Prof. Dr. Urs Hartl is a faculty member in the Department of Mathematics and Computer Science at the University of Münster, affiliated with the Faculty of Mathematics and Computer Science. He is an Investigator in Mathematics Münster and a member of the Collaborative Research Centre (CRC) 1442 'Geometry: Deformations and Rigidity.' His research focuses on arithmetic geometry, representation theory, algebraic number theory, and arithmetic of function fields. He holds a prominent position in the field, contributing to areas such as Shimura varieties, p-adic Hodge theory, and the Langlands program. Affiliations: Member of CRC 1442 Geometry Investigator in Mathematics Münster Research Interests: Arithmetic algebraic geometry Algebraic number theory Arithmetic of function fields Structure theory of Shimura varieties p-adic Hodge theory p-adic Langlands programme Model theory Recent Publications: Hartl's recent work includes studies on moduli stacks of global G-shtukas, periods of Drinfeld modules, and p-adic Galois representations. His research emphasizes foundational contributions to arithmetic geometry and number theory, often involving collaborations with leading mathematicians such as Rajneesh Kumar Singh and Eva Viehmann. Grants & Advising: Hartl’s involvement in CRC 1442 reflects his leadership in geometric research. While specific advising details are not provided, his extensive publications suggest active mentorship in advanced mathematical research. Labs/Teams: Collaborates within the Mathematics Münster research group and the CRC 1442 team, focusing on geometric and arithmetic structures.
Jay David Bolter holds the Wesley Chair of New Media and serves as Professor and Director of Computational Media at the Georgia Institute of Technology, where he is affiliated with the School of Literature, Media, and Communication within the Ivan Allen College of Liberal Arts. A foundational figure in digital media studies, he is renowned for his influential theoretical works and practical contributions to new media forms. His research spans Augmented Reality , Virtual Reality , Digital Culture , and the History of Media , with particular emphasis on remediation theory (developed with Richard Grusin) and the evolution of digital writing. As an active member of the Augmented Environments Lab, Bolter creates narrative-driven AR applications for cultural heritage sites and educational contexts, blending theoretical rigor with experimental design. His work consistently examines how new media technologies reshape human perception and cultural practices. Recent publications reveal a concentrated exploration of reality media (AR/VR) as narrative spaces, with articles addressing biofeedback integration in VR fitness, agency-driven interactive storytelling, and theoretical frameworks for understanding immersive experiences. His scholarship bridges historical media analysis with cutting-edge technical implementation, demonstrating how remediation processes continue to evolve in mixed reality environments. This trajectory reflects his lifelong investigation into the interplay between technological capabilities and human expression. Bolter maintains significant collaborative partnerships, including co-authoring seminal texts like Remediation and developing the Storyspace hypertext system with Michael Joyce. His leadership in the Augmented Environments Lab drives interdisciplinary projects that merge humanities perspectives with technological innovation, particularly in creating culturally resonant AR experiences. Teaching responsibilities include advanced courses in mixed reality design, computational media, and digital media theory, shaping the next generation of media scholars and practitioners.
Ambuj Varshney is an Assistant Professor at the National University of Singapore (NUS) School of Computing , leading the WEISER research group . His work bridges electronics, wireless communication, computer science, and AI with a focus on creating ultra-low-power embedded systems for sustainable IoT deployments. University of California, Berkeley: Postdoctoral Scholar (2020-2022) Uppsala University: PhD in Sustainable Networked Systems NXP Semiconductors: Software Engineer (prior to PhD) Bachelors in Information & Communication Technology Research interests center on overcoming wireless systems' energy asymmetry through tunnel diode oscillators , LiFi-RF hybrid networks , and battery-free communication architectures . His group develops STICORS —sticker-like computers for industrial and medical monitoring. Recent publications demonstrate AudioCast 's FM-band utilization for 130m transmission, TunnelSense 's vital monitoring, and PixelGen 's diffusion model cameras. These works combine IoT sustainability, spectrum efficiency, and hardware innovation . 2024: Google Research Scholar Award 2023: MobiSys Best Demonstration 2021: Berkeley FORM+FUND Fellowship 2019: ABB's $300K Research Award As an educator, he teaches CS4222 Wireless Networking and CS5272 Embedded Software Design . Past students include Wenqing Yan (NUS/UCB PhD), Qiao Yukai , and Kunjun Li . His team collaborates with Prabal Dutta (UCB), Christian Rohner (Uppsala), and Prateek Saxena (NUS).
