Triantafyllia Liana Konstantinidou serves as a Professor of German as a Foreign and Second Language at the Institute of Language Competence , Zurich University of Applied Sciences (ZHAW). Her work bridges academic research with practical applications in vocational education contexts. Current Affiliation: Director of European Literacy Network (2023-2028) Advisor to Internationaler Verband für Deutschlehrer:innen (IDV) since 2021 Her research focuses on vocational literacy , plurilingual competence development , and technology-enhanced language learning . Key projects include: Digital Literacy Skills (completed 2024) Literacy for Entrepreneurship (completed 2024) Integrated Reading-Writing Support (completed 2024) Recent publications analyze writing competence profiles in vocational contexts and explore scenario-based literacy education across diverse professional fields. Her work demonstrates strong connections between corpus linguistics , language testing , and educational policy .
Shashi Kumar is a doctoral student in the Doctoral Program in Electrical Engineering (EDDEE) at École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the School of Engineering (STI) and the IDIAP Research Institute (LIDIAP) . He holds the role of Doctoral Assistant at LIDIAP, contributing to research in speech technology and machine learning. His work focuses on advancing automatic speech recognition (ASR), optimal transport frameworks, and variational autoencoders for speech enhancement and signal processing. Research interests include speech recognition systems , multimodal task unification , far-field speech processing , and machine learning applications in signal processing and computer vision. His publications highlight contributions to SLAM-ASR performance analysis, joint speaker change detection, and PCB defect classification using image segmentation techniques. Shashi's research is anchored at the IDIAP Research Institute , where he collaborates on projects involving deep learning, audio signal processing, and speech technology. While no awards or grants are explicitly listed, his work reflects active engagement in international challenges like the Interspeech DiCOVA competition.
Giorgia Ramponi is an Assistant Professor with Tenure Track at the Faculty of Business, Economics and Informatics at the University of Zurich. She is also an affiliated professor at the ETH AI Center and the Data Science and AI, Computer Science and Engineering department at Chalmers University of Technology. Her educational background includes a Ph.D. in Information Technology from Politecnico di Milano (completed June 2021 with honors), advised by Marcello Restelli, and a Master of Science in Computer Science with Honours Programme (110/110 cum laude) from la Sapienza (July 2017), advised by Flavio Chierichetti and Alessandro Panconesi. Dr. Ramponi's research focuses on machine learning and mathematical modeling, with particular emphasis on reinforcement learning and multiagent learning. Her work bridges theoretical foundations with practical applications, exploring how learning algorithms can make optimal decisions in complex environments. She has made significant contributions to areas including inverse reinforcement learning, multi-agent systems, constrained Markov decision processes, and human-AI interaction through preference learning. Her recent publications demonstrate a strong trend toward addressing fundamental challenges in reinforcement learning, particularly in multi-agent settings, constrained optimization, and learning from human feedback. Her work combines theoretical rigor with practical applications across robotics, economics, and decision-making systems. Hassler Research Grant for "Unified Feedback Integration Framework for Reinforcement Learning" Dr. Ramponi actively contributes to the academic community through conference participation, invited lectures (including at the Mediterranean Machine Learning Summer School), and teaching. She designed and taught the "Data Science and Machine Learning" course for the ETH-Ashesi Master program. She is also a member of the ELLIS community, which connects excellence in AI research across Europe. Her research group focuses on developing frameworks for reinforcement learning with various feedback types, including preferences, rewards, and demonstrations. The group aims to advance the theoretical understanding of learning algorithms while addressing practical challenges in real-world applications.
