Delhi, India

Manasi Malik


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2024

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1 patent (USPTO):Explore Patents

Title: Inventor Manasi Malik: Pioneering Advertising Solutions

Introduction

Manasi Malik, an accomplished inventor based in Delhi, India, is making her mark in the field of digital advertising. Her innovative thinking and research have led to the development of a significant patent that addresses the optimization of advertisement campaign allocations within budget constraints.

Latest Patents

Malik holds a patent titled "Budget constrained deep Q-network for dynamic campaign allocation in computational advertising." This groundbreaking invention focuses on maximizing conversions from advertisement campaigns while adhering to a fixed budget and duration. By formulating the allocation problem as a constrained Markov Decision Process (MDP), her method integrates user and advertiser states, action spaces, and a unique cumulative reward model that enhances total conversions.

Career Highlights

Currently, she is associated with Tata Consultancy Services Limited, where she contributes her expertise in computational advertising and artificial intelligence. Her work has not only garnered attention in the industry but has also positioned her as a rising star among inventors in the realm of technology and advertising.

Collaborations

Throughout her career, Malik has engaged with various teams within Tata Consultancy Services, collaborating on projects that merge technology and advertising strategies. Her innovative approach to problem-solving has facilitated cross-disciplinary collaborations, enriching the overall impact of her work.

Conclusion

Manasi Malik is a notable figure in the field of innovations related to digital advertising. Her patented solutions pave the way for improved campaign management and exemplify how inventive minds can address modern challenges in technology and advertising industries. As she continues to develop her career, her contributions will undoubtedly inspire future innovations in computational advertising.

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