Bikram Pandit, Full-stack Developer in Corvallis, United States
Bikram Pandit

Full-stack Developer in Corvallis, United States

Member since December 13, 2022
Bikram is a full-stack developer building front end, back end, and mobile applications with thousands of downloads and daily active users. He served many international clients and worked for US and Dutch companies for four years. Bikram is in the top 2% of the Stack Overflow community, generously helping other developers and contributing to Flutter.
Bikram is now available for hire




Corvallis, United States



Preferred Environment

MacOS, Slack, JetBrains, Linux, Windows, Discord, Teams

The most amazing...

...thing I've developed is the Background Recorder app, which has 200,000+ downloads and 500 daily active users.


  • Research Assistant

    2021 - PRESENT
    Oregon State University
    • Developed an obstacle avoidance and autonomous navigation maneuver in the bipedal robot Cassie, which set the Guinness world record for the fastest robot in a 100-meter race and a continuous 5,000 run.
    • Taught 150+ students as a teaching assistant and increased overall class performance by 14%.
    • Developed an agent to pick a tool and fetch a goal in an unknown environment as part of the DARPA research project and secured the second position when competing with CMU, MIT, IBM, and UCB.
    Technologies: Machine Learning, Computer Vision, Python 3, C, C++
  • Full-stack Developer

    2021 - 2021
    • Built an in-app chat infrastructure by writing XMPP chat plugins and increased user engagement and retention rate.
    • Acted as an open-source contributor by developing a feature in Flutter, which is an open-source UI software development kit created by Google.
    • Contributed to an app for the international market used by people all over the world.
    Technologies: Android, iOS, Flutter, React
  • Mobile Developer

    2017 - 2021
    Digital Product Labs
    • Developed Android, iOS, Flutter, and React mobile apps and published them in app stores for over 500 international clients.
    • Managed client apps, provided long-term support, and helped scale the app's infrastructure.
    • Developed automation tools and increased the team's productivity.
    Technologies: Android, iOS, Flutter, Java, JavaScript, Swift, Django, React, Google Cloud, Amazon Web Services (AWS)


  • Background Recorder

    I developed a surveillance application for Android. It can take videos, capture images, or record audio in disguise or immediately whenever needed. This app has over 200,000 downloads with over 500 daily active users. I actively maintain it, so the app has been republished.

  • Universal Translator

    A translator for adding different languages to the application. This project can be integrated into almost any application with a low-cost subscription. The advantage for a developer using this tool is rapid application development without relying on a third-party application that can be expensive, require its extension, and, therefore, challenging to integrate.

  • ShareByte

    It is a web application enabling users to collaborate and write in the same place. ShareByte is an excellent tool for instantly sharing a document online as it does not require any login but only a five-digit permalink. It synchronizes immediately among any number of sessions around the world.

  • Lab Reporting Software

    A progressive web app that can be opened in the browser and installed as an application on Windows, Mac, Linux, Android, and iOS devices. This app is used in a pathology laboratory to record tests and print them in the required format.

  • Multimodal Analysis of Songs Using Late Fusion Model

    I developed a late fusion neural network that can classify the mood of a song based on audio and lyrics. It is useful for a recommendation system such as Spotify or YouTube, where songs are targeted to the audience according to their mood, thus increasing user engagement.

  • Self-balancing with Reinforcement Learning

    I built a self-balancing platform using reinforcement learning and the PPO algorithm. It is better than a PID or model-based balancing system due to the development's complexity and the learning-based approach's robustness. It can be used in robot applications for balancing on uneven terrain or transportation.


  • Languages

    Python 3, JavaScript, C, C++, Java, Swift
  • Frameworks

    Flutter, Django
  • Libraries/APIs

  • Platforms

    Android, iOS, Amazon Web Services (AWS), Linux, Windows
  • Storage

    Google Cloud
  • Other

    Machine Learning, Computer Vision, Software Engineering, Reinforcement Learning, Web Hosting, Deployment, Discord, Teams


  • Master's Degree in Computer Science
    2021 - 2022
    Oregon State University - Corvallis, Oregon, USA

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