Iman Dolatkia

+989124869956 .

Senior Android Developer with +8 years of experience in designing, developing,
and delivering user-centric software applications with +5.4m users.
Proficient in Java, Kotlin, and android SDK.


Senior Android Developer

Taaghche is a famous Persian bookstore with +3M local users and +100K books. screenshots, download.

  • Designed the architecture and developed it from the beginning. Using Java & Kotlin.
  • Increased crash-free users to 99.4% by bug troubleshooting and creating a release pipeline.
  • Designed the new UI/UX of the app that increased 20% profit.
  • Developed complex and unique custom views and animations.
  • Created a High performance, full-featured, encrypted ePUB reader.
  • Developed a full-featured, encrypted audiobook player.
  • Worked on the iOS app for about a year, using Objective-C & Swift.
  • DEC 2014 - PRESENT (7 years)

    Owner & Unity Developer

    I created an independent game to play with Persian kinds of music named “Boom boom”, with more than +1.5M downloads from all over the world.

  • Did initial ideation, game design, and ad design.
  • Designed architecture and developed it from the beginning. Using C# & Unity.
  • JUL 2017 - PRESENT (4 years) . Part-time

    Android Developer

  • Developed an Android app with Java that increases sim cards credit, named “Charger” with +800K users.
  • Developed an Android App with Java for dieting, named “Salemsho”. With +60K users.
  • Developed an Android app With Java to pay the bills with QR code. With +1K users.
  • DEC 2013 - DEC 2014 (1 years)

    Junior Developer

    FreeLancer, Tehran, Iran

  • Created an Android currency price application for “Artin exchange", using java.
  • Create a factory warehousing system for “Ahoora co”, using Java.
  • DEC 2012 - DEC 2013 (1 years)


    Android Animated Theme Manager

    400+ stars

    Create custom themes and change them dynamically with the ripple animation

    FullScreenCardViewPager for Android

    120+ stars

    Endless full-screen card ViewPager inspired by apple iBook for Android.


  • Java, Kotlin, C#, Unity
  • Git
  • SQL, Realm, SQLight
  • Retrofit, Gson, Json
  • Service, AsyncTask, WorkManager
  • Jira, Scrum
  • Design Patterns, Clean Code
  • Glide, Picasso
  • Hitl, Ioc, DI
  • Firebase, appmetrica, appcenter
  • RxJava, LiveData
  • Layout Optimization
  • Layout Performance
  • Complex Animation & UI
  • Proguard Rules, R8, encryption
  • CICD, Gitlab CI

  • Education

    University of Science and Culture

    Tehran, Iran — Master's degree, Computer Software Engineering
    September 2013 - December 2015

    Imam Khomeini International University

    Tehran, Iran — Engineer’s Degree, Computer Software Engineering
    September 2009 - July 2013


    Music recommendation system based on the continuous combination of contextual information

    IEEE - 2016 Second International Conference on Web Research (ICWR)
    With the progress of technology in music players, especially in intelligent cell phones, users have access to large archives. Quick and easy selecting favorite music among these large archives becomes one of the biggest problems for users. For example, selecting music in a silent forest is different from a crowded street or feelings for listening to music in a morning of a working day is different from an afternoon of a holiday. In this paper, a system has been designed that it collects users' context information such as weather, temperature, geographical position, etc., and according to a weighted combination of them, it recommends an appropriate music that is a user's favorite at the moment. Thus, this system includes a rating method that determines how close are music's context, which have been played before, in the moment's context and recommend the music that has the most closeness. The result of this research shows that recommendations that this system makes in different conditions, is closed to the user's choice.

    Appropriate Context for Context Aware Music Recommendation

    Journal of Engineering and Applied Sciences
    There are various environmental factors that impact on selection of appropriate music. For example, selection of music in a foggy mountain is totally different with music selections in traffic jam or human sensation for listening to music on a weekend morning is extremely different with a research day’s afternoon. In this study, context information which can impact on user’s choices is evaluated through psychology of music inclinations, context information used in related researches and studies and also smartphones limitations and entirely most appropriate scheme will be offered. Particularly, these context information can be used in all context aware music recommendations. Finally, adopted experiments reveals that recommendations which apply these context information are acceptably similar to user’s selection in all circumstances.