Dr. Simon A. Morrison is a Senior Lecturer in the Division of Communication, Screen & Performance within the Faculty of Arts, Humanities and Social Sciences at the University of Chester. He serves as Programme Leader for the Music Journalism degree, which he helped design, build and deliver from its first cohort in 2014. With 25 years of experience as a writer, broadcaster, and academic, Morrison brings extensive industry knowledge to his teaching and research, having worked as a music journalist reporting from locations worldwide including Beijing, Brazil, Moscow, and Marrakech. Dr. Morrison holds a PhD from the University of Leeds (completed 2018), an MA from the University of Manchester (1995-1997), and a BA Hons from the University of Manchester (1989-1992). Prior to his position at Chester, he worked as an Associate Lecturer at Manchester Metropolitan University (2012-2014) and as a Visiting Lecturer at Leeds University (2011-2013). His academic journey follows a substantial career in media where he presented TV for Rapture TV, hosted radio shows in Ibiza, produced and presented for Kiss Radio, and appeared on BBC Breakfast and BBC 5 Live. Dr. Morrison's research centers on the intersection of words and music , with particular focus on Popular Music , Musico-Literary Intermediality , and Electronic Dance Music Culture . His work explores how music subcultures, particularly rave and dance music scenes, are represented in literature and journalism. He examines the connections between different countercultural movements, notably drawing parallels between the Beat Generation writers and contemporary 'Chemical Generation' authors who write about club culture. His research also investigates the relationship between music journalism and subcultural movements across different historical periods. His recent publications reveal a clear trajectory connecting historical dance music developments across continents and eras. Morrison's work traces the evolution of electronic dance music from its American roots in Chicago and Detroit through its transatlantic journey to Europe and back again, examining how cultural exchange shaped musical innovation. His analyses of Pink Floyd demonstrate how rock bands interact with media landscapes, while his investigations of music journalism document the changing nature of music criticism in digital eras. The recurring theme across his scholarship is the examination of how subcultural experiences are translated into written form, whether through journalism, fiction, or academic analysis. Dr. Morrison actively supervises undergraduate dissertation projects and Negotiated Study production projects across all three years of undergraduate study. He has successfully supervised an MRes project to completion and examined PhDs (including one internal and two external, one being an Australian PhD by Artefact & Exegesis). He has served as an External Examiner for Music Journalism programs at Southampton Solent University (2016-2019) and BIMM London, Birmingham and Manchester (2016-2020). His teaching spans modules including Introduction to Journalism, Live Journalism, Dancing About Architecture: Popular Music Media, Histories and Technologies, The Cultural Politics of Music Journalism, The Politics of Social Media, Magazine Publishing and Music PR and Promotional Writing.
Antonia Holzapfel is a doctoral researcher at the Institute for Data Science in Mechanical Engineering (DSME) of RWTH Aachen University. Supervised by Prof. Sebastian Trimpe, her work focuses on safe and explainable machine learning (XAI) for robotics and time-series modeling, with applications in mechanical engineering and medical technology. Bachelor's in Mechanical Engineering (Design Engineering specialization) Master's in General Mechanical Engineering (Simulation Technology and Medical Technology specializations) Her research addresses safety in learning processes , including Bayesian optimization for quadcopters and concept extraction for model interpretability. Her Friedrich-Wilhelm Award -winning thesis (2024) explored safe online learning in time-varying environments, presented at the L4DC conference. She contributes to DFG-funded projects on data-driven process modeling in forming technology. Key scientific contributions include: Advancing safe Bayesian optimization for autonomous systems Developing explainable AI methods for time-series analysis Improving model robustness through internal representation patterns Scientific awards: Friedrich-Wilhelm Award for outstanding Master's thesis (2024) Antonia's work bridges machine learning safety with practical applications in robotics and industrial processes.
Dr. Beibei Ren is an Assistant Professor in the Department of Mechanical Engineering at Texas Tech University. She earned her Ph.D. in Electrical and Computer Engineering from the National University of Singapore (NUS) in 2010, followed by postdoctoral work at UCSD and a research fellowship at NUS. Education: Ph.D. in Electrical and Computer Engineering (NUS, 2010) Previous Positions: Postdoctoral Scholar (UCSD, 2010-2013), Research Fellow (NUS, 2009-2010) Her research focuses on dynamic systems and control with applications in renewable energy integration, microgrids, UAVs, MEMS, marine systems, and manufacturing. At Texas Tech, she directs the Dynamic Intelligent Systems, Control and Optimization (DISCO) Group , emphasizing robust control strategies for uncertain systems. The 15 most recent publications highlight her expertise in uncertainty and disturbance estimator (UDE)-based control , with applications in smart grid technologies, wind and solar energy systems, quadrotor robotics, and power electronics. Her work bridges theoretical control theory with practical implementations in renewable energy and autonomous systems. STEM Outreach: Actively promotes diversity in engineering through Texas Tech's STEM CORE programs.
