John Redmond is Professor of English Literature at the University of Liverpool's School of the Arts, specializing in contemporary poetry and creative writing. He holds a D.Phil and is an established poet with three collections published by Carcanet Press. His critical work examines privacy in poetic interpretation and Irish literary traditions. Research intersects creative practice with critical analysis, exploring poetry's relationship with folk drama, online culture, and food (gastro-criticism). Authored the textbook 'How to Write a Poem' and edited James Liddy's Selected Poems. Current projects include a novel and new poetry collection. Regularly participates in literary events including readings at the Anthony Burgess Foundation and Christ Church, Oxford. Chairs the School Extenuating Circumstances Committee and contributes to the Centre for New and International Writing.
Zhi Da is the Howard J. and Geraldine F. Korth Chair in Finance and Professor of Finance at the University of Notre Dame , Mendoza College of Business, Department of Finance. He completed his Ph.D. in Finance at Northwestern University’s Kellogg School of Management (2006), preceded by an M.Sc. in Financial Engineering from the National University of Singapore (2001) and a B.B.A. with First-Class Honors (1999) from the same institution. Holding editorial roles at Journal of Finance , Management Science , Review of Financial Studies and several other top journals, he is a leading voice in empirical finance research. Education Ph.D. in Finance, 2006 – Kellogg School of Management, Northwestern University M.Sc. in Financial Engineering, 2001 – National University of Singapore B.B.A. (1st Class Honors), 1999 – National University of Singapore Research Interests Zhi Da’s scholarship sits at the intersection of asset pricing , behavioral finance , and market microstructure . He investigates how investor attention, institutional trading, liquidity frictions, and information flows jointly determine the cross-section of expected returns. His work delves into retail margin trading, the role of pension-fund flows in exchange-rate dynamics, the informational content of SEC filings, and the efficiency of short-selling mechanisms. By combining large-scale data analytics, textual analysis, and structural modeling, he uncovers novel predictors of returns ranging from presidential approval ratings to real-time attention measures. Recent projects explore fractional trading ’s impact on price efficiency, hedging demand as a driver of intraday momentum, and the hidden effort problem in delegated portfolio management. These themes collectively advance our understanding of limits to arbitrage and the formation of extrapolative beliefs. Publication Landscape Spanning 2025 back to 2009, his 15 most recent articles in Journal of Finance , Review of Financial Studies , Management Science , Journal of Financial Economics , and Journal of Financial and Quantitative Analysis converge on three broad motifs: (1) micro-level trading frictions—liquidity costs, margin requirements, and short-selling constraints; (2) macro-finance linkages—exchange rates, fiscal policy, and global capital flows; and (3) information economics—attention allocation, media analytics, and regulatory disclosures. The collective evidence demonstrates that seemingly small trading or informational frictions aggregate into large, persistent cross-sectional return predictability. Honors and Awards 2017 William F. Sharpe Award for Best Paper, Journal of Financial and Quantitative Analysis Lead-article distinctions in Journal of Finance , Review of Financial Studies , and Management Science Featured coverage in SmartMoney and CNBC Teaching & Mentorship At Notre Dame’s Mendoza College, Professor Da teaches Investments (undergraduate and MBA) and Fixed Income Securities , integrating cutting-edge research insights into the curriculum. While specific advisees are not listed, his extensive co-author network (22+ recurring collaborators) attests to a vibrant mentoring environment. Laboratory & Data Resources He publicly distributes the NAT (Net Arbitrage Trading) dataset, a stock-quarter panel of arbitrage positions used in Chen, Da & Huang (2019). This resource has become a standard tool for researchers studying arbitrage capital movements.
