Sneha Roychowdhury

Head of Design

New Delhi, Delhi, India0 mo experience

Key Highlights

Finalist at Citadel Datathon 2025
Led team to win Smart India Hackathon 2024
Best Paper Award at AIST-2025 conference

Stackforce AI infers this person is a skilled AI/ML engineer with strong leadership and project management capabilities.

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Skills

Core Skills

Deep LearningComputer Vision

Other Skills

CommunicationData ScienceData StructuresFinancial ModelingFront-End DevelopmentImage ProcessingLeadershipMulti-modal Pipeline DevelopmentProduct DevelopmentPyTorchStatisticsTensorFlow

Experience

Tedxigdtu

President and Curator

Sep 2025 – Present · 6 mos · Delhi, India · On-site

Secured official TEDx license and leading cross-functional teams across content, operations, and marketing.
Driving sponsorships, partnerships, curating speakers & performers for a high-impact event.
Overseeing strategy, timelines, and execution to deliver a seamless TEDx experience.

Citadel

Citadel Datathon’25 Finalist

May 2025 – May 2025 · 0 mo · London Area, United Kingdom · Remote

Advanced to the Terminal round at the Citadel, Citadel Securities & Correlation One Datathon 2025, ranking in the top 60 from thousands of applicants across the continent.
Collaborated on high-impact predictive modeling challenges at the intersection of finance, economics, and real-world data, presenting actionable insights to Citadel’s engineering and quantitative research teams.

Icpc - international collegiate programming contest

Competitive Programming Mentor

Apr 2025 – May 2025 · 1 mo · Delhi, India · Remote

Mentored 5000+ participants in an international, women-centric initiative sponsored by ICPC and Jane Street, a proprietary trading firm.
Introduced women to competitive programming through structured roadmaps, doubt-solving sessions, and collaborative planning with the core team.

Defence research and development organisation (drdo)

Summer Research Intern

Jan 2025 – Jul 2025 · 6 mos · Defence Scientific Information & Documentation Centre, Civil Lines, Delhi · On-site

Developed multi-modal deep learning pipeline using ResNet50, FFT analysis, and attention fusion to detect machine-generated artwork with 95% accuracy on 21k+ image dataset.
Implemented complete training system with ablation studies, few-shot learning, automated evaluation metrics, Grad-CAM visualizations, and robustness testing using PyTorch.

Deep LearningPyTorchMulti-modal Pipeline DevelopmentComputer Vision

Delhi technological university (formerly dce)

Summer Research Intern

May 2024 – Jul 2024 · 2 mos · Machine Learning Research Lab, DTU · On-site

Received foundational training in Machine Learning, Deep Learning, NLP, and Generative AI with the CSE Department, DTU.
Worked on individual and group projects applying these concepts, and was further selected to contribute to a computer vision project focused on optimizing object detection under varying lighting conditions using TensorFlow, Keras, OpenCV, and deep learning techniques.