Porting of run-time environment for Lua-based applications. - Marko Grumic; Marko Vasic; Jelena Kovacevic; Ivan Kastelan (ICCE-Berlin, 2015)

Regression test selection across JVM boundaries. - Ahmet Çelik; Marko Vasic; Aleksandar Milicevic; Milos Gligoric 001 (ESEC/SIGSOFT FSE, 2017)

File-level vs. module-level regression test selection for .NET. - Marko Vasic; Zuhair Parvez; Aleksandar Milicevic; Milos Gligoric 001 (ESEC/SIGSOFT FSE, 2017)

: Molecular Programming Language. - Marko Vasic; David Soloveichik; Sarfraz Khurshid (DNA, 2018)

Neural Program Repair by Jointly Learning to Localize and Repair. - Marko Vasic; Aditya Kanade 001; Petros Maniatis; David Bieber; Rishabh Singh (ICLR (Poster), 2019)

MoËT: Interpretable and Verifiable Reinforcement Learning via Mixture of Expert Trees. - Marko Vasic; Andrija Petrovic; Kaiyuan Wang; Mladen Nikolic; Rishabh Singh; Sarfraz Khurshid (CoRR, 2019)

CRNs Exposed: Systematic Exploration of Chemical Reaction Networks. - Marko Vasic; David Soloveichik; Sarfraz Khurshid (CoRR, 2019)

A Study of the Learnability of Relational Properties (Model Counting Meets Machine Learning). - Muhammad Usman 024; Wenxi Wang; Kaiyuan Wang; Marko Vasic; Haris Vikalo; Sarfraz Khurshid (CoRR, 2019)

CRNs Exposed: A Method for the Systematic Exploration of Chemical Reaction Networks. - Marko Vasic; David Soloveichik; Sarfraz Khurshid (DNA, 2020)

Deep Molecular Programming: A Natural Implementation of Binary-Weight ReLU Neural Networks. - Marko Vasic; Cameron T. Chalk; Sarfraz Khurshid; David Soloveichik (ICML, 2020)

Designing Neural Networks Using Logical Specs. - Shikhar Singh; Marko Vasic; Sarfraz Khurshid (ISSRE, 2020)

A study of the learnability of relational properties: model counting meets machine learning (MCML). - Muhammad Usman 024; Wenxi Wang; Marko Vasic; Kaiyuan Wang; Haris Vikalo; Sarfraz Khurshid (PLDI, 2020)

CRN++: Molecular programming language. - Marko Vasic; David Soloveichik; Sarfraz Khurshid (Nat. Comput., 2020)

Programming and Training Rate-Independent Chemical Reaction Networks. - Marko Vasic; Cameron T. Chalk; Austin Luchsinger; Sarfraz Khurshid; David Soloveichik (CoRR, 2021)

MoËT: Mixture of Expert Trees and its application to verifiable reinforcement learning. - Marko Vasic; Andrija Petrovic; Kaiyuan Wang; Mladen Nikolic; Rishabh Singh; Sarfraz Khurshid (Neural Networks, 2022)