Teruko Mitamura is a prominent researcher at Carnegie Mellon University with over three decades of contributions to natural language processing, computational linguistics, and artificial intelligence. Her work spans from foundational research in event representation to advanced applications in multimodal systems and question answering. Her research interests focus on event detection and understanding, question answering systems, information retrieval, and multimodal processing. She has made significant contributions to event coreference resolution, timeline construction, and cross-document event analysis, developing methodologies that have become standard in the field. Her work often bridges theoretical advances with practical applications, particularly in complex information environments requiring deep semantic understanding. Natural Language Processing : Specializing in event extraction, coreference resolution, and narrative understanding with over 179 publications Question Answering Systems : Developing advanced techniques for complex question answering, particularly through NTCIR QA Lab and PoliInfo tasks Multimodal Processing : Integrating textual, visual, and temporal information for richer understanding in systems like ProMQA Evaluation Methodologies : Creating robust frameworks for assessing NLP systems through TAC KBP Event Tracks Her recent publication trends show a strong focus on leveraging large language models for event understanding, multimodal question answering, and timeline construction. She has expanded her research into specialized domains including patent analysis and novelty examination, demonstrating the breadth of her research impact across academic and practical applications. Active participant in major NLP conferences including ACL, EMNLP, NAACL, and AAAI with consistent publications Long-standing collaborator with researchers at CMU's Language Technologies Institute including Eduard H. Hovy and Eric Nyberg Contributor to shared tasks that have shaped research directions in event processing and question answering Organizer of multiple NTCIR QA Lab tasks focused on political information question answering Dr. Mitamura has mentored numerous researchers who have gone on to make their own contributions to the field, as evidenced by her extensive co-authorship network and the progression of her former students and collaborators into faculty and research positions. Her work continues to evolve with the field while maintaining her focus on deep semantic understanding of events and narratives.
Nelly V. Litvak is a Full Professor in Algorithms for Complex Networks at Eindhoven University of Technology (Mathematics and Computer Science). She works on mathematical methods and algorithms for complex networks (social networks, WWW) using random graph models. She joined TU/e as a part-time professor in 2017 after being an Associate Professor at the University of Twente since 2012. Affiliations: 4TU Applied Mathematics Institute, Data Science Center Eindhoven, CTIT Industry Partners: ABN-AMRO Bank, Philips Lighting, Thales Editorial Role: Managing Editor of Internet Mathematics Her research focuses on extracting value from network data across three areas: (1) Information extraction and prediction, (2) Mathematical analysis of network characteristics, and (3) Efficient algorithms for incomplete network data. Key topics include PageRank, HITS algorithm, random graphs, homophilic networks, and network epidemiology. Recent work (2022-2025) spans network growth mechanisms, fairness in ranking algorithms, educational pedagogy, and pandemic forecasting dashboards. She contributes to SDGs through data-driven approaches to societal challenges. Teaching activities include course development at TU/e and earlier institutions, with innovative methods for computer engineering students' statistical understanding.
Jason Schweinsberg is a Professor in the Department of Mathematics at the University of California, San Diego (UCSD), where he has been a faculty member since Fall 2004. His academic journey began with a Ph.D. in Statistics from the University of California, Berkeley in 2001, followed by a three-year NSF Postdoctoral Fellowship at Cornell University. His research focuses on probability theory with applications to evolutionary biology and population genetics. Schweinsberg's work centers on stochastic processes involving coalescence, branching Brownian motion, and their connections to biological phenomena. He has made significant contributions to understanding population models undergoing selection, cancer evolution, and spatial mutation processes. Recent publications reveal a strong emphasis on coalescent theory (particularly Λ-coalescents and nested coalescents), branching processes with absorption, and spatial evolutionary models. His work often bridges rigorous mathematical analysis with biological applications, especially in population genetics and cancer modeling. The 15 most recent articles demonstrate consistent focus on asymptotic analysis of stochastic processes, genealogical structures, and mutation dynamics in evolving populations. Scientific Awards: Fellow of the Institute of Mathematical Statistics NSF Postdoctoral Research Fellowship While specific student names aren't listed in the source material, Schweinsberg has delivered numerous lecture series at international institutions including the Indian Institute of Science (Bangalore), Centre de Recherches Mathématiques (Montreal), and the Isaac Newton Institute (Cambridge), indicating active mentorship and academic leadership. His collaborations span multiple institutions, with frequent co-authorship with researchers like Julien Berestycki, Nathanaël Berestycki, and Rick Durrett. Though no formal lab structure is mentioned, Schweinsberg participates in interdisciplinary research communities through workshops at institutions like BIRS (Banff International Research Station), where he presented on mutation patterns in spatially structured populations in May 2025. His work connects probability theory with biological applications through sustained collaborations across mathematics, statistics, and computational biology fields.
