Predavanja možete pratiti i online putem MITEAM stranice Seminara za računarstvo i primenjenu matematiku:
https://miteam.mi.sanu.ac.rs/asset/qGapAHyEBad2FDwXR
PLAN RADA SEMINARA ZA JUN 2026. GODINE
Utorak, 02.06.2026. u 14:15, Knez Mihailova 36, sala 301f i
Online
Veljko Milutinović, Elektrotehnički fakultet, Univerzitet u Beogradu
ENTREPRENEURSHIP
This presentation describes the course on the topic from the title.
This topic can be covered as an isolated lecture of one to four academic hours or as a full one-semester course of 12 to 36 academic hours with 12 homework assignments. It covers 12 management-oriented high-tech supported paradigms for creative and holistic management of projects in any field of interest, with the stress on AI and Big Data.
Themes included: (a) Writing proposals for the NSF in the USA or for Horizon in Europe, (b) Mastering the elevator-pitch generation skills, by writing short analytical esseys for GMAT or GRE, (c) Strategic planning using CMMI of DARPA, (d) Tactical planning using Agile Methods of DARPA, (e) Creating a Highly Visible web presence for Worldwide Markets, a strategy created at Harvard, (f) Creating the Mind Genomics Campaign for Targeted Marketing, a strategy created at Harvard, (g) Incorporating based on SBA of USA, (h) Protecting based on PTO of USA, (i) Writing survey articles for SCI journals, (j) Writing research articles for SCI journals, (k) Data Mining and Semantic Web, and (l) Creativity and Branding.
Each theme includes theory, practice, examples, and an anectode that stresses the essence.
So far, in the last 40 year, the course was presented, in its various forms, for years in the line, at Indiana University, Purdue University, MIT, and Harvard in the USA. In Asia at Hebrew University in Jerusalem, Technion, Bogazici, Koç, Thinghua, Shandong, Sendai, and Tokyo. Also, in Europe at ETH, EPFL, UNIWIE, TUWIEN, Siena, Salerno, Barcelona, Madrid. In exYu at Belgrade, Podgorica, Zagreb, and Ljubljana.
The presentation is based on author's experiences from his DARPA projects on GaAs and DataFlow computing, and is inspired by current VicePresidents (for the company's core business) of Qualcomm, Intel, IBM, AMD, NCR, and HP Labs, who all graduated from the University of Belgrade, where this course is/was obligatory or elective in four different schools (ETF, MATF, GRF, FON).
In the current academic year, or in the very near past, the course has been taught also for students of Purdue University, Indiana University in Bloomington, MIT, Harvard, Hebrew University of Jerusalem, Tel Aviv University, Technion, Weizmann, Universities of Salerno and Siena, as well as of UNIWIE and TUWIEN.
The course is supported with a textbook by Cambridge Publishers, for which the pearls of wisdom were contributed by 20 Nobel Laureates.
Zajednički sastanak sa seminarom Veštačka inteligencija.
Utorak, 09.06.2026. u 14:15, Pariske Komune bb, Niš i
Online
Melanija Mitrović, University of Niš, Faculty of Mechanical Engineering
AN INTRODUCTION TO CONSTRUCTIVE CALCULUS OF RELATIONS
Following A. Tarski,
On the calculus of relations, Journal of Symbolic Logic
6 (1941), 73–89, “Aside from the fact that the concepts occurring in this calculus possess an objective importance and are in these times almost indispensable in any scientific discussion, the calculus of relations has an intrinsic charmand beauty which makes it a source of intellectual delight to all who become acquainted with it.” It is commonly accepted that binary relations are a mathematical way of talking about relationships that exist between pairs of objects. Such relations permeate every aspect of mathematics, of science, and of human affairs.
In this presentation, we will limit ourselves primarily to the constructive theory of binary relations defined on a set with apartness, focusing more specifically on the part of this theory called the constructive calculus of relations. Overall, we aim to provide a clear and understandable picture of constructive calculus of relations defined on a set with (non-tight) apartness, which we develop in Bishop’s style of constructive mathematics, BISH. The talk will draw primarily on our ongoing work M. Mitrovic, M. N. Hounkonnou,
Constructive Calculus of Relations vs. Classical Calculus of Relations.
