Christian M. Adriano
A5085962666- Software Engineering Research
- Dark Matter and Cosmic Phenomena
- Neutrino Physics Research
- Software Reliability and Analysis Research
- Particle Detector Development and Performance
- Mobile Crowdsensing and Crowdsourcing
- Innovative Teaching and Learning Methods
- Particle physics theoretical and experimental studies
- Autonomous Vehicle Technology and Safety
- Open Source Software Innovations
- Atomic and Subatomic Physics Research
- Software Testing and Debugging Techniques
- Radiation Detection and Scintillator Technologies
- Software System Performance and Reliability
- Advanced Software Engineering Methodologies
- Mobile Learning in Education
- Quantum, superfluid, helium dynamics
- Astrophysics and Cosmic Phenomena
- Neural Networks and Applications
- Business Process Modeling and Analysis
- Usability and User Interface Design
- Spreadsheets and End-User Computing
- Advanced Aircraft Design and Technologies
- Cloud Computing and Resource Management
- Bayesian Modeling and Causal Inference
Hasso Plattner Institute
2018-2024
University of Potsdam
2022-2024
Universidade Estadual de Campinas (UNICAMP)
2000-2024
University of California, Irvine
2012-2015
Microtask crowdsourcing organizes complex work into workflows, decomposing large tasks small, relatively independent microtasks. Applied to software development, this model might increase participation in open source development by lowering the barriers contribu-tion and dramatically decrease time market increasing parallelism work. To explore idea, we have developed an approach programming Work is coordinated through tracking changes a graph of artifacts, generating appropriate microtasks...
Abstract DUNE is an international experiment dedicated to addressing some of the questions at forefront particle physics and astrophysics, including mystifying preponderance matter over antimatter in early universe. The dual-site will employ intense neutrino beam focused on a near far detector as it aims determine mass hierarchy make high-precision measurements PMNS matrix parameters, CP-violating phase. It also stand ready observe supernova bursts, seeks nucleon decay signature grand...
Abstract This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The finds most probable offset track length track-like object by comparing measured ionization density as function position with theoretical prediction energy loss energy, including models electron recombination and detector response. can be used to measure that interact before they stop,...
The Module-0 Demonstrator is a single-phase 600 kg liquid argon time projection chamber operated as prototype for the DUNE near detector. Based on ArgonCube design concept, features novel 80k-channel pixelated charge readout and advanced high-coverage photon detection system. In this paper, we present an analysis of eight-day data set consisting 25 million cosmic ray events collected in spring 2021. We use sample to demonstrate imaging performance light systems well signal correlations...
A primary goal of the upcoming Deep Underground Neutrino Experiment (DUNE) is to measure $\mathcal{O}(10)$ MeV neutrinos produced by a Galactic core-collapse supernova if one should occur during lifetime experiment. The liquid-argon-based detectors planned for DUNE are expected be uniquely sensitive $\nu_e$ component flux, enabling wide variety physics and astrophysics measurements. key requirement correct interpretation these measurements good understanding energy-dependent total cross...
Abstract The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. is primary event software used at ProtoDUNE-SP, a prototype for Deep Underground Neutrino Experiment far detector. located CERN, exposed charged-particle test beam. This paper gives an overview algorithms how they have been tailored use ProtoDUNE-SP. In complex events with numerous...
Architecture-based self-adaptive systems that are rule-based can be steered by predicting changes of the system utility. However, building predictions for these is challenging. One reasons lack detailed information about performance model makes it difficult to construct an analytic representation We mitigate this problem with a methodology learn utility without relying on system. evaluated our over real range complexities and different machine learning methods trained publicly available...
Abstract The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique particularly suitable a pixelated charge readout time projection chambers, given large number channels that this technology employs. Here we present first full microphysical simulator liquid argon chamber (LArTPC) equipped with light and readout, developed DUNE Near...
Measurements of electrons from νe interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well searches physics beyond standard model, supernova detection, and solar measurements. This article describes selection reconstruction low-energy (Michel) in ProtoDUNE-SP detector. is one prototypes DUNE far detector, built operated at CERN a charged particle test beam experiment. A sample produced by decay cosmic muons selected with purity 95%....