Christopher Kopper is an Associate Professor in the Department of History at Bielefeld University's Faculty of History, Philosophy and Theology. His academic career spans over three decades with significant contributions to economic history, banking history, and transport history. Appointed as an extraordinary professor at Bielefeld University in April 2012, he has held various research and teaching positions including visiting professorships at Charles University in Prague, University of Siegen, University of Münster, and West Virginia University. His research interests focus on German economic history, particularly banking systems during the Nazi era, transport policy, corporate history, and European economic integration. Kopper has led and participated in numerous research projects including 'From the Reichsbank to the Bundesbank' and served as Project Manager for Subproject 6 on infrastructure buildings during National Socialism. He has been a member of the Historikerkommission (History Commission) for the German Federal Ministry of Economics since 2012 and the Selection Committee of the Friedrich Ebert Foundation since 2013. Kopper's publication record demonstrates consistent scholarly output with recent works focusing on corporate responsibility under military dictatorships (particularly Volkswagen in Brazil), monetary policy consequences of German occupation in Greece, and the internationalization of German banks. His research shows a trend toward examining corporate ethics in authoritarian regimes and the long-term economic consequences of historical events. As a member of multiple academic committees and research networks, Kopper maintains active engagement with the historical research community. His work bridges economic, political, and social history with particular attention to institutional development and policy impacts. Professor Kopper supervises research projects and collaborates with international scholars, contributing significantly to contemporary historical scholarship through his expertise in German economic and business history. His current research continues to explore the intersections of corporate behavior, political regimes, and economic policy across different historical periods.
Marija Rosic is a Lecturer in the Department of Slavic Languages and Literatures at the University of Michigan's International Institute. She holds a Diploma in Serbo-Croatian language and Yugoslav literature from the University of Belgrade (1982). Her expertise focuses on Bosnian, Croatian, and Serbian (B/C/S) languages, emphasizing language instruction and cultural context in教学. She has presented at professional conferences such as the 2018 AATSEEL Conference, discussing teaching strategies for less commonly taught Slavic languages and integrating Balkan cultural studies into language education. Her affiliations include the Center for Russian, East European, & Eurasian Studies (CREES), the Weiser Center for Europe and Eurasia, and the Slavic Languages & Literatures program. Rosic teaches first- and second-year B/C/S courses and Independent Reading, emphasizing linguistic diversity across the three variants. She collaborates with colleagues like Dr. Tatjana Aleksic on Balkan cultural studies and post-Yugoslav literary analysis. No specific grants or awards are listed, though her contributions to curriculum development and student engagement are highlighted through departmental news updates. She actively participates in student celebrations and academic events, fostering community within the B/C/S program at U-M.
Omar Rifki is an Associate Professor (Maître de Conférences) specializing in combinatorial optimization and artificial intelligence applications. His research bridges theoretical computer science with practical logistics challenges, focusing on routing problems, process mining, and machine learning integration for complex decision systems. His core research interests include phase transitions in NP-hard problems, vehicle routing optimization under time constraints, and healthcare process modeling. Rifki's work demonstrates a consistent pattern of integrating reinforcement learning with traditional optimization techniques to solve large-scale real-world problems in transportation and logistics, with particular emphasis on spatio-temporal data effects and collaborative systems. Analysis of his 15 publications (2019-2025) reveals three dominant research thrusts: (1) Fundamental studies of combinatorial problem hardness using phase transition frameworks, (2) Practical applications of deep reinforcement learning in vehicle routing and taxi assignment, and (3) Healthcare process optimization through advanced process mining techniques. His work consistently addresses scalability challenges in real-world implementations while maintaining theoretical rigor. No scientific awards were documented in the provided materials. His collaborative work with researchers like Christine Solnon and Thierry Garaix indicates active participation in European operations research communities, though specific grant details remain unreported. Rifki's research shows increasing integration of graph theory and machine learning in transportation applications, particularly evident in his Lyon City case studies on autonomous ride-sharing systems.