Dr. Christina Haag is a postdoctoral researcher at the Institute for Implementation Science in Health Care , affiliated with the Faculty of Medicine at the University of Zurich . She leads interdisciplinary projects at the intersection of mental health, digital health, and computational linguistics, focusing on chronic illnesses like multiple sclerosis (MS). Her work leverages free text, sensor data, and advanced analysis techniques such as hierarchical modeling and natural language processing (NLP). Doctorate from the Institute of Psychology, University of Zurich Research experience at the MRC Cognition & Brain Sciences Unit, University of Cambridge Her research explores: Daily-life mental and physical health indicators in MS Development of NLP methods for text classification and topic modeling Digital biomarker creation using wearable sensor data Mindfulness interventions for affective executive control Implementation of remote monitoring tools in healthcare Her recent publications highlight trends in applying NLP and machine learning to unstructured health data, analyzing MS activity patterns, and refining interdisciplinary research methodologies. She contributes to DSI communities including AI & Law , Health , and Ethics , and collaborates on projects like BarKA-MS and DSI-Approach . She is a core member of the UZH Digital & Mobile Health Group , working under Prof. Viktor von Wyl.
Robert Soulé is an Associate Professor in the Departments of Computer Science and Electrical Engineering at Yale University, and holds an Adjunct Professor position at the Università della Svizzera italiana (USI) in Lugano, Switzerland. His research focuses on distributed systems, networking, and applied programming languages, with notable contributions to in-network computing, consensus protocols, and energy-efficient systems. He received his B.A. from Brown University and his Ph.D. from New York University, followed by postdoctoral work at Cornell University. Education: B.A. in Computer Science, Brown University, 1999 Ph.D. in Computer Science, New York University, 2012 Research Interests: Dr. Soulé’s work spans distributed systems, networking, and programming languages, emphasizing practical systems such as in-network computing, consensus algorithms (e.g., NetPaxos), and carbon-aware networking. His research bridges theory and practice, addressing challenges in scalability, performance, and sustainability. Articles Trends: Recent work includes innovations in quantum networks (algebraic specifications), carbon-aware networking (energy efficiency), and system optimization (e.g., P4-based data plane verification). He explores network programmability, microservices acceleration, and zero-copy serialization techniques. Awards: Best Paper Awards at ACM DEBS 2012, NSDI 2018, and CoNEXT 2020 Google Faculty Research Award IBM Invention Plateau Award Advising and Grants: He has advised numerous PhD students and postdocs, including Pietro Bressana (Intel Corporation) and Theo Jepsen (Stanford Postdoc). His grants support projects in networked systems, distributed computing, and sustainable infrastructure. Labs/Teams: Active in Yale’s Systems Research group, collaborating on projects like NetChain (sub-RTT coordination) and P4-based systems (e.g., P4xos for consensus). Engages with industry through partnerships on microservices optimization and energy-efficient networking.
Dr. Felix Härer is a Lecturer and researcher at the University of Applied Sciences FHNW, School of Business, Basel, Switzerland, and also teaches externally at the University of Fribourg. He is affiliated with the Digital Trust Competence Center, where he conducts research and teaching in IT Security, Cybersecurity, Digital Trust, Blockchain, AI, Cloud Computing, and Systems Modeling. His research interests span a broad and interdisciplinary range, including: Digital Trust and Cybersecurity Blockchain and Decentralized Systems AI and Knowledge-based Systems (including LLMs and RAG) Software and Systems Modeling (BPMN, ArchiMate) Data Science and ETL-based Analytics Zero Trust and Secure Architectures His recent publications (2020–2023) demonstrate a strong focus on blockchain interoperability, model-driven engineering, decentralized applications, and the integration of AI with conceptual modeling. He explores scalable architectures, cross-chain query languages, and secure attestation mechanisms, often combining modeling approaches with emerging technologies. His work bridges academic rigor with practical implementation in distributed and cloud environments. Scientific awards include: Best Paper Award at IEEE PKIA 2023 He actively supervises bachelor’s and master’s theses and student projects in digital trust and related domains. He has served on PhD committees externally and is a reviewer and program committee member for journals and conferences such as IEEE Transactions, WWW, CAiSE, and EMISAJ. His professional experience includes industry work at Siemens Healthineers in software engineering. He is a member of the IEEE Blockchain Group (Switzerland) and contributes to UN/CEFACT standards for e-commerce and supply chain data. He is involved in organizing workshops and conferences, including B4ISE 2025, B4TDS 2023–2024, and DESRIST 2023, and has delivered keynotes on Computational Trust and Blockchain Interoperability.
