Posts

Showing posts from 2018

Lambdas Query with Reason

I will be visiting  Simon Thompson  and the  PLAS seminar  organized by  Olaf Chitil  at University of Kent on 15 Oct 2018. Speaker Ralf Lämmel , Facebook London and University of Koblenz-Landau (on leave) Title Lambdas Query with Reason Abstract Much of the Big Data hype focuses on the size of data and on the use of ML/AI to get something out of the data and on the programming technologies and infrastructure to deal with size, ML, and AI. Our research focuses on a complementary problem: the ontological semantics of data and how to use it for querying data programmatically and to help programmers in the tradition of static typing. In this talk, I present two strongly connected pieces of work: i) $\lambda_{\mathit{DL}}$ -- a lambda calculus with description logic-aware type system and means of querying semantic data ('triples'); ii) a completed language integration such that description logic and a subset of the standardized Sparql language are embedded into Scala.

Message Everyone -- Startup Announcement

Please check out the date at the bottom of the post before sending more inquiries to me and others. I have taken unpaid leave of absence from my faculty job to work on a startup idea — public codename: “Message Everyone”. Sorry for misleading colleagues and family about my career plans for the last few months. The idea took shape more than two years ago, when I was organizing the IFL 2015 conference on campus and where I had to communicate with 2 secretaries, 3 more local staff members, and 3 student volunteers; I had to keep in touch with about 8 persons shortly before, during, and shortly after the event to ensure a smooth operation. Upfront, I was offering the following access paths: Skype, Telegram, WhatsApp, Twitter, FB Messenger,   Google Hangout, SMS (and Email and phone). This wouldn’t cover everyone’s messaging preferences and so I would need to install two more apps which I don't remember by now.  If I ran this conference today, Signal, Viber, SnapShat, LI

Big Code Science

I am pitching "Big Code Science" (my take on the mashup of mining software repositories, source-code analysis, program comprehension, etc.) to an inter-faculty audience at my university. (I am about to start an extended unpaid leave of absence to join Facebook and do work possibly a bit related to big code science.) I will just have 15min in a brown-bag setting and thus, I am going to use images, charts, and simple messages. Title : Big Code Science Abstract : Code Science is Data Science for code. Big Code Science is the scientific approach to accessing, analyzing, and understanding big data where the data here is code or data related to software development. There is several reasons why Big Code Science has taken off. (i) Open Source development has exploded in the last 10 years so that we have access to terabytes of source code, version history, developer communication, documentation, release infos, bug tracking info, etc.; not trying to learn from the past would be cr