Nina Bandelj serves as a Professor in the Department of Sociology at the University of California, Irvine, where she is an active affiliate of the Center for Organizational Research (COR). Her research bridges economic sociology and family studies, examining how money, debt, and market logics permeate intimate social relations. She frequently participates in COR initiatives like the Academic Speed-Dating events held in Social Sciences Plaza B, fostering interdisciplinary collaboration among scholars. Bandelj's research centers on three interconnected domains: (1) the economization of family life , analyzing how parenting transforms into human capital investment through debt-financed childcare and education; (2) cross-national inequality , investigating ethnic marginalization in Eastern Europe and gender pay gaps within workplaces; and (3) money's social meaning , exploring emotional economies of modern parenting and the valuation of 'priceless' social domains. Her work consistently challenges the 'hostile worlds' thesis by demonstrating how economic and intimate spheres co-constitute each other. Recent publications reveal intensifying focus on debt-driven middle-class parenting (e.g., mortgage debt tied to childrearing) and commodified childhood (e.g., pricing early education), while maintaining strong comparative analysis of postsocialist economies. This trajectory reflects broader shifts in economic sociology toward studying financialization's penetration into familial spheres. Bandelj actively cultivates scholarly communities through COR events and writing initiatives like 'U See I Write,' emphasizing collaborative knowledge production. Her work demonstrates how micro-level family economies scaffold macro-level policy failures, particularly regarding America's family-hostile welfare state.
Asst. Prof. Hilal Öztürk Baydere serves in the Department of Western Languages and Literatures at Karadeniz Technical University's Faculty of Arts and Humanities since 2021, advancing to Assistant Professor in 2024 after beginning her academic career at the university's School of Foreign Languages in 2013. Her institutional trajectory reflects deep integration within Turkey's translation studies community. Her academic foundation includes: Doctorate in Translation Studies (2016-2022) from Istanbul University's Institute of Social Sciences Postgraduate degree in English Translation and Interpretation (2011-2015) from Hacettepe University Undergraduate degree in English Language and Literature (2007-2011) from Hacettepe University Her research centers on Translation Studies with acute focus on machine translation's disruption of literary translation practices. She investigates translator competence evolution in AI-driven environments, creativity preservation in machine-assisted workflows, and historical/cultural dimensions of translation. Her work bridges theoretical linguistics with practical technological applications, particularly examining lexical diversity and stylistic integrity in neural machine translation outputs. Publication analysis reveals three dominant research vectors: (1) Machine translation evaluation frameworks for literary texts (25% of output), (2) Historical/cultural memory representation through translation (33%), and (3) Translator identity and competence in digital ecosystems (42%). Recent work increasingly incorporates large language models while maintaining strong philological grounding in English-Turkish translation contexts. She actively supervises student research on AI translation applications including subtitle translation effectiveness and e-commerce review sentiment analysis. Her TUBITAK-funded doctoral scholarship (2017-2022) and current membership in the European 'Language in the Human-Machine Era' research consortium demonstrate significant grant acquisition and international collaboration. Conference participation spans 8+ annual international symposia since 2017, primarily KTUDELL and NALANS events. Her ongoing projects with the European Cooperation in Science and Technology group indicate future research directions exploring human-AI symbiosis in translation pedagogy and professional practice, particularly regarding creativity metrics and cultural adaptation in neural machine translation systems.
Hermann M. Fritz is a full Professor at the Georgia Institute of Technology within the College of Engineering's School of Civil and Environmental Engineering. With expertise spanning tsunamis, coastal hazards, hurricane storm surges, landslides, and submarine volcanic eruptions, his research focuses on the fluid dynamics aspects of these natural hazards and their mitigation strategies. Dr. Fritz earned his Doctorate degree (Dr. sc. ETH Zurich) in 2002 from the Swiss Federal Institute of Technology in Zurich. His extensive field experience includes leading or participating in more than a dozen post-disaster reconnaissance campaigns across multiple continents, documenting tsunami events from the 2004 Indian Ocean tsunami through the 2017 Greenland event, and hurricane surveys from Hurricane Katrina (2005) to Hurricane Nate (2017). His research integrates physical modeling with field observations, with recent work focusing on tsunamis generated by submarine volcanic eruptions, as evidenced by his development of a unique volcanic tsunami generator for large-scale wave basin experiments. His publication record shows consistent high-impact research in natural hazard science, with a particular emphasis on understanding wave generation mechanisms, coastal inundation patterns, and sediment transport processes during extreme events. Among his notable recognitions is the Plinius Medal from the European Geosciences Union (2014), highlighting his significant contributions to natural hazard research. His work bridges fundamental fluid dynamics with practical applications for coastal protection and disaster risk reduction. Plinius Medal, EGU (European Geosciences Union) - 2014 Dr. Fritz has mentored numerous students through his research projects, though specific names aren't provided in the available information. His collaborative approach is evident through his extensive co-authorship network spanning multiple institutions worldwide. Current research directions include advanced physical modeling of tsunami generation mechanisms, particularly those related to volcanic activity and landslides, as well as improving coastal resilience against extreme events. His laboratory work at Georgia Tech involves sophisticated experimental setups including large three-dimensional wave basins and specialized generators for simulating complex natural phenomena under controlled conditions. This experimental approach complements his extensive field survey experience, creating a powerful research methodology that connects theoretical understanding with real-world observations.
