CAIN 2022 Contributors

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A Hadil AbukwaikAbukwaik, Hadil ABB Corporate ResearchGermany TopSelect: A Topology-based Feature Selection Method for Industrial Machine Learning
Bram AdamsAdams, Bram Queen's University, Kingston, OntarioCanada Committee Member in Program Committee within the CAIN-track
David AdkinsAdkins, David Meta AI Method Cards for Prescriptive Machine-Learning Transparency
Ankit AgrawalAgrawal, Ankit University of Notre DameUnited States Committee Member in Program Committee within the CAIN-track
Hamed AlhooriAlhoori, Hamed Northern Illinois University Improving Generalizability of ML-enabled Software through Domain Specification
Bilal AlsallakhAlsallakh, Bilal Meta AI Method Cards for Prescriptive Machine-Learning Transparency
Marcel AltendeiteringAltendeitering, Marcel Fraunhofer ISSTGermany Data Sovereignty for AI Pipelines: Lessons Learned from an Industrial Project at Mondragon Corporation
Saleema AmershiAmershi, Saleema Microsoft Research Challenges in creating responsible and human-centered AI
Preethu Rose AnishAnish, Preethu Rose TCS ResearchIndia Data is about Detail: An Empirical Investigation for Software Systems with NLP at Core
Giuliano AntoniolAntoniol, Giuliano Polytechnique MontréalCanada Identification of Out-of-Distribution Cases of CNN using Class-Based Surprise Adequacy
Håkan ArdöArdö, Håkan Axis Communications, Lund, Sweden Exploring ML testing in practice - Lessons learned from an interactive rapid review with Axis Communications
B Chetan BansalBansal, Chetan Microsoft Research Committee Member in Program Committee within the CAIN-track
Earl T. BarrBarr, Earl T. University College London, UK Committee Member in Program Committee within the CAIN-track
Hamed BarzaminiBarzamini, Hamed Improving Generalizability of ML-enabled Software through Domain Specification
Nelly BencomoBencomo, Nelly Durham UniversityUnited Kingdom Committee Member in Program Committee within the CAIN-track
Johan BengtssonBengtsson, Johan Lund University Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice
Amel BennaceurBennaceur, Amel The Open UniversityUnited Kingdom Committee Member in Program Committee within the CAIN-track
Teemu BirkstedtBirkstedt, Teemu University of Turku AI Governance in the System Development Life Cycle: Insights on Responsible Machine Learning Engineering
Justus BognerBogner, Justus University of Stuttgart, Institute of Software Engineering, Empirical Software Engineering GroupGermany Towards A Methodological Framework for Production-ready AI-based Software Components
Markus BorgBorg, Markus RISE Research Institutes of SwedenSweden Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice Exploring ML testing in practice - Lessons learned from an interactive rapid review with Axis Communications
Olimar BorgesBorges, Olimar PUCRS UniversityBrazil Preliminary Insights to enable automation of the Software Development Process in Software StartUps. A Investigation Study from the use of Artificial Intelligence and Machine Learning
Jan BoschBosch, Jan Chalmers University of TechnologySweden Conference Initiator in Organizing Committee for CAIN 2022 Session Chair of Welcome to CAIN (part of CAIN) Session Chair of Closing and Awards (part of CAIN) Session Chair of Training & Learning (part of CAIN) The Goldilocks Framework: Towards Selecting the Optimal Approach to Conducting AI Projects Committee Member in Industrial Track Committee within the CAIN-track
Lionel BriandBriand, Lionel University of Luxembourg; University of OttawaLuxembourg Committee Member in Program Committee within the CAIN-track
C Christian CabreraCabrera, Christian Department of Computer Science and Technology, Univesity of Cambridge An Empirical Evaluation of Flow Based Programming in the Machine Learning Deployment Context
