ὅδε οἶκος, ὦ ἑταῖρε, μνημεῖον ἐστιν ζῴων τῶν σοφῶν ἀνδρῶν, καὶ τῶν ἔργων αὐτῶν

Seminar on Computer Science and Applied Mathematics

 

PROGRAM


Matematički Institut SANU, Beograd
Knez Mihajlova 36
Fakultet organizacionih nauka, Univerzitet u Beogradu,
Jove Ilica 154
IEEE Chapter Computer Science (CO-16) Belgrade, Republic of Serbia

SEMINAR ZA RAČUNARSTVO I PRIMENJENU MATEMATIKU

MI SANU, Knez Mihailova 36, sala 301f

Upravni odbor Matematickog instituta SANU je na nedavnoj sednici doneo odluku da se dosadasnji Seminar za primenjenu matematiku, sada nazove Seminar za racunarstvo i primenjenu matematiku, a u cilju potenciranja znacaja racunarstva kao jedne od oblasti delatnosti Instituta. Istovremeno, Upravni odbor doneo je odluku o osnivanju Odeljenja za racunarstvo i primenjenu matematiku i vezao rad novog odeljenja za rad Seminara za racunarstvo i primenjenu matematiku.

PLAN RADA SEMINARA ZA AVGUST 2016. GODINE



PETAK, 12.08.2016. u 14:15, Sala 301f, MI SANU, Kneza Mihaila 36
Snežana Minić, Simon Fraser University, Vancouver
A NEW VARIATION OF THE TRAVELING SALESMAN PROBLEM: SATELLITE IMAGE ACQUISITION SCHEDULING OF DEEP-SPACE EARTH-ORBITING OBJECTS
This talk presents an image acquisition scheduling problem for a Canadian surveillance-of-space satellite named Sapphire that takes images of deep space Earth-orbiting objects. For a set of resident space objects (RSOs) that needs to be imaged within the time horizon of one day, the Sapphire image acquisition scheduling (SIAS) problem is to find a schedule that maximizes the “Figure of Merit” of all the scheduled RSO images. To address the problem, we propose an effective GRASP heuristic that alternates between a randomized greedy constructive procedure and a local search procedure.


PETAK, 26.08.2016. u 14:15, Sala 301f, MI SANU, Kneza Mihaila 36
Zoran Obradovic, Data Analytics and Biomedical Informatics Center, Computer and Information Sciences Department, Statistics Department, Temple University, Philadelphia, USA
DISEASE TYPES DISCOVERY AND HEALTHCARE QUALITY MODELING FROM A LARGE DATABASE OF INPATIENT RECORDS
We map a very large EHR database of Electronic Health Records containing millions of inpatient cases into a low dimensional space wherediseases with similar phenotypes have similar representation. This embedding allows for an effective segmentation of diseases into more homogeneous categories, an important task of discovering disease types for precision medicine. Our results show evidence that such representations have phenotypes of higher quality and also provide benefit when predicting hospitalization length of stay, total incurred charges, and mortality rates.
Results reported in this talk are in press at
- Gligorijevic, Dj., Stojanovic, J., Obradovic, Z., Discovering Disease Phenotypes from a Large Database of Inpatient Records: A Sepsis Study, Methods, in press.
- Stojanovic, J., Gligorijevic, Dj., Radosavljevic, V., Djuric, N., Grbovic, M., Obradovic, Z., Modeling Healthcare Quality via Compact Representations of Electronic Health Records, IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press.


RUKOVODIOCI SEMINARA

MI SANU
Vera Kovačević-Vujčić
Milan Dražić

FON
Zorica Bogdanovic
Marijana Despotovic-Zrakic

IEEE
Bozidar Radenkovic