Jin Siyan is a Professor of Chinese Literature in the Department of Oriental Studies at the University of Artois, France, where she has been teaching since 2006. She serves as co-director of the research axis 'Études transculturelles: Occident et Orient: l'imaginaire de l'autre, Identité, réception et critique' and is a full member of the 'Textes et cultures' Research Center. Her academic career spans multiple prestigious institutions across France and China. Her educational background includes: Doctorat ès Lettres Modernes from Université de Paris-Sorbonne (Paris IV) in 1992 Habilitation to Direct Research in Literature and Languages from Jean Moulin University Lyon 3 in 2005 Maîtrise de langue et littérature françaises from Université de Pékin in 1984 Licence ès lettres from Université de Pékin (1978-1982) Jin Siyan's research focuses on transcultural studies between China and the West, with particular emphasis on the three historical encounters between Chinese and Western civilizations. Her work explores the modern history of Chinese literary theory, examining subjectivity in contemporary Chinese writing, Chinese feminine writing, and the complex relationship between language consciousness and identity. She has conducted groundbreaking research on the history of literary reception between China and France, and has pioneered studies on cultural transfers, particularly the translation of Buddhist sacred texts in 5th century China and its impact on the formation of classical Chinese language and poetics. Her work on the Wenxin Diaolong (The Literary Mind and the Carving of Dragons) by Liu Xie represents a major contribution to understanding classical Chinese literary theory. Her extensive publication record includes 14 monographs (7 in Chinese, 7 in French), 21 edited volumes, 10 literary works, 19 translations, and over 90 scholarly articles. Her recent research focuses on transcultural methodology, Buddhist text translation, and the relationship between Chinese poetics and Western literary theory. She has supervised 14 doctoral theses and 4 cotutelle theses covering topics in literary criticism, reception theory, and Chinese women's literature. As an active academic, Jin Siyan has participated in 168 scientific events (including 101 international conferences, 25 study days, and 42 doctoral seminars), organizing 30 of these events herself. She co-directs the journal 'Dialogue Transculturel' and the 'Espace transculturel' book series, fostering scholarly exchange between Chinese and Western academic communities.
Dennis Esch serves as Lecturer (Assistant Professor) in Marketing and Behavioural Science at Cranfield School of Management, Cranfield University, where he acts as the Strategic Marketing and Sales Group's liaison for research matters. Previously, he directed the Cranfield Customer Management Forum, one of the School's premier research practice clubs. Dr. Esch holds award-winning academic qualifications in marketing, psychology and behavioural science from Lancaster University Management School and Cranfield School of Management, establishing a strong interdisciplinary foundation for his research. His research program centers on three interconnected domains: the psychological mechanisms of brand influence in consumer decision-making, the transformative impact of emerging technologies on consumer perceptions and preferences, and the complex relationship between social consumption experiences and human happiness. Methodologically, he integrates behavioral science principles with marketing theory through quantitative approaches including experiments, field studies, and big data analysis to address questions with both theoretical significance and practical managerial relevance. Dr. Esch's publication record reveals an evolving research trajectory from foundational consumer behavior studies (2016-2019) examining product assortment effects, sports consumption impacts, and social identity dynamics, toward contemporary methodological innovations in mobile research platforms (2022-2025). His recent work demonstrates particular expertise in evaluating mobile-first platforms for crowdsourcing behavioral, advertising, and personality research, addressing critical questions about digital research validity and ecological relevance. While specific major scientific awards beyond his noted 'award-winning degrees' aren't detailed in available information, his research has been published in reputable outlets including Behavior Research Methods and Academy of Marketing Science proceedings, indicating scholarly recognition. Dr. Esch brings extensive international teaching experience across multiple contexts, having instructed postgraduate students and executives in brand management, marketing strategy, consumer behavior, and research methods in the UK, Germany, and Switzerland. His pre-academic industry background includes significant roles at Audi, Henkel, Vaillant Group, and Swiss Post, providing practical grounding for his academic work and enhancing the real-world applicability of his research findings. His research methodology reflects a commitment to bridging the gap between laboratory rigor and field relevance, particularly through his investigations of mobile research platforms that can capture authentic consumer experiences while maintaining scientific validity. This approach addresses contemporary challenges in behavioral research methodology while generating actionable insights for marketing practitioners.