Fabio CalefatoCalefato, Fabio University of BariItaly Pynblint: a Static Analyzer for Python Jupyter Notebooks
Wing-Kwong ChanChan, Wing-Kwong City University of Hong Kong, Hong KongChina Committee Member in Program Committee within the CAIN-track
Adeel CheemaCheema, Adeel Meta AI Method Cards for Prescriptive Machine-Learning Transparency
Shing-Chi CheungCheung, Shing-Chi Hong Kong University of Science and TechnologyChina Committee Member in Program Committee within the CAIN-track
Jane Cleland-HuangCleland-Huang, Jane University of Notre DameUnited States PC Co-Chair in Organizing Committee for CAIN 2022 Session Chair of Welcome to CAIN (part of CAIN) Session Chair of Closing and Awards (part of CAIN) Session Chair of Keynote Saleema Amershi (part of CAIN) PC Co-Chair in Program Committee within the CAIN-track
Maxime CordyCordy, Maxime University of Luxembourg, Luxembourg Robust Active Learning: Sample-Efficient Training of Robust Deep Learning Models Influence-Driven Data Poisoning in Graph-Based Semi-Supervised Classifiers
Ivica CrnkovicCrnkovic, Ivica Chalmers University of TechnologySweden General Chair in Organizing Committee for CAIN 2022
Luís CruzCruz, Luís Deflt University of TechnologyNetherlands Data smells in Public Datasets Code Smells for Machine Learning Applications Committee Member in Program Committee within the CAIN-track
D Fabiano DalpiazDalpiaz, Fabiano Utrecht UniversityNetherlands Committee Member in Program Committee within the CAIN-track
Rimma DzhusupovaDzhusupova, Rimma McDermottNetherlands The Goldilocks Framework: Towards Selecting the Optimal Approach to Conducting AI Projects
E Emelie EngstromEngstrom, Emelie Lund UniversitySweden Exploring ML testing in practice - Lessons learned from an interactive rapid review with Axis Communications
F Aleksander FabijanFabijan, Aleksander MicrosoftUnited States Committee Member in Program Committee within the CAIN-track
Michael FeldererFelderer, Michael University of InnsbruckAustria Data Smells: Categories, Causes and Consequences, and Detection of Suspicious Data in AI-based Systems What is Software Quality for AI Engineers? Towards a Thinning of the Fog
Robert FeldtFeldt, Robert Chalmers University of Technology, SwedenSweden Committee Member in Program Committee within the CAIN-track
Stephen J FinkFink, Stephen J FacebookUnited States Committee Member in Program Committee within the CAIN-track
Harald FoidlFoidl, Harald University of InnsbruckAustria Data Smells: Categories, Causes and Consequences, and Detection of Suspicious Data in AI-based Systems
Adriano FranciFranci, Adriano University of LuxembourgLuxembourg Influence-Driven Data Poisoning in Graph-Based Semi-Supervised Classifiers
Daniel FrieselFriesel, Daniel Universität Osnabrück Black-Box Models for Non-Functional Properties of AI Software Systems
Yoshiaki FukazawaFukazawa, Yoshiaki Waseda UniversityJapan Traceable Business-to-Safety Analysis Framework for Safety-critical Machine Learning Systems
G Isabella GagnerGagner, Isabella NordAxon AB Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice
Smita GhaisasGhaisas, Smita TCS ResearchIndia Data is about Detail: An Empirical Investigation for Software Systems with NLP at Core Committee Member in Program Committee within the CAIN-track
Arda GoknilGoknil, Arda SINTEF Digital UDAVA: An Unsupervised Learning Pipeline for Sensor Data Validation in Manufacturing
Valentina GolendukhinaGolendukhina, Valentina University of Innsbruck What is Software Quality for AI Engineers? Towards a Thinning of the Fog
Ian GortonGorton, Ian Northeastern University – Seattle, USAUnited States Committee Member in Program Committee within the CAIN-track
Denise GoyaGoya, Denise UFABCBrazil MLOps: Five Steps to Guide its Effective Implementation