Matthias Bannert is a Lecturer at the Department of Management, Technology, and Economics at ETH Zürich, where he works at the KOF Swiss Economic Institute (Konjunkturforschungsstelle). His work focuses on the intersection of economics, software development, and data management, with particular expertise in time series analysis and official statistics. Bannert designs solutions for state-of-the-art data processing, management, and publishing of economic data and research. Bannert completed his doctoral thesis titled "Survey Based Research in Economics - Essays on Methodology, Economic Applications and Long Term Processing of Economic Survey Data" at ETH Zürich in 2016. His academic journey began when he joined KOF in late 2008, initially working as a researcher for the Business Tendency Survey group before transitioning to the institute's IT department. Dr. Bannert's research interests span several interconnected domains at the nexus of economics and data science. He specializes in developing software environments for official statistics, with particular focus on processing and managing economic time series data through open-source driven data pipelines. His technical expertise includes R programming and PostgreSQL database systems, which he applies to create robust solutions for economic data analysis. Bannert is particularly interested in survey methodology, nowcasting techniques, and the development of reproducible research workflows. His work bridges the gap between theoretical economics and practical software implementation, ensuring that economic research can leverage state-of-the-art data processing techniques. Analysis of Bannert's publication record reveals a consistent focus on the application of data science techniques to economic research problems, particularly in the domain of official statistics and survey-based economics. His work demonstrates a progression from theoretical survey methodology to practical software implementation, with increasing emphasis on real-time economic forecasting and data management systems. A distinctive feature of his research is the development of open-source R packages that make advanced economic data analysis more accessible to researchers and practitioners. As an active contributor to the R language for Statistical computing and the open source community, Bannert has developed several notable software packages including timeseriesdb, tstools, and kofdata, which are available on CRAN. These tools reflect his commitment to creating reproducible, transparent, and efficient workflows for economic data analysis. Bannert serves as a data science supervisor for multiple KOF research projects and is a co-Principal Investigator in an SNF-funded Digital Lives project in collaboration with KOF's labor market expert group. His teaching activities include "Hacking for Sciences - An Applied Guide to Programming with Data" and involvement in the Nowcasting Lab, which provides live out-of-sample forecasting and model testing capabilities for economic researchers. Dr. Bannert is affiliated with the KOF Swiss Economic Institute, where he contributes to several research groups including the KOF Macroeconomic Forecasting group and the KOF Data Science and Macroeconomic Methods group. His work at KOF bridges the institute's traditional economic research with modern data science approaches, helping to position the institute at the forefront of data-driven economic analysis.
Andreas Hein is an Assistant Professor of IT Management at the University of St. Gallen's Institute of Information Systems and Digital Business (IWI-HSG). His research focuses on digital services, AI literacy, conversational agents, and ethical design in education and business contexts. He holds a PhD (summa cum laude) from the University of Kassel and has led projects funded by SNSF and Innosuisse. Hein is an AIS Distinguished Member Cum Laude and has received numerous awards for research and academic service, including the AIS Best Conference Paper Award (2024) and Best Paper Awards at DESRIST (2023) and HICSS (2020). His work bridges design science and interdisciplinary collaboration, addressing topics like privacy nudges, gamification in learning, and lawful technology development. Hein actively contributes to academic communities, serving as associate editor for ECIS, ICIS, and AOM divisions, and has organized conferences like the Wirtschaftsinformatik-Nachwuchs-Treffen 2023. His teaching spans undergraduate to graduate levels, emphasizing data-driven service innovation and research practices. Hein's research has been published in top journals (ISR, JAIS, EJIS) and frequently recognized for innovation and impact. Education: PhD in Business Information Systems (Kassel University, 2018), Master of Arts in Communication Management, Diplom in Economic Sciences (Kassel University). Key Achievements: Over €2.2m in third-party funding, 60+ co-authors, and impactful contributions to digital education and AI ethics. His work on privacy nudges and conversational agents has been featured in leading conferences and journals.
