Professore Associato

Antinisca Di Marco


Performance Engineering, Context-aware software systems, Data Science, Bioinformatics
06 Ingegneria del Software
INF/01 - Informatica
Computer Science and Operations Research

Curriculum   Scholar DBLP Scopus


Bachelor theses supervised: 30 thesis at University of L’Aquila.
Master theses supervised: 10 theses in Computer Science, Mathematics, Bioinfor-matics (also at University of Rome Tor Vergata), in Applied Data Science at University of L’Aquila.
Ph.D. Students: 8 Ph.D. students since 2009 at University of L’Aquila.
  • Francesco Gallo(2009-2013, University of L’Aquila) focuseshis Ph.D. program on the study of adaptable systems. In particular, his goal was to specify and develop a framework that allows the specification and execution of reconfiguration plans. The framework is called Proteus and it follows the STEM paradigm we devised for adaptive systems, as inspired by STEM cells and ingeneral by biological cell lifecycle. The Proteus framework actually implements part of the paradigm and is composed by: (i) a language (PROTEUS Language)that defines concepts to specify reconfiguration plans, and (ii) an engine thatinterprets the plan and executes it on the real applications. Such an engine isdistributed and each Proteus resource is equipped with this engine. To developthe framework we used several programming languages (Java, Phyton, C), but thefinal release is in GROOVY language that allowed us to implement all featuresand capabilities of PROTEUS.
  • Stefano Pace (2010-2014, University of L’Aquila) developed a framework for the modeling, analysis and code generation of AGILLA-basedWireless Sensor Networks application. The devised framework permits to model the application by using UML language and specific devised UML profiles, to simulate the application behavior, and to perform timing analysis and performance analysis of multiple agents sharing a common WSN node.
  • Mai Abu-Sair: (December 2014-2018). She worked on context-aware systems. In particular, she worked on user-satisfaction and how this extra functional requirement can guide towards a soft reliability requirement of a system. She defined and modelled context variables and context situations (as a combination of context variables and thresholds) and extended a reliability model to embed such context knowledge to determine the best trade-off reconfiguration actions of a mobile system that permit to implement a context-aware system still guaranteeing user satisfaction.
  • Walter Tiberi: (November 2016-2020). The objective of his thesis is to define a security framework composed of tools, (agent-based WSN middlewares, intrusion detection systems) techniques (hybrid cryptography, elliptic curve cryptography, hardware acceleration for cryptography, blockchains as anti-tampering mechanism) and methodologies (model-based porting for WSN software applications)specifically designed for the resource constrained devices, with particular focus onWireless Sensor Networks.
  • Evans Etrue Howard (started on January 2019) is working in the contest of Territori Aperti and specifically on how to robustly allocate shelters/facilities in a prescribed safe area in an emergency logistic planning; and on how to safely evacuate/route people in-case of a natural disaster considering the uncertainties that might occur during the disaster. So his thesis will focus on robust optimization models built for pre-disaster(evacuation plan) and ”immediate-term post-disaster” (citizens evacuation) planning.
  • Ghulam Mudassir (started on January 2019) is working in the contest of Territori Aperti to realize an approach of decision-support system for post-disaster reconstruction planning of buildings damaged by a natural disaster. The proposed framework determines a set of alternative plans of a damaged area that can be a whole city or a part of it, which satisfy all constraints, accommodate political priorities, and guarantee social benefits for theaffected population. The determined plans are then provided to public servants that select the plan to implement.
  • Andrea Bianchi (started on November 2020). The development of high-throughput technologies has created a need for researchers to develop strategies for analyzingand interpreting the massive amounts of data they generate. At the same time, the growth of AI and its techniques has led to the development of several advanced tools and now researchers and doctors have access to huge volumes of data, sophisticated sensors, imaging tools, and other sources. Bioinformatics approaches are used to analyze biological data to sketch logical conclusions. Online,there is a gigantic amount of data in biological databases and the annotation ofsuch data is still a question for the researchers or doctors. In this contest, Andrea aims to combine bioinformatics and AI to improve disease diagnosis and focusing the study on individual patients. The aim is to improve the personalize medicine leveraging on the huge amount of biological data available online.
  • Giordano D’Aloisio (started on November 2021). The recently increased complexity of Machine Learning (ML) and, more in general, Artificial Intelligence (AI)systems lead to the necessity to ease machine learning pipelines realization. Moreover, since machine learning is becoming a widely used instrument, applied to allapplication domains and affecting our real life, its pipeline must comply with qual-ity constraints, such as fairness, privacy, and explainability. In his PhD, Giordanowill deal with the challenge of fully or semi-automatic generation of ML pipelinesthat respect quality constraints and that allow to easily design of the complete analytic process from the raw datasets preprocessing to the test and train of several machine learning models.
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