Martin GubriGubri, Martin University of Luxembourg, Luxembourg Influence-Driven Data Poisoning in Graph-Based Semi-Supervised Classifiers
Muhammad Ali GulzarGulzar, Muhammad Ali Virginia TechUnited States Committee Member in Program Committee within the CAIN-track
Jin L.C. GuoGuo, Jin L.C. McGill UniversityCanada Committee Member in Program Committee within the CAIN-track
Yuejun GUoGUo, Yuejun Interdisciplinary Centre for Security Robust Active Learning: Sample-Efficient Training of Robust Deep Learning Models
H Alexander HagelbornHagelborn, Alexander NordAxon AB Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice
Tim HalloranHalloran, Tim GoogleUnited States Committee Member in Industrial Track Committee within the CAIN-track
Rachel HarrisonHarrison, Rachel Oxford Brookes University United Kingdom Committee Member in Program Committee within the CAIN-track
Markus HaugHaug, Markus University of Stuttgart, Institute of Software Engineering, Empirical Software Engineering GroupGermany Towards A Methodological Framework for Production-ready AI-based Software Components
Petra HeckHeck, Petra Fontys University of Applied SciencesNetherlands What Is an AI Engineer? An Empirical Analysis of Job Ads in the Netherlands Committee Member in Program Committee within the CAIN-track
Hadi HemmatiHemmati, Hadi University of CalgaryCanada Committee Member in Program Committee within the CAIN-track
Hans-Martin HeynHeyn, Hans-Martin University of Gothenburg & Chalmers University of TechnologySweden Structural Causal Models as Boundary Objects in AI System Development
Jati Hiliamsyah HusenHiliamsyah Husen, Jati Waseda UniversityJapan Traceable Business-to-Safety Analysis Framework for Safety-critical Machine Learning Systems
Helena Holmström OlssonHolmström Olsson, Helena Malmö UniversitySweden Conference Initiator in Organizing Committee for CAIN 2022 Session Chair of Welcome to CAIN (part of CAIN) Session Chair of Closing and Awards (part of CAIN) Session Chair of Posters (part of CAIN) The Goldilocks Framework: Towards Selecting the Optimal Approach to Conducting AI Projects Posters Co-Chair in Posters Committee within the CAIN-track
Falk HowarHowar, Falk TU Dortmund UniversityGermany Data Sovereignty for AI Pipelines: Lessons Learned from an Industrial Project at Mondragon Corporation
Qiang HuHu, Qiang University of Luxembourg Robust Active Learning: Sample-Efficient Training of Robust Deep Learning Models
Erik Johannes HusomHusom, Erik Johannes SINTEF Digital UDAVA: An Unsupervised Learning Pipeline for Sensor Data Validation in Manufacturing
I Maki InuiInui, Maki Fujitsu LimitedJapan A New Approach for Machine Learning Security Risk Assessment
Fuyuki IshikawaIshikawa, Fuyuki National Institute of InformaticsJapan Practical Insights of Repairing Model Problems on Image Classification
J Brittany JohnsonJohnson, Brittany George Mason UniversityUnited States Committee Member in Program Committee within the CAIN-track
K Gail KaiserKaiser, Gail Columbia UniversityUnited States Committee Member in Program Committee within the CAIN-track
Ali KansoKanso, Ali Microsoft Engineering a Platform for Reinforcement Learning Workloads
Fumiyoshi KasaharaKasahara, Fumiyoshi Fujitsu LimitedJapan A New Approach for Machine Learning Security Risk Assessment
Foutse KhomhKhomh, Foutse Polytechnique MontréalCanada Identification of Out-of-Distribution Cases of CNN using Class-Based Surprise Adequacy Committee Member in Program Committee within the CAIN-track
Eric KnaussKnauss, Eric Chalmers \| University of GothenburgSweden Structural Causal Models as Boundary Objects in AI System Development Committee Member in Program Committee within the CAIN-track
Narine KokhlikyanKokhlikyan, Narine Meta AI Method Cards for Prescriptive Machine-Learning Transparency