The finer-granularity of microservices facilitate their evolution and deployment on shared resources. However, resource concurrency creates elusive interdependencies, which can cause complex interference patterns to propagate as performance anomalies across distinct applications. Meanwhile, the existing methods for Anomaly Detection (AD) Root-Cause Analysis (RCA) are confounded by this phenomenon because they operate within single call-graphs. To bridge gap, we develop a graph formalism...
Generative foundation models like Stable Diffusion comprise a diverse spectrum of knowledge in computer vision with the potential for transfer learning, e.g., via generating data to train student downstream tasks. This could circumvent necessity collecting labeled real-world data, thereby presenting form data-free distillation. However, resultant show significant drop accuracy compared trained on real data. We investigate possible causes this and focus role different layers model. By...
ProtoDUNE Single-Phase (ProtoDUNE-SP) is a 770-ton liquid argon time projection chamber that operated in hadron test beam at the CERN Neutrino Platform 2018. We present measurement of total inelastic cross section charged kaons on as function kaon energy using 6 and <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"><a:mrow><a:mn>7</a:mn><a:mtext> </a:mtext><a:mtext> </a:mtext><a:mi>GeV</a:mi><a:mo>/</a:mo><a:mi>c</a:mi></a:mrow></a:math> momentum settings. The...
Abstract Doping of liquid argon TPCs (LArTPCs) with a small concentration xenon is technique for light-shifting and facilitates the detection scintillation light. In this paper, we present results first doping test ever performed in kiloton-scale LArTPC. From February to May 2020, carried out special run single-phase DUNE Far Detector prototype (ProtoDUNE-SP) at CERN, featuring 720 t total mass 410 fiducial mass. A 5.4 ppm nitrogen contamination was during campaign. The goal measure light...
In the field of evaluation research, computer scientists live constantly upon dilemmas and conflicting theories. As is differently perceived modeled among educational areas, it not difficult to become trapped in dilemmas, which reflects an epistemological weakness. Additionally, designing developing a computer-based learning scenario easy task. Advancing further, with end-users probing system realistic settings, even harder. Computer science research faces immense challenge, having cope...
Open source software development enabled distributed teams of programmers to contribute large systems that became standards in the operation government and business. Crowdsourcing went further by enabling contributions form small independent tasks. This allowed scale from dozens hundreds people. While crowdsourcing established as industry practice areas testing, it is challenging for code related tasks, e.g., debugging. One reasons complex dependencies can make many tasks difficult partition...
In the last four years, number of distinct autonomous vehicles platforms deployed in streets California increased 6-fold, while reported accidents 12-fold. This can become a trend with no signs subsiding as it is fueled by constant stream innovations hardware sensors and machine learning software. Meanwhile, if we expect public regulators to trust vehicle platforms, need find better ways solve problem adding technological complexity without increasing risk accidents. We studied this from...
Microtask crowdsourcing is the practice of breaking down an overarching task to be performed into numerous, small, and quick microtasks that are distributed unknown, large set workers. has shown potential in other disciplines, but with only a handful approaches explored date software engineering, its our field remains unclear. In this paper, we explore how microtask might serve as means fault localization. We particularly take first step assessing whether crowd workers can correctly locate...
Measurements of electrons from $\nu_e$ interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well searches physics beyond standard model, supernova detection, and solar measurements. This article describes selection reconstruction low-energy (Michel) in ProtoDUNE-SP detector. is one prototypes DUNE far detector, built operated at CERN a charged particle test beam experiment. A sample produced by decay cosmic muons selected with purity...
Software debugging comprises most of the software maintenance time and is notorious for requiring high-level skills application specific knowledge. Crowdsourcing could lower those barriers by having each programmer perform small, self-contained parallelizable tasks, hence accommodating different levels availability expertise. Therefore, such new approach might enable society to tackle massive development efforts, as instance, setting a task force hundreds programmers debug adapt existing be...