Mohit Iyyer is an Associate Professor in Computer Science at the University of Maryland, College Park (UMD), affiliated with the Manning College of Information and Computer Sciences (CICS) and the CLIP lab. Previously, he held roles at UMass Amherst, AI2, and completed his PhD at the University of Maryland. His research focuses on advancing NLP and machine learning, particularly in long-context LLMs, factuality evaluation, and human-LLM collaboration. Education : PhD, Computer Science, University of Maryland, College Park (2017) MS, Computer Science, University of Maryland, College Park (2014) BS, Computer Science, Washington University (2012) Research Interests : His work emphasizes improving instruction-following in LLMs, evaluating long-form text, detecting AI-generated content, and enhancing LLM robustness. He actively explores multilingual LLMs, literary translation, and creative writing support through AI. Key Contributions : Developed influential frameworks like ELMo and QuAC, and introduced benchmarks such as BEARCUBS and BooookScore. His work on watermarking (PostMark) and adversarial attacks (OverThink) addresses security and reliability in AI systems. Awards & Recognition : NSF CAREER Award (2021) Samsung AI Researcher of the Year (2022) Best Paper Awards at NAACL 2018 and CCS 2023 Advising & Grants : Advises a dynamic research group and has received grants for projects like multilingual QA and long-context LLM evaluation. Collaborates with industry partners like AI2 and DeepMind. Labs & Teams : Leads the CLIP lab at UMD, focusing on foundational NLP research and applications in literature, dialogue systems, and computational storytelling.
Tatsunori Hashimoto is an Assistant Professor of Computer Science at Stanford University, specializing in artificial intelligence, machine learning, and natural language processing. His research focuses on developing robust and ethical language models, addressing challenges in bias mitigation, fairness, and transparency. He leads projects like the Stanford Alpaca, exploring instruction-following models and their societal impacts. Key research interests include generative models, AI ethics, and privacy-preserving techniques. His recent work examines language model behaviors, security risks, and the societal implications of AI systems. Notable contributions include frameworks for auditing language models, improving factual accuracy, and reducing disparities in speech recognition. His publications highlight advancements in long-context processing, few-shot learning, and automated benchmarking. He emphasizes practical applications of AI while addressing dual-use concerns and ensuring alignment with human values.
Dima Damen is a Professor of Computer Vision at the School of Computer Science, University of Bristol, where she leads the Machine Learning and Computer Vision Group. She also serves as a Senior Research Scientist at Google DeepMind. As an EPSRC Early Career Fellow (2020-2025) and a Fellow of ELLIS for Europe, her research focuses on advancing computer vision, particularly in egocentric (first-person) vision, video understanding, and action recognition. Her educational background and professional journey have positioned her as a leader in the field of computer vision, with a particular emphasis on understanding human activities from wearable cameras. She has received numerous awards including Best Paper at ACCV 2024 and Outstanding Paper at ICASSP 2021. Professor Damen's research interests span multiple areas of computer vision and machine learning. She specializes in egocentric vision, where she has made significant contributions to understanding human activities from first-person perspectives. Her work explores video understanding, action recognition, hand-object interactions, and the development of vision-language models that can interpret and generate instructions from visual data. She has pioneered approaches to unique video captioning, long video understanding through active memory representations, and spatial reasoning from egocentric videos. Her research often bridges the gap between theoretical computer vision and practical applications in human-centered AI. Her recent publications demonstrate a strong focus on egocentric vision, with papers like "AMEGO: Active Memory from long EGOcentric videos" (ECCV 2024) and "HOI-Ref: Hand-Object Interaction Referral in Egocentric Vision" (2024) advancing the state of the art in understanding long-form first-person videos. She has also contributed to vision-language models with works like "ShowHowTo: Generating Scene-Conditioned Step-by-Step Visual Instructions" (CVPR 2025) and "It's Just Another Day: Unique Video Captioning by Discriminitave Prompting" (ACCV 2024, Best Paper). Her research shows a consistent trajectory toward building systems that can understand human activities in natural environments with human-like capabilities. Professor Damen has received significant recognition for her work, including: EPSRC Early Career Fellow (2020-2025) ELLIS Fellow for Europe (Nov 2024) Best Paper at ACCV 2024 Outstanding Paper at ICASSP 2021 (awarded to only 3 out of 1700 papers) Outstanding Reviewer for CVPR 2020 and 2021 Program Chair for ICCV 2021 She has successfully advised numerous PhD students and postdoctoral researchers, many of whom have gone on to prestigious positions in academia and industry. Her group has secured significant research funding including the EPSRC Programme Grant Visual AI and the EPSRC UMPIRE grant. She actively collaborates with industry partners including Google DeepMind, Adobe, and Meta, ensuring her research has practical impact. Professor Damen leads the Machine Learning and Computer Vision Group at the University of Bristol, which focuses on egocentric vision, video understanding, and the development of vision-language models. The group has created influential datasets like EPIC-KITCHENS, which has become a standard benchmark in egocentric vision research. Her team regularly participates in and organizes workshops at major computer vision conferences including CVPR, ICCV, and ECCV.