Anne KoziolekKoziolek, Anne Karlsruhe Institute of TechnologyGermany Committee Member in Program Committee within the CAIN-track
Iva KrastevaKrasteva, Iva Sofia University, GATE InstituteBulgaria Posters Co-Chair in Organizing Committee for CAIN 2022 Session Chair of Welcome to CAIN (part of CAIN) Session Chair of Closing and Awards (part of CAIN) Session Chair of Posters (part of CAIN) Posters Co-Chair in Posters Committee within the CAIN-track
L Samuli LaatoLaato, Samuli University of TurkuFinland AI Governance in the System Development Life Cycle: Insights on Responsible Machine Learning Engineering
Filippo LanubileLanubile, Filippo University of BariItaly Pynblint: a Static Analyzer for Python Jupyter Notebooks Committee Member in Program Committee within the CAIN-track
Felix LarrinagaLarrinaga, Felix Mondragon Unibertsitatea Data Sovereignty for AI Pipelines: Lessons Learned from an Industrial Project at Mondragon Corporation
Neil D. LawrenceLawrence, Neil D. Department of Computer Science and Technology, Univesity of Cambridge An Empirical Evaluation of Flow Based Programming in the Machine Learning Deployment Context
Yves Le TraonLe Traon, Yves University of Luxembourg, LuxembourgLuxembourg Robust Active Learning: Sample-Efficient Training of Robust Deep Learning Models Influence-Driven Data Poisoning in Graph-Based Semi-Supervised Classifiers
Wei LeLe, Wei Iowa State UniversityUnited States Committee Member in Program Committee within the CAIN-track
Noah LeeLee, Noah Meta Platforms, Inc. Committee Member in Program Committee within the CAIN-track
Jon LegaristiLegaristi, Jon Mondragon Unibertsitatea Data Sovereignty for AI Pipelines: Lessons Learned from an Industrial Project at Mondragon Corporation
Valentina LenarduzziLenarduzzi, Valentina University of OuluFinland What is Software Quality for AI Engineers? Towards a Thinning of the Fog Preliminary Insights to enable automation of the Software Development Process in Software StartUps. A Investigation Study from the use of Artificial Intelligence and Machine Learning
Grace LewisLewis, Grace Carnegie Mellon Software Engineering InstituteUnited States Committee Member in Program Committee within the CAIN-track
Hongyu LiuLiu, Hongyu Huawei Galois Lab, ChinaChina Automatic Checkpointing and Deterministic Training for Deep Learning
David LoLo, David Singapore Management UniversitySingapore Committee Member in Program Committee within the CAIN-track
Qinghua LuLu, Qinghua CSIRO’s Data61Australia Towards a Roadmap for Software Engineering for Responsible AI
Lucy Ellen LwakatareLwakatare, Lucy Ellen University of HelsinkiFinland Proceedings Chair in Organizing Committee for CAIN 2022 Session Chair of Welcome to CAIN (part of CAIN) Session Chair of Closing and Awards (part of CAIN) Session Chair of AI Models & Pipelines (part of CAIN)
Michael LyuLyu, Michael The Chinese University of Hong Kong Committee Member in Program Committee within the CAIN-track
M Jie M. ZhangM. Zhang, Jie King's College LondonUnited Kingdom Committee Member in Program Committee within the CAIN-track
Mira MarhabaMarhaba, Mira Polytechnique MontrealCanada Identification of Out-of-Distribution Cases of CNN using Class-Based Surprise Adequacy
Beatriz MatsuiMatsui, Beatriz UFABCBrazil MLOps: Five Steps to Guide its Effective Implementation
Emily McReynoldsMcReynolds, Emily Meta AI Method Cards for Prescriptive Machine-Learning Transparency
Marcel MeestersMeesters, Marcel Fontys University of Applied Sciences What Is an AI Engineer? An Empirical Analysis of Job Ads in the Netherlands
Tim MenziesMenzies, Tim North Carolina State UniversityUnited States Committee Member in Program Committee within the CAIN-track
Ettore MerloMerlo, Ettore Polytechnique MontrealCanada Identification of Out-of-Distribution Cases of CNN using Class-Based Surprise Adequacy