Manos Athanassoulis is an Associate Professor in the Department of Computer Science at the College of Arts and Sciences, Boston University. He is the Founder and Director of the BU Data-intensive Systems and Computing (DiSC) lab and a member of the BU MiDAS group. His research focuses on data systems, particularly cloud data management, hybrid transactional/analytical workloads, and integration with emerging hardware such as non-volatile memory and heterogeneous computing. His educational background includes a PhD from EPFL (2014), an MSc in Computer Systems Technology, and a BSc in Informatics and Telecommunications from the University of Athens, Greece. Prior to BU, he was a Postdoctoral Researcher and Research Associate at Harvard University, supported by a SNSF Postdoc Mobility Fellowship. His research interests span data systems, database architectures, LSM trees, indexing, storage systems, and performance optimization. He explores how novel hardware can be leveraged to improve data management efficiency and scalability, especially in cloud environments. His recent publications (2021–2025) predominantly focus on LSM trees, covering topics such as compaction policies, Bloom filter tuning, DPU offloading, adversarial resilience, and sustainable caching. Earlier works include foundational contributions on access methods (RUM Conjecture) and optimal key-value stores (Monkey). The trend shows a consistent focus on data system efficiency, adaptability, and robustness under varying workloads and hardware constraints. Scientific Awards: NSF CAREER Award (2022) Facebook Faculty Research Award (2020) NSF CRII Award (2019) Best of VLDB 2017 and Best of SIGMOD 2017 SIGMOD Most Reproducible Paper Award (2017) Multiple ACM SIGMOD Distinguished PC Member recognitions (2018–2025) VLDB 2023 Best Demo Award RedHat Collaboratory Research Incubation Awards (multiple, 2021–2023) SNSF Postdoc Mobility Fellowship (2015–16) IBM PhD Fellowship (2011–12) Dr. Athanassoulis has advised numerous students and collaborators, evident from his co-authorship on works with researchers such as Niv Dayan, Stratos Idreos, and A. Ailamaki. His grants include major awards from NSF, Facebook, and RedHat, supporting research in robust data systems, hardware-software co-design, and learned cost models. He has also been recognized for teaching excellence at Harvard University. He leads the DiSC lab at Boston University, which focuses on data-intensive computing and systems research. The lab explores next-generation data architectures, particularly in cloud and hardware-aware environments. Collaborations with the BU MiDAS group enhance interdisciplinary research in data science and AI.
Krisztian Balog is a Professor of Computer Science at the University of Stavanger and a Staff Research Scientist at Google DeepMind. His work focuses on advancing AI-driven information retrieval, natural language processing, and machine learning for user-centric systems. Key affiliations include co-organizing the Sim4IA 2025 Workshop at SIGIR, leading tutorials on user simulation in generative AI, and directing the NorwAI research center’s PhD project on LLMs for recommendations. Research Interests: User simulation, conversational AI, transparency in recommender systems, and simulation frameworks like SimIIR 3 . Scientific Recognition: Recipient of the Karen Spärck Jones Award (2018) and Best Resource Paper Award at CIKM’23 . Leadership: Serves on program committees for SIGIR, WSDM, WWW, and ECIR. Co-organized workshops and tutorials at SIGIR, AAAI, and WWW. Recent Publications highlight advancements in user simulation methodologies, generative AI applications, and open web infrastructure (e.g., SimIIR 3 , OpenWebSearch.eu ). His work bridges theoretical models (e.g., Markov Decision Processes) with practical toolkits for synthetic data generation and system evaluation.
