New York, New York, United States
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Product leader with a decade of experience building B2B platforms across financial…

Articles by Adil

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Experience & Education

  • EY

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Licenses & Certifications

Publications

  • Solving the Problem of Congestion in Public Buses: A Solution through Data Pattern Analysis using Raspberry pi and Neural Networks

    IETE 45th Mid Term Symposium on Broadband-Technologies and Services for Rural India MTS

    This paper presents a genuine and simple method to provide an analysis for the overcrowding of public buses. The aim is to find a set of solutions for the same by collecting live data of the
    number of people, location, speed and the time stamp of running buses, during its day to day route around the city. Buses get crowded at particular times during the day or may even be empty during some other time. We can take an approximate count on the number of people presently on a running bus at any…

    This paper presents a genuine and simple method to provide an analysis for the overcrowding of public buses. The aim is to find a set of solutions for the same by collecting live data of the
    number of people, location, speed and the time stamp of running buses, during its day to day route around the city. Buses get crowded at particular times during the day or may even be empty during some other time. We can take an approximate count on the number of people presently on a running bus at any point of time by using image processing of the pictures captured in a camera connected to the raspberry pi. This along with the location and time stamp are sent to a server. The raw data received at the server has to be processed and parsed to extract relevant information to draw out our conclusions.
    This process has to be automatic and the patterns have to be formed and clustered on a live basis. This requires the need of a learning based system like artificial neural networks. Hence the data received by the server undergoes a series of analysis by neural network clustering algorithms to obtain our required conclusions. The conclusions can be solutions like the allocation of new buses or the modification of existing routes.

    See publication

Projects

  • Audionet

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    Audionet is a conceptual idea for a digital reader service that allows users to organize and listen to their digital reading in a natural human-like voice (think Audible for the internet!). The service was conceived and designed as part of my Digital Service Innovation class at CMU. Together with three other teammates, I envisioned to design a product that creates a new aural experience in content consumption where users can seamlessly save and listen to digital text across all platforms and…

    Audionet is a conceptual idea for a digital reader service that allows users to organize and listen to their digital reading in a natural human-like voice (think Audible for the internet!). The service was conceived and designed as part of my Digital Service Innovation class at CMU. Together with three other teammates, I envisioned to design a product that creates a new aural experience in content consumption where users can seamlessly save and listen to digital text across all platforms and devices.

    See project
  • WhatsApp for Teams

    -

    WhatsApp for Teams implements a UX and feature enhancement for the original WhatsApp Messenger allowing for better team collaboration capabilities. The project was built as part of my Human-Computer Interaction class at Carnegie Mellon University. The project followed Google's iterative Design Sprint process to build a solution in the following stages:
    1. Scoping the Team Collaboration Problem
    2. Identifying the Customer Persona
    3. Conducting Users Interviews
    4. Ideating and…

    WhatsApp for Teams implements a UX and feature enhancement for the original WhatsApp Messenger allowing for better team collaboration capabilities. The project was built as part of my Human-Computer Interaction class at Carnegie Mellon University. The project followed Google's iterative Design Sprint process to build a solution in the following stages:
    1. Scoping the Team Collaboration Problem
    2. Identifying the Customer Persona
    3. Conducting Users Interviews
    4. Ideating and Synthesising Solutions
    5. Building and Usability Testing a Solution
    6. Creating a High-Fidelity Mockup of the Solution

    See project

Honors & Awards

  • Hackathon Winner | Ethereum India

    ETHGlobal

    https://devfolio.co/submissions/contractify-by-lumio

  • Hackathon Winner | CTF Codeathon

    AUSTRAC

    http://ctfcodeathon.org/project/5

  • 6th Rank in National Level Programming Competition

    India's Best Brains 2014

    Finished with a rank of 6 among 3500+ participants in a National level programming competition, India's Best Brains 2014, held in IIT Kharagpur during the month of August 2014.

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