Mira MeziniMezini, Mira TU DarmstadtGermany Committee Member in Program Committee within the CAIN-track
Tommi MikkonenMikkonen, Tommi University of Helsinki AI Governance in the System Development Life Cycle: Insights on Responsible Machine Learning Engineering Committee Member in Program Committee within the CAIN-track
Matti MinkkinenMinkkinen, Matti University of Turku AI Governance in the System Development Life Cycle: Insights on Responsible Machine Learning Engineering
Pushkar MishraMishra, Pushkar Meta AI Method Cards for Prescriptive Machine-Learning Transparency
Ikuya MorikawaMorikawa, Ikuya Fujitsu LimitedJapan A New Approach for Machine Learning Security Risk Assessment
Henry MucciniMuccini, Henry University of L'Aquila, ItalyItaly Conference Promotor in Organizing Committee for CAIN 2022 Session Chair of Welcome to CAIN (part of CAIN) Session Chair of Closing and Awards (part of CAIN) Session Chair of Quality Assurance (part of CAIN)
Matti MäntymäkiMäntymäki, Matti University of Turku AI Governance in the System Development Life Cycle: Insights on Responsible Machine Learning Engineering
N Tien N. NguyenNguyen, Tien N. University of Texas at Dallas Committee Member in Program Committee within the CAIN-track
O Takanori OikawaOikawa, Takanori Fujitsu LimitedJapan A New Approach for Machine Learning Security Risk Assessment
Ipek OzkayaOzkaya, Ipek Carnegie Mellon Software Engineering InstituteUnited States Industrial Chair in Organizing Committee for CAIN 2022 Session Chair of Welcome to CAIN (part of CAIN) Session Chair of AI Engineering Practices (part of CAIN) Session Chair of Closing and Awards (part of CAIN) Session Chair of AI Smells (part of CAIN) Industrial Chair in Industrial Track Committee within the CAIN-track
P Andrei PaleyesPaleyes, Andrei Department of Computer Science and Technology, Univesity of Cambridge An Empirical Evaluation of Flow Based Programming in the Machine Learning Deployment Context
Julia PampusPampus, Julia Fraunhofer ISST Data Sovereignty for AI Pipelines: Lessons Learned from an Industrial Project at Mondragon Corporation
Mike PapadakisPapadakis, Mike University of Luxembourg, LuxembourgLuxembourg Robust Active Learning: Sample-Efficient Training of Robust Deep Learning Models Influence-Driven Data Poisoning in Graph-Based Semi-Supervised Classifiers Committee Member in Program Committee within the CAIN-track
Kinshuman PatraPatra, Kinshuman Microsoft Engineering a Platform for Reinforcement Learning Workloads
Patrizio PelliccionePelliccione, Patrizio Gran Sasso Science Institute, L'Aquila, ItalyItaly Committee Member in Program Committee within the CAIN-track
Mauro PezzePezze, Mauro USI Lugano; Schaffhausen Institute of TechnologySwitzerland Committee Member in Program Committee within the CAIN-track
Barbara PlankPlank, Barbara IT University of Copenhagen, DK Committee Member in Program Committee within the CAIN-track
Rafael PrikladnickiPrikladnicki, Rafael School of Technology at PUCRS UniversityBrazil Preliminary Insights to enable automation of the Software Development Process in Software StartUps. A Investigation Study from the use of Artificial Intelligence and Machine Learning Committee Member in Program Committee within the CAIN-track
Chavez ProcopeProcope, Chavez Meta AI Method Cards for Prescriptive Machine-Learning Transparency
Corina S. PăsăreanuPăsăreanu, Corina S. Carnegie Mellon UniversityUnited States Committee Member in Program Committee within the CAIN-track
Q Luigi QuarantaQuaranta, Luigi University of Bari, ItalyItaly Pynblint: a Static Analyzer for Python Jupyter Notebooks
R Chaiyong RagkhitwetsagulRagkhitwetsagul, Chaiyong Mahidol University, ThailandThailand Committee Member in Program Committee within the CAIN-track
