To help making education and learning easier and more widespread


 
Solo code ︎︎
  1. 2013: ActorFS Indexer
  2. 2019: iam
  3. 2023: GRID
  4. 2024: Coffee 

Ventures ︎︎
  1. 2005: Nourtia
  2. 2012: Miras
  3. 2021: eveince (GmbH and Inc.)


Mohsen —
life~
I’m an Iranian businessman and inventor, currently living in Munich. I grew up in Iran, I did my studies and research in software engineering and AI; Co-founded Nourtia (Isfahan-Iran), Miras Technologies (registered in the US, operating in Luxembourg and Iran), and eveince (Germany and US). Nourtia was focused on optimization systems in city planing. Miras was an enterprise data technology provider. eveince was initially building AI models for market risk assesment and trading systems (Hq in Germany) and after a one-year pause, now is designing and implementing AI applications (Hq in US). In eveince we’re very curious about the impact of AI on education and learning. I’d love to get in touch and share our experince if you’re working in this field. Email me or DM me on social media.


Mark
Patents

My patents are designs for data intensive applications which were implemented in ActorFS.
  • Actor system and method for analytics and processing of big data US 9338226
    The embodiments herein provide a system architecture, application model and methods to write Big Data programs using actor systems and asynchronous messaging middleware akka and scala language. The system comprises an actor network connected to a cloud network and to a distributed virtual machine (DVM) network. The actors are connected respectively to the DVMs based on a predefined protocol. A scheduler is provided to schedule the resources to an actor in the actor network. A stop and start mechanism is provided to change a connection between the actors and the DVMs. The system server sends a message to the actor to disconnect an actor connected to one DVM and to connect the actor to another DVM based on a load of a process agent present in each DVM to balance a load on the actor. The system server adds three fundamental operations over actor systems.
  • System and method providing hierarchical cache for big data applications US 9338226
    The embodiments herein develop a system for providing hierarchical cache for big data processing. The system comprises a caching layer, a plurality of actors in communication with the caching layer, a machine hosting the plurality of actors, a plurality of replication channels in communication with the plurality of actors, a predefined ring structure. The caching layer is a chain of memory and storage capacity elements, configured to store a data from the input stream. The plurality of actors is configured to replicate the input data stream and forward the replicated data to the caching layer. The replication channels are configured to forward the replicated data from a particular actor to another actor. The predefined ring structure maps the input data to the replica actors.
  • System and method for process resolution and composition in actor systems US 20150052363A1
    The various embodiments herein provide an actor oriented system and a method for providing communication between a plurality of processes in the actor system. The system uses actor model as the basis for a large scale process distribution. The system abstracts the plurality of processes and adopts a method of process composition and resolution. The method provides binding of different processes in the system to create a multi-functional distributed application.
  • System and method providing marketplace for big data applications US 20150052363A1
    The embodiments herein disclose a system and method for providing a marketplace for Big Data applications. The system facilitates a repository of applications, data sets, process compositions and extension modules received from the various vendors. The assets provided by the marketplace are deployed upon receiving the requests on public and private clouds. The marketplace comprises the algorithms, data sets and software systems to generate, share and save the insights for a plurality of cloud users. The system provides Big Data applications on demand from the cloud users and installs the requested application on a dedicated platform adopted for online Big Data processing.