Andrew Mondschein is Associate Professor of Urban and Environmental Planning at University of Virginia School of Architecture, serving as Associate Dean of Research. His work focuses on equitable transportation systems, sustainable accessibility, and impacts of emerging technologies on urban mobility. Education includes: PhD, University of California, Los Angeles MA Urban Planning, University of California, Los Angeles BA Architecture, Yale University Research examines how transportation technologies affect social equity and urban form, with emphasis on pedestrian wellbeing, autonomous vehicle adoption, parking policy, and community-centered planning. Recent publications demonstrate strong focus on psychophysiological impacts of urban walking, cross-cultural mobility studies, and spatial analysis of transportation preferences. Articles show consistent themes: urban walkability (especially health impacts), autonomous vehicle integration, parking policy analysis using novel data sources, and community-centered planning approaches. Methodologically, employs mixed methods including biometric sensing, sentiment analysis of social media, geospatial modeling, and participatory design. No specific awards mentioned. Teaching covers transportation policy, land use, environmental impacts, and research methods with emphasis on ethical planning practices.
Associate Professor Lasantha Meegahapola is a Deputy Head of Department (Teaching & Learning) at RMIT University's School of Engineering in Melbourne, Australia. He holds an IEEE Senior Membership and serves as an Associate Editor for several prestigious journals, including IEEE Transactions on Power Systems and IET Renewable Power Generation. His research focuses on Power System Stability with Renewable Integration, Microgrid Control, and Smart Grid Technologies, addressing challenges like voltage stability, inverter-based grid dynamics, and renewable energy penetration. He has supervised 16 PhD students to completion and published over 200 articles. Key contributions include identifying stability issues in microgrids and advancing grid-forming inverter control strategies. His work aligns with UN Sustainable Development Goals 7 (Clean Energy), 9 (Infrastructure), and 13 (Climate Action). He is actively involved in IEEE committees, including the PSDP Task Force on Microgrid Stability. Teaching roles include Programme Manager for the Bachelor of Electrical Engineering (HK) and Subject Coordinator for Power System Analysis and Control courses. Collaborations span industry and international research institutions, emphasizing real-world applications of his research in power systems and renewable energy integration.
Emily M. Bender is the Thomas L. and Margo G. Wyckoff Endowed Professor in the Department of Linguistics at the University of Washington. She also holds adjunct appointments in the School of Computer Science and Engineering and the Information School. Her research spans multilingual grammar engineering, computational linguistics, societal impacts of language technology, and sociolinguistic variation. She directs the Computational Linguistics Laboratory (The Treehouse) and leads the CLMS program. Bender is a Fellow of the AAAS (2022) and previously served as Howard and Frances Nostrand Endowed Professor (2019–2022). She has authored influential textbooks on NLP fundamentals and pioneered work on data statements to mitigate bias in NLP systems. Her work integrates linguistic theory with computational methods, emphasizing ethical AI and language documentation. Education: PhD in Linguistics from Stanford University (advisor: Ivan A. Sag), AB in Linguistics from UC Berkeley, with studies at Tohoku University. Past roles include NAACL Executive Board Chair (2016–2017) and current roles in the Association for Computational Linguistics leadership. Her Erdős number is 4. Research focuses on the LinGO Grammar Matrix, automatic grammar inference from interlinear glossed text (AGGREGATION project), and societal implications of NLP technologies like large language models. She co-leads the RAISE initiative and contributes to labs like the Tech Policy Lab and Value Sensitive Design Lab. Over 30 advisees have completed PhD and MS degrees under her mentorship. Teaching includes courses on syntax for NLP, societal impacts of language tech, and computational linguistics. Her 2020 ACL paper on form-meaning distinctions in NLP has been influential in ethical discussions. Current projects include The AI CON (2025) on combating tech hype.