Silvia Cascianelli is an AI and Computer Vision Researcher at the University of Modena and Reggio Emilia (UNIMORE). She actively contributes to the computer vision and document analysis communities through research, conference organization, and academic mentorship. She serves as Area Chair for major computer vision conferences including CVPR2025, BMVC2025, and ECCV2024, demonstrating her standing in the field. Her research focuses on several key areas within computer vision and document analysis: Image Generation : Developing efficient and lightweight methods for image generation with desired characteristics, particularly using diffusion models Handwriting Imitation : Creating algorithms for generating images of text with specific content and handwriting styles, along with evaluation methods Document Understanding : Extracting information from 2D and 3D document images, ranging from modern documents to historical artifacts like carbonized Roman papyri Dr. Cascianelli's work shows a clear progression toward more sophisticated generative models and evaluation frameworks, with recent publications focusing on diffusion models for handwritten text generation, efficient token reduction for multimodal tasks, and innovative approaches to historical document analysis. Her research bridges theoretical advancements with practical applications across diverse document types. Her scientific contributions have been recognized through invitations to serve as Area Chair for top-tier computer vision conferences (CVPR, ECCV, BMVC) and opportunities to organize specialized workshops including VisionDocs at ICCV, AI4DH at ECCV, and ADAPDA at ICDAR. Area Chair at CVPR2025 Area Chair at BMVC2025 Area Chair at ECCV2024 Organizer of VisionDocs Workshop at ICCV2025 Organizer of AI for Digital Humanities Workshop at ECCV2024 Organizer of ADAPDA Workshop at ICDAR2024 Dr. Cascianelli actively mentors the next generation of researchers: Vittorio Pippi - PhD Student at UniMoRe (National PhD program in AI) Fabio Quattrini - PhD Student at UniMoRe (ICT program) Carmine Zaccagnino - Research Intern at UniMoRe (formerly MSc student) Kostantina Nikolaidou - PhD Student at Luleå University of Technology Pau Torras Coloma - PhD Student at Computer Vision Center, Universitat Autònoma de Barcelona Bram Vanherle - CV Engineer at Colruyt Group Smart Innovation (formerly PhD student) She is actively involved in several research initiatives including the AI Governance Lab where she serves as a lecturer, and collaborates with institutions worldwide. Her current projects focus on advancing diffusion models for image generation, improving handwritten text recognition systems, and developing novel methods for document understanding across historical and contemporary contexts.
PD Dr. Kaspar Riesen is the Head of the Pattern Recognition Group at the Institute of Computer Science, University of Bern. His research focuses on graph-based methods for pattern recognition, with applications in document analysis, environmental modeling, and healthcare. Key interests include graph matching, neural networks, and spatio-temporal modeling. His work spans structural pattern recognition, graph embeddings, and keyword spotting in historical documents. Recent projects involve river network analysis using graph regression and hypoglycemia prediction via LSTM-GNN hybrid models. Publications emphasize graph theory advancements, such as normalized graph compression and geometric similarity learning. Collaborations include developing specialized algorithms for automated error detection and improving decision-making in simulated sports. Labs/Teams: Pattern Recognition Group (PRG) at the University of Bern.
Prof. Dr. Miriam A. Locher is a Professor of the Linguistics of English at the University of Basel's Department of Languages and Literatures within the Faculty of Humanities and Social Sciences. She teaches in the BA English, MA English, and MA Language and Communication programs and is a member of the eucor Hermann-Paul School of Linguistics for PhD students in linguistics. Her research focuses on interpersonal pragmatics, linguistic politeness, relational work, and computer-mediated communication. She has led projects such as 'Language and Health Online' (SNF 2012–2016) and currently explores 'Pragmatics of Fiction: Lay subtitling and online communal viewing' (UniBas 2019-current). Her research output includes monographs on pragmatics in translation, corpus pragmatics, and the pragmatics of fiction. She edits the 'Pragmatics & Beyond New Series' for Benjamins and the 'Journal of Pragmatics'. Locher administers the SWELL mailing list for Swiss English linguistics researchers. Her work bridges theoretical and applied linguistics, with a focus on digital discourse, health communication, and fan translation practices. Recent publications emphasize online interaction dynamics, such as fan translations of Korean TV dramas and communal viewing practices on platforms like Viki. She explores how humor, emotive stance, and relational work shape communication in digital spaces. Her research integrates cross-cultural and global perspectives, addressing politeness and impoliteness in diverse contexts. Locher’s contributions to pragmatics highlight the evolving role of media and technology in shaping linguistic practices and social interactions.
