph.D. in Machine Learning with extensive research experience.
Led high-performance Data Science teams at top companies.
Expertise in developing innovative machine learning solutions.

Stackforce AI infers this person is a Data Science leader with expertise in Machine Learning and Computer Vision across various industries.

Contact

adhishprasoon@gmail.com LinkedIn

Skills

Core Skills

Data ScienceMachine Learning

Other Skills

3D visualizationCCoaching & MentoringComputer VisionCredit risk modelingCross-functional Team LeadershipDeep LearningFinTechFintech data scienceGraph machine learningImage AnalysisImage ProcessingLaTeXLarge Language Models (LLM)Leadership

About

I am a Ph.D. in Machine Learning from Department of Computer Science, University of Copenhagen, Denmark. I have been working in Machine Learning, Data Science and related areas since 2007 and have been managing high performance Data Science teams since 2017. I am currently working as Research Director, Data Science at Flipkart. Before joining Flipkart, I worked as Senior Vice President in Data Science at Info Edge India where I was leading and managing a team of Data Scientists to find solutions for critical business problems for Naukri.com, Jeevantsathi.com and 99acres.com. Previously, I led some important and challenging Machine Learning Projects for Mobileum Inc. and Samsung Research. I have a Masters in Technology from Indian Institute of Technology Bombay, India. During my masters, I received DAAD scholarship and worked on my M.Tech project at Computer Vision and Remote Sensing Group of Technical University of Berlin, Germany for a period of 9 months. After finishing my masters, and before joining my Ph.D., I worked as a Research Scientist at Core Projects and Technologies for approximately 2.5 years. During my stint at Core Projects and Technologies I was chosen to be a part of the team sent to get trained at Centre of Higher Learning, Stennis Space Centre, NASA, USA for a period of 1 year.

Experience

Flipkart

Research Director - Data Science

Jul 2021 – Present · 4 yrs 8 mos · Bengaluru, Karnataka, India

Stakeholder ManagementPython (Programming Language)People ManagementMachine LearningImage AnalysisImage Processing+24

Info edge india ltd

3 roles

Senior Vice President in Data Science

May 2019 – Jul 2021 · 2 yrs 2 mos

Stakeholder ManagementPython (Programming Language)People ManagementMachine LearningImage AnalysisImage Processing+21

Vice President in Data Science

May 2018 – May 2019 · 1 yr

Stakeholder ManagementPython (Programming Language)People ManagementMachine LearningImage AnalysisImage Processing+21

Associate Vice President in Data Science

Nov 2016 – May 2018 · 1 yr 6 mos

Stakeholder ManagementPython (Programming Language)People ManagementMachine LearningImage AnalysisImage Processing+21

Mobileuminc

Lead Data Scientist

Jun 2015 – Oct 2016 · 1 yr 4 mos · Gurgaon, India

Machine Learning Research

Stakeholder ManagementPython (Programming Language)Machine LearningImage AnalysisImage ProcessingNeural Networks+14

Samsung r&d institute india

Chief Engineer

Sep 2013 – May 2015 · 1 yr 8 mos · Noida, Uttar Pradesh, India

Research and Innovation in Computer Vision, Image Analysis and Machine Learning.

Stakeholder ManagementPython (Programming Language)Machine LearningImage AnalysisImage ProcessingNeural Networks+12

Department of computer science, university of copenhagen - diku

Ph.D candidate

Jun 2010 – Aug 2013 · 3 yrs 2 mos · Copenhagen Metropolitan Area · On-site

During my PhD, I worked on Machine Learning and Image Analysis approaches for voxel/pixel classification based segmentation methods and applied them for segmentation of anatomical structures in medical images. I worked on deep learning architectures for autonomous feature-learning in case of 3D medical images and developed a triplanar convolutional neural network(CNN). Although, the triplanar convolutional neural network learned 2D features on single scale, it still performed better than the state-of-the-art method which relies on hand-crafted features for cartilage segmentation in knee MRIs. The state-of-the-art method uses 3D as well as multi-scale features, whereas our triplanar CNN learns single scale 2D features. The other significant part of my PhD thesis is a cascaded classifier. Many classification and segmentation tasks are particularly challenging for machine learning algorithms because of the huge amount of training data involved. Learning methods scaling badly in the number of
training data points may not be applicable. This may exclude powerful classifiers with good generalization performance. I developed a two-stage classifier which enables us to use such classifiers in large-scale machine learning problems. I applied the two-stage cassifier comprising
kNN and Support Vector Machine as the two stages to classify voxels in knee MRIs.

Python (Programming Language)Machine LearningImage AnalysisImage ProcessingNeural NetworksData Science+7

Core projects & technologies ltd

Research Scientist

Dec 2007 – Feb 2010 · 2 yrs 2 mos

After finishing my masters, I worked as a Research Scientist at Core Projects and Technologies for 2.5 years in the field of computer vision/graphics and 3D immersive visualization. During my stint at Core Projects and Technologies I was chosen to be a part of the team sent to get trained at Stennis Space Centre, NASA, USA for a period of 1 year.

Machine LearningImage AnalysisImage ProcessingNeural NetworksOpenGLData Science+7