Joint meeting with the seminar Decision making – Theory, technology and practice.
Utorak, 16.06.2026. u 14:15, Knez Mihailova 36, sala 301f i
Online
Dušan Kostić, Miloš Jolović, i grupa studenata, Fakultet organizacionih nauka
PREZENTACIJA STUDENTSKIH REŠENJA SA „FON HAKATON – WEB4 CHALLENGE 2026“
Katedra za elektronsko poslovanje Fakulteta organizacionih nauka uspešno nastavlja da podstiče inovacije kroz studentska takmičenja u oblastima savremenih tehnologija. Na ovom predavanju biće predstavljeni najbolji radovi sa nedavno završenog, četvrtog po redu, hakatona FON Hakaton – Web4 Challenge 2026, koji je organizovan na Fakultetu organizacionih nauka, a u okviru međunarodnog EIT HEI projekta TROPHY. Tokom ovog predavanja, studentski timovi će demonstrirati svoje praktične radove kojima su odgovorili na kompleksne izazove u oblasti Web4 tehnologija. Studentski timovi će prikazati razvijene prototipe i poslovne modele, a pored tehničke implementacije, fokus će biti i na inovativnim biznis konceptima koji pokazuju kako savremene tehnologije transformišu elektronsko poslovanje.
Utorak, 23.06.2026. u 14:15, Knez Mihailova 36, sala 301f i
Online
Sanja Štajner
AUTOMATIC ASSESSMENT OF CONCEPTUAL TEXT COMPLEXITY USING KNOWLEDGE GRAPHS
Complexity of texts is usually assessed only at the lexical and syntactic levels. Although it is known that conceptual complexity plays a significant role in text understanding, only a few attempts have been made at assessing it automatically. This talk describes the first approach to an automated estimation of the conceptual complexity of texts by exploiting a number of graph-based measures on a large knowledge base. By using a high-quality language learners corpus for English, we show that graph-based measures of individual text concepts, as well as the way they relate to each other in the knowledge graph, have a high discriminative power when distinguishing between two versions of the same text. Furthermore, when used as features in a binary classification task aiming to choose the simpler of two versions of the same text, those measures achieve high performance even in a default setup.
Utorak, 30.06.2026. u 14:15, Knez Mihailova 36, sala 301f i
Online
Nataša Pržulj, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE; Department of Computer Science, University College London, London, United Kingdom
MULTI-OMICS DATA FUSION FOR PRECISION MEDICINE AND THERAPEUTICS
Large amounts of multi-omic data are increasingly becoming available. They provide complementary information about cells, tissues and diseases. We need to utilize them to better stratify patients into risk groups, discover new biomarkers and targets, re-purpose known and discover new drugs to personalize medical treatment. This is nontrivial, because of computational intractability of many underlying problems on large interconnected data (networks, or graphs), necessitating the development of new algorithms for finding approximate solutions (heuristics).
We develop versatile artificial intelligence (AI) frameworks for multi-omics data fusion, constrained by the state-of-the-art network science methods, to address key challenges in precision medicine and pharmacology from time-series, multi-omics data, including patient-derived single-cell data, to: better stratify patients, predict new biomarkers and targets, re-purpose existing and discover new drugs; we apply these to different types of cancer, Covid-19, Parkinson’s and other diseases. Our new methods stem from graph-regularized non-negative matrix tri-factorization (NMTF), a machine learning (ML) technique for dimensionality reduction, inference, fusion and co-clustering of heterogeneous datasets, coupled with novel graphlet-based network science algorithms. We utilize our new frameworks for improving the understanding of the molecular organization of life and of diseases from the embedding spaces of omics data. Also, we utilize the local network topology to correct for the topological information missed by random walks used in many ML methods, and to enable embedding of multi-omics networks into more linearly separable spaces, allowing for their explainable and sustainable mining. The aim is to develop an overreaching framework encompassing all multi-omics data towards consumer-facing precision medicine products
Zajednički sastanak sa seminarom Veštačka inteligencija.
RUKOVODIOCI SEMINARA
MI SANU
Vera Kovačević-Vujčić
Milan Dražić
FON
Zorica Bogdanovic
Marijana Despotovic-Zrakic
IEEE
Bozidar Radenkovic