Mona RahimiRahimi, Mona Northern Illinois UniversityUnited States Improving Generalizability of ML-enabled Software through Domain Specification Committee Member in Program Committee within the CAIN-track
Rudolf RamlerRamler, Rudolf Software Competence Center HagenbergAustria Data Smells: Categories, Causes and Consequences, and Detection of Suspicious Data in AI-based Systems
Baishakhi RayRay, Baishakhi Columbia UniversityUnited States Committee Member in Program Committee within the CAIN-track
Sergio RicoRico, Sergio Lund University, SwedenSweden Exploring ML testing in practice - Lessons learned from an interactive rapid review with Axis Communications
Pablo RodriguezRodriguez, Pablo ABBGermany TopSelect: A Topology-based Feature Selection Method for Industrial Machine Learning
Per RunesonRuneson, Per Lund UniversitySweden Committee Member in Program Committee within the CAIN-track
Barbara RussoRusso, Barbara Free University of BolzanoItaly Committee Member in Program Committee within the CAIN-track
Christopher RéRé, Christopher Software 2.0, Foundation Models, Data-Centric AI, and why I’m excited enough to tolerate these buzzwords
S Jeremy SawrukSawruk, Jeremy Meta AI Method Cards for Prescriptive Machine-Learning Transparency
Sagar SenSen, Sagar UDAVA: An Unsupervised Learning Pipeline for Sensor Data Validation in Manufacturing
Alexander SerebrenikSerebrenik, Alexander Eindhoven University of TechnologyNetherlands What Is an AI Engineer? An Empirical Analysis of Job Ads in the Netherlands
Murtuza ShahzadShahzad, Murtuza Northern Illinois University Improving Generalizability of ML-enabled Software through Domain Specification
Emad ShihabShihab, Emad Concordia UniversityCanada Committee Member in Program Committee within the CAIN-track
Arumoy ShomeShome, Arumoy Delft University of TechnologyNetherlands Data smells in Public Datasets
Norbert SiegmundSiegmund, Norbert Leipzig UniversityGermany Committee Member in Program Committee within the CAIN-track
Anmol SinghalSinghal, Anmol TCS Research Data is about Detail: An Empirical Investigation for Software Systems with NLP at Core
Dirk SlamaSlama, Dirk Bosch, Ferdinand-Steinbeis-Institute Committee Member in Program Committee within the CAIN-track
Carol J. SmithSmith, Carol J. Software Engineering Institute - Carnegie Mellon UniversityUnited States Committee Member in Industrial Track Committee within the CAIN-track
Pratik SonarSonar, Pratik TCS Research Data is about Detail: An Empirical Investigation for Software Systems with NLP at Core
Qunying SongSong, Qunying Lund UniversitySweden Exploring ML testing in practice - Lessons learned from an interactive rapid review with Axis Communications
Olaf SpinczykSpinczyk, Olaf Universität Osnabrück Black-Box Models for Non-Functional Properties of AI Software Systems
Lefter SulaSula, Lefter ABB Corporate Research CenterGermany TopSelect: A Topology-based Feature Selection Method for Industrial Machine Learning
Jun SunSun, Jun Singapore Management UniversitySingapore Committee Member in Program Committee within the CAIN-track
T Hironori TakeuchiTakeuchi, Hironori Musashi UniversityJapan Traceable Business-to-Safety Analysis Framework for Safety-critical Machine Learning Systems
Kla TantithamthavornTantithamthavorn, Kla Monash UniversityAustralia Committee Member in Program Committee within the CAIN-track
Guanhong TaoTao, Guanhong Purdue University, USA Automatic Checkpointing and Deterministic Training for Deep Learning
Patanamon ThongtanunamThongtanunam, Patanamon University of MelbourneAustralia Committee Member in Program Committee within the CAIN-track
Susumu TokumotoTokumoto, Susumu Fujitsu LimitedJapan Practical Insights of Repairing Model Problems on Image Classification
Piotr TomaszewskiTomaszewski, Piotr RISE Research Institutes of Sweden Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice
Hnin Thandar TunTun, Hnin Thandar Waseda UniversityJapan Traceable Business-to-Safety Analysis Framework for Safety-critical Machine Learning Systems
Simeon TverdalTverdal, Simeon SINTEF Digital UDAVA: An Unsupervised Learning Pipeline for Sensor Data Validation in Manufacturing
V Karthik VaidhyanathanVaidhyanathan, Karthik University of L'AquilaItaly Committee Member in Program Committee within the CAIN-track
Arie van Deursenvan Deursen, Arie Delft University of Technology, NetherlandsNetherlands Data smells in Public Datasets Code Smells for Machine Learning Applications
Joost VisserVisser, Joost Leiden UniversityNetherlands Committee Member in Industrial Track Committee within the CAIN-track
W Erin WangWang, Erin Meta AI Method Cards for Prescriptive Machine-Learning Transparency
Song WangWang, Song York UniversityCanada Committee Member in Program Committee within the CAIN-track
Hironori WashizakiWashizaki, Hironori Waseda UniversityJapan Traceable Business-to-Safety Analysis Framework for Safety-critical Machine Learning Systems
Jon WhittleWhittle, Jon CSIRO's Data61 and Monash UniversityAustralia Towards a Roadmap for Software Engineering for Responsible AI
X Xin XiaXia, Xin Huawei Software Engineering Application Technology LabChina Committee Member in Program Committee within the CAIN-track
Tao XieXie, Tao Peking UniversityChina Committee Member in Program Committee within the CAIN-track
Zhenchang XingXing, Zhenchang Australian National UniversityAustralia Towards a Roadmap for Software Engineering for Responsible AI
Xiangzhe XuXu, Xiangzhe Purdue University Automatic Checkpointing and Deterministic Training for Deep Learning
Xiwei (Sherry) XuXu, Xiwei (Sherry) CSIRO Data61Australia Towards a Roadmap for Software Engineering for Responsible AI
Zhou XuanXuan, Zhou Purdue University Automatic Checkpointing and Deterministic Training for Deep Learning
Y Jun YajimaYajima, Jun Fujitsu LimitedJapan A New Approach for Machine Learning Security Risk Assessment
Akihito YoshiiYoshii, Akihito Fujitsu LimitedJapan Practical Insights of Repairing Model Problems on Image Classification
Nobukazu YoshiokaYoshioka, Nobukazu Waseda University, JapanJapan A New Approach for Machine Learning Security Risk Assessment Traceable Business-to-Safety Analysis Framework for Safety-critical Machine Learning Systems
Z Haiyin ZhangZhang, Haiyin AI for Fintech Research, ING Code Smells for Machine Learning Applications
Tianyi ZhangZhang, Tianyi Purdue UniversityUnited States Committee Member in Program Committee within the CAIN-track
Xiangyu ZhangZhang, Xiangyu Purdue UniversityUnited States Automatic Checkpointing and Deterministic Training for Deep Learning Committee Member in Program Committee within the CAIN-track
Hao ZhongZhong, Hao Shanghai Jiao Tong University Committee Member in Program Committee within the CAIN-track
Liming ZhuZhu, Liming CSIRO’s Data61; UNSWAustralia Towards a Roadmap for Software Engineering for Responsible AI Committee Member in Industrial Track Committee within the CAIN-track
Roshanak Zilouchian MoghaddamZilouchian Moghaddam, Roshanak Microsoft Committee Member in Program Committee within the CAIN-track
Thomas ZimmermannZimmermann, Thomas Microsoft ResearchUnited States Program Co-Chair in Organizing Committee for CAIN 2022 Session Chair of Welcome to CAIN (part of CAIN) Session Chair of Keynote Christopher Re (part of CAIN) Session Chair of Closing and Awards (part of CAIN) Session Chair of AI Smells (part of CAIN) Program Co-Chair in Program Committee within the CAIN-track
Polina ZvyaginaZvyagina, Polina Meta AI Method Cards for Prescriptive Machine-Learning Transparency
Ö Harald ÖsterlingÖsterling, Harald Lund University Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice