publications
publications by categories in reversed chronological order.
2023
- Data Monetization Strategy for EnterprisesSubhadip Mitra2023
This paper presents an in-depth exploration of Data Monetization for Enterprises that would enable them to effectively transform their data assets into significant economic value. The paper introduces: (a) Data Monetization Framework - that encompasses key strategic technical capabilities, collaborative Data Product development, agile experimentation, product incubation, delivery model, pricing model and privacy/security by design; and (b) Activation of the Data Monetization Strategy - a 12-month long structured approach is discussed to implement, operationalize, scale, and sustain the strategy-through a Data COE. Data Product Development, Pricing Strategy, Delivery Mode and prioritization is also discussed through a Value-effort study. Technology strategy is discussed in detail with MoSCoW scoring. The paper delves into the role of emerging technologies such as generative AI (large language models), big data analytics, artificial intelligence, and machine learning in enhancing data monetization efforts. It also addresses the challenges and opportunities presented by these technologies, including issues related to data privacy, security, and ethical considerations.
2021
- Open Location Proof (OLP)Subhadip MitraMore Information can be found here , 2021
A privacy aware open protocol to prove without repudiation an entity’s point-in-time presence, participation and location in physical or virtual space. GoLocate.Me is a planned implementation node demonstrating the protocol.
- OConsent: Open Consent Protocol for Privacy and Consent Management with BlockchainSubhadip MitraMore Information can be found here , 2021
In the current connected world - Websites, Mobile Apps, IoT Devices collect a large volume of users’ personally identifiable activity data. These collected data is used for varied purposes of analytics, marketing, personalization of services, etc. Data is assimilated through site cookies, tracking device IDs, embedded JavaScript, Pixels, etc. to name a few. Many of these tracking and usage of collected data happens behind the scenes and is not apparent to an average user. Consequently, many Countries and Regions have formulated legislations (e.g., GDPR, EU) - that allow users to be able to control their personal data, be informed and consent to its processing in a comprehensible and user-friendly manner.This paper proposes a protocol and a platform based on Blockchain Technology that enables the transparent processing of personal data throughout its lifecycle from capture, lineage to redaction. The solution intends to help service multiple stakeholders from individual end-users to Data Controllers and Privacy Officers. It intends to offer a holistic and unambiguous view of how and when the data points are captured, accessed, and processed. The framework also envisages how different access control policies might be created and enforced through a public blockchain including real time alerts for privacy data breach.
2016
- Cascading algorithm: Bayesian price convergence for arbitrage free option pricingSubhadip Mitra2016
In this paper, we introduce a novel Cascading Algorithm that leverages Bayesian inference to facilitate arbitrage-free pricing of financial options. Our approach uniquely integrates prior market knowledge with sequentially updated price information to create a convergent pricing model that continuously refines the estimates of option prices under the principle of no-arbitrage. By employing Bayesian updating mechanisms, the algorithm accounts for uncertainties inherent in market data and dynamically adjusts to new information, ensuring robust convergence towards equilibrium prices. We detail the mathematical framework that underpins our model, emphasizing the convergence properties of the algorithm through both theoretical analysis and extensive simulation. The Cascading Algorithm is tested against standard datasets, demonstrating superior performance in achieving faster convergence and higher accuracy in price estimates compared to traditional models. This work not only provides a significant advancement in option pricing but also proposes a framework that could be extended to other financial instruments for achieving efficient, arbitrage-free market predictions.
2015
- CTDBN based Financial Markets Analysis and Differential PredictionsSubhadip Mitra2015
Coupled Temporal Deep Belief Networks alongwith Conditional Restricted Boltzman Machines to encode intra-market movements and temporary coupling with global indices and FX trades.Data acquiring channels: Indices, Key Economic indicators, Streaming Social Networks (Twitter/Facebook for crowd sentiment analysis) and Youtube Live Videos.
2014
- Dynamic Compression - Multicuts for planar graphs with outer terminalsSubhadip Mitra2014
On the fly creation and calculation of Max-flow min-cut gap and approximation of multicuts with deep emulations of a fault-free mesh on a mesh with random faults. Text extractions from HTML and XML documents and compressing the adjacency list representation of graphs, specifically for web graphs, mobile hosts and social networks.
2012
- XPath Ranking and Graph compressionSubhadip Mitra2012
Designed algorithms for automatic on-the-fly wrapper creation for extractions from HTML and XML documents and compressing the adjacency list representation of graphs, specifically for web graphs and social networks. Also, included calculation of Max-flow min-cut gap and approximation of multicuts with deep emulations of a fault-free mesh on a mesh with random faults.
2009
- Real time multiple target tracking using arrayed sensorsSubhadip Mitra2009
A discrete time-step optimization algorithm based on limited parameters of the sensor-target systems. With the idea of a covering graph, designed an iterative solution for a single sensor, forwarded to multiple sensors by a set (matrix) of flags for tagging operation. Furthermore, an OpenCV based implementation of the resulting algorithm is found to perform better than other notable approaches.
2008
- Swarm Intelligence: Micro-mechanical flying insect for low cost outdoor surveillanceSubhadip MitraMore Info about DRDO , 2008
Micromechanical Flying insect for low cost outdoor surveillance: Created micromechanical flying insect based on swarm intelligence driven by peizo electric thorax actuators and muscle wire technology. Integrated onboard GPS and real time imaging. Ingenious navigation algorithms were conceptualized with inputs from the compound eye. A discrete time-step optimization algorithm based on limited parameters of the sensor-target systems for the arrayed eye sensors. With the idea of a covering graph, designed an iterative solution for a single sensor, forwarded to multiple sensors by a set (matrix) of flags for tagging operation.The later evolution of the project saw swarm intelligence incorporated across terrestrial and ariel domains. Project selected and Sponsored by DRDO (Defense Research Development Organization, Ministry of Defense, Government) under the Golden Jubilee Nationwide Students’ Competition from among 271 proposals.
2007
- Low energy wireless electricity transmissionSubhadip MitraMore Information about SC07 , 2007
This paper explores the innovative realm of low-energy wireless electricity transmission, presenting a novel framework for transmitting electrical power without direct physical connections and minimizing energy loss. I start by examining the current methodologies and limitations of traditional wireless power transfer systems, including inductive, capacitive, and radiative techniques. The focus then shifts to the development of a new, more efficient transmission method that leverages advancements in electromagnetic and resonance technologies to enhance range and energy efficiency. Through a series of experiments and simulations, I demonstrate how our proposed system reduces energy wastage and improves the viability of wireless power for a broader range of applications, from small consumer electronics to large-scale industrial machinery. The findings suggest significant implications for the future of energy distribution, potentially leading to safer, cleaner, and more flexible power management systems. The paper concludes with a discussion on the potential environmental impacts and the economic benefits of adopting low-energy wireless electricity transmission technologies.