Shinji Watanabe is an Associate Professor at Carnegie Mellon University's Language Technologies Institute and a Courtesy Professor in the Electrical and Computer Engineering department. He holds a Ph.D. (Dr. Eng.) from Waseda University, Japan, and has held research roles at NTT Communication Science Laboratories, Mitsubishi Electric Research Laboratories (MERL), and Johns Hopkins University. His research focuses on automatic speech recognition, speech enhancement, and machine learning for speech processing. Watanabe has published over 300 peer-reviewed papers and received the Best Paper Award at IEEE ASRU 2019. His work emphasizes robust speech processing in challenging environments, multilingual models, and neural audio codecs. He leads the ESPnet toolkit development for end-to-end speech processing systems and contributes to technical committees like IEEE SLTC and APSIPA SLA. Recent research trends include streaming speech systems, universal speech enhancement (URGENT challenges), and fusion of discrete speech units with self-supervised representations. He explores scalable speech foundation models through benchmarks like ML-SUPERB 2.0 and investigates cross-modal audio-visual processing in challenges like MISP 2025. Education : B.S., M.S., Ph.D. (Waseda University) Affiliations : CMU Language Technologies Institute, CMU ECE, Former roles at MERL and Johns Hopkins Key Projects : ESPnet, OpenWhisper-Style Models, URGENT Challenge Frameworks
Dr. Madhav Manjrekar is an Associate Professor in the Department of Electrical and Computer Engineering at the University of North Carolina at Charlotte. He earned his Ph.D. from the University of Wisconsin–Madison in 1999. His research focuses on power electronics applications in utility systems, renewable energy interfaces, and cybersecurity of electricity infrastructure. Key areas include power quality improvement in microgrids, high-voltage direct current (HVDC) transmission, and advanced electrical machine design for electric vehicles and wind energy systems. His work emphasizes innovative solutions for energy storage integration, grid resiliency, and fault-tolerant power systems. Recent publications highlight advancements in DSTATCOM for microgrids, solid-state circuit breakers, and doubly salient electrical machines. He has contributed to projects like the US-Caribbean Super Grid and HVDC interconnectors for offshore renewable energy. Dr. Manjrekar’s research also addresses cybersecurity vulnerabilities in power infrastructure and explores next-gen semiconductor technologies like SiC MOSFETs. His interdisciplinary approach bridges power electronics, machine design, and grid stability, with applications in both academic and industry settings.
Thomas Bäck is a Professor at the Leiden Institute of Advanced Computer Science (LIACS) , Leiden University , Netherlands, and a member of the interdisciplinary programme Society, Artificial Intelligence and Life Sciences (SAILS) . His academic career spans roles at Leiden University (1996–present) and leadership positions at the Center for Applied Systems Analysis in Dortmund (1994–2000). Education : Diplom-Informatiker (Computer Science), Technische Universität Dortmund (1990) Dr. rer. nat. (Computer Science), Technische Universität Dortmund (1994) Research Interests : Dr. Bäck specializes in evolutionary computation , machine learning , and their applications in sustainable smart industry and healthcare . Recent work focuses on integrating large language models (LLMs) and quantum computing into optimization frameworks, with projects like CIMPLO (predictive maintenance), ECOLE (experience-based optimization), and SAPPAO (airline operations optimization). Scientific Contributions : His 526+ publications cover evolutionary algorithms, quantum optimization, and LLM-driven design, with recent trends including: Quantum computing (e.g., quantum approximate optimization, quantum advantage challenges) LLM integration (e.g., hyperparameter tuning, mutation control, code evolution graphs) Healthcare and industry (e.g., predictive maintenance, anomaly detection, melt quality prediction) Algorithm benchmarking (e.g., IOHprofiler, MA-BBOB, explainable benchmarking) Scientific Awards : IEEE Fellow (2022) Royal Netherlands Academy of Arts and Sciences (KNAW) member (2021) Academia Europaea member (2022) IEEE Computational Intelligence Society Evolutionary Computation Pioneer Award (2015) Fellow, International Society of Genetic and Evolutionary Computation (2003) Best Ph.D. thesis award, German Society of Computer Science (GI) (1995) Advising and Grants : He supervises Ph.D. candidates in evolutionary computation and machine learning and has secured 7 major grants from organizations like the Dutch Research Council , European Commission , and The Research Council of Norway . His editorial roles include Editor-in-Chief of the Evolutionary Computation Journal and associate editorships in leading AI journals.