Florian Eugster serves as Associate Professor of Auditing at the University of St. Gallen (HSG), Switzerland, where his research and teaching focus on auditing, financial accounting, and valuation. Based in St. Gallen at Tigerbergstrasse 9 (Office 57-106), he maintains an active academic profile with international collaborations and editorial responsibilities. His educational foundation includes a summa cum laude PhD in Finance from the University of Zurich (2009–2013), complemented by pedagogical training from the Stockholm School of Economics (2017) and CEIBS (2015). Earlier degrees comprise a Master of Arts in Business Administration (summa cum laude, 2007–2009) and Bachelor of Arts in Banking and Finance (2004–2007), both from the University of Zurich, with a visiting period at the University of Toronto’s Rotman School (2012–2013). Eugster’s research spans critical domains in accounting: Auditing : Investigating audit quality determinants, materiality judgments during crises, and digital transformation’s impact on assurance processes Financial Accounting : Analyzing valuation techniques, supply chain disclosures, and cross-cultural earnings reporting practices Contemporary Issues : Pioneering studies on climate-related disclosures, passive investor influences, and green bond verification mechanisms His scholarly output demonstrates increasing engagement with ESG factors and regulatory challenges in global markets. Analysis of his 15 most recent publications reveals a methodological emphasis on archival data spanning US, UK, Chinese, and Swiss contexts. Key trajectories include the growing intersection of digitalization with auditing standards, heightened scrutiny of climate disclosures, and the evolving role of institutional investors in financial oversight. His work consistently addresses regulatory gaps while maintaining technical rigor in accounting measurement. Eugster contributes to academic governance as a member of the European Accounting Review editorial board, reflecting peer recognition of his expertise. This service represents his primary documented scholarly contribution beyond publications. As an educator, he supervises doctoral research through courses like ‘Topics in Accounting Research’ and ‘Empirical Archival Methods’, while teaching bachelor/master courses in auditing, financial statement analysis, and valuation. His executive education involvement includes the CAS Internal Auditing program. Project leadership in ‘Weiterentwicklung IKS/RCM @ HSG’ demonstrates institutional engagement with risk control systems, though specific grant funding details remain undisclosed. While no dedicated laboratories are mentioned, his ‘Advanced Auditing & Audit Data Analytics’ course indicates integration of computational methods into assurance practices, suggesting emerging work in audit technology applications.
Massimo Scaglioni is a Full Professor of Media History at the Catholic University of the Sacred Heart in Milan, affiliated with the Faculty of Foreign Languages and Department of Communication and Performing Arts. He concurrently serves as a Lecturer in Transmedia Narratives and Television Communication at Università della Svizzera italiana (USI) in Lugano. Scaglioni directs research at Ce.R.T.A. (Research Centre for Television and Audiovisual Media) and leads the "Fare Tv" Master program at ALMED, while contributing to editorial boards of "View," "Comunicazioni Sociali," "Bianco e Nero," and "Series" journals. His research centers on institutional, economic, and social media history with emphasis on Italian radio and television within international contexts. He pioneers historical methodology application to audiovisual sources, analyzes technological-cultural convergence phenomena, and investigates transmedia narratives. His television text analysis specializes in American and European serial forms, while audience studies explore measurable viewership patterns, fandom dynamics, and evolving spectatorship practices in digital environments. Scaglioni's conference presentations from 2004-2011 reveal consistent engagement with Italian media history, public service broadcasting evolution, and audience behavior transformations. His work demonstrates how media institutions negotiate technological convergence, with recurring themes of national identity construction through broadcasting, transmedia storytelling frameworks, and the tension between traditional broadcaster control and participatory audience practices in digital convergence. As Didactic Director of ALMED's "Fare Tv" Master program, Scaglioni shapes graduate curricula in television analysis and management. His 2012 visiting professorship at Carleton University was funded by the Centre for European Studies - European Union Centre for Excellence grant, supporting transatlantic academic exchange in European media studies. Scaglioni's research leadership manifests through Ce.R.T.A. at Università Cattolica, which investigates television's historical and contemporary evolution, and the "Fare Tv" Master program that trains media professionals in television production, management, and communication strategies within Italy's dynamic broadcasting landscape.