Dr Peter Braunsteins serves as a Lecturer in Statistics within the School of Mathematics and Statistics at the University of New South Wales (UNSW Sydney), operating under the Faculty of Science. His academic appointment focuses on advancing theoretical and applied probability through rigorous mathematical research. He completed his PhD at the University of Melbourne in 2018, followed by postdoctoral positions at the University of Amsterdam and King Abdullah University of Science and Technology (KAUST) before joining UNSW. His scholarly background bridges European and Middle Eastern research institutions with Australian academia. Braunsteins' research centers on stochastic processes , with pioneering contributions in three interconnected domains: branching processes (modeling population dynamics and extinction events), random graphs (analyzing network evolution and structural properties), and spatial extremes (studying rare events in geographical contexts). His work combines deep theoretical insights with applications in epidemiology, insurance risk modeling, and network science, often employing large deviation principles and parameter estimation techniques for complex systems. Analysis of his 15 most recent publications reveals a sustained focus on branching process theory, particularly population-size-dependent models and extinction probabilities, while simultaneously developing novel frameworks for dynamic random graphs. His research demonstrates increasing interdisciplinary reach, connecting probability theory with actuarial science through adaptations of the Cramér-Lundberg model and with network science through graphon analysis. No scientific awards or major honors are documented in the available materials. His collaborative network includes prominent researchers such as Sophie Hautphenne, Frank den Hollander, and Michel Mandjes across multiple continents. Professional activities include manuscript review for leading probability journals and participation in academic seminars at UNSW, though specific advising roles or grant funding details remain undisclosed in the source material. His office is located in Room 2056 of the Anita B. Lawrence Centre at UNSW Sydney.
Lauren Tompkins is an Associate Professor of Physics in the School of Humanities and Sciences at Stanford University, holding appointments in the Physics Department. Her research focuses on fundamental particle interactions through participation in major international experiments including the ATLAS experiment at CERN's Large Hadron Collider, the Light Dark Matter Experiment (LDMX) at SLAC, and the Heavy Photon Search (HPS) at Jefferson Laboratory. Her research interests span particle physics , dark matter detection , and advanced trigger systems . She investigates the Higgs boson's properties, searches for evidence of dark sectors through heavy flavor fermions, and develops FPGA-based real-time processing systems for particle detectors. Her group specializes in custom electronics for high-rate collision environments, particularly focusing on identifying rare events like Higgs boson production and potential dark matter signatures. Professor Tompkins' recent publications demonstrate strong focus on dark matter searches, Higgs boson physics, and advanced computing techniques. Her work bridges experimental particle physics with cutting-edge computational methods, particularly in deep learning applications for vertex reconstruction and FPGA-based trigger systems for the High Luminosity LHC upgrade. CAREER Award, National Science Foundation (2016-2021) Terman Fellow, Stanford University (2014-2017) US ATLAS Education and Public Outreach Award (awarded to group member Rocky Bala Garg) She actively mentors doctoral students and postdoctoral researchers, currently advising Elizabeth Berzin, Noe Gonzalez, Sadaf Kadir, and Rory O'Dwyer as Doctoral Dissertation Advisor. Her group participates in multiple collaborative projects including the NSF Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP) and contributes to the development of the ACTS open source software project. The Tompkins Group maintains active research programs across three major experimental facilities in Switzerland, California, and Virginia.
