Sarah Annunziato is an Associate Professor of Italian and Director of both the Undergraduate Program in Italian and the Italian Language Program (1000-2000 level courses) at the University of Virginia. She holds a Ph.D. from Johns Hopkins University and a B.A. from Smith College. Her research focuses on children’s literature, media, and trauma representation, with a particular emphasis on Italian and U.S. texts. She also investigates language pedagogy, including game-based learning and the role of streaming media in language acquisition. Her teaching spans graduate courses like Dante’s Inferno on Film and undergraduate courses such as Elementary Italian and Small Screen Italy . She has advised MA theses on topics ranging from Italian literature to comparative cinema. Annunziato has received multiple grants, including funding for a tutoring clinic and curriculum development for healthcare-focused Italian courses. Her publications include Clic! L’italiano col telecomando (2024) and articles on topics like colonialism in Emilio Salgari’s works and Dante’s influence on American TV. She actively serves as an editor for La Vendemmia and contributes to initiatives like the Moons and Bonfires archive of Italian-American history.
Wesley Willett is an Associate Professor in the Department of Computer Science at the University of Calgary, holding the NSERC CRC II Chair in Visual Analytics. His primary research focuses on information visualization, human-computer interaction, and new media applications. He leads the Data Experience Lab and Interactions Lab, exploring innovative methods for data representation and interaction in augmented/virtual reality environments. Education includes a B.S. in Computer Science from the University of Colorado (2006) and a Ph.D. in Computer Science from UC Berkeley (2012). His work bridges technical innovation with user-centered design principles, emphasizing ethical considerations in data visualization and inclusive representation. Key research contributions include: spatial visualization techniques for large environments, gesture-based interfaces for AR/VR, and physical data representations through projects like Cetonia (swarm robotics visualization) and Data Embroidery. His work has been recognized with Best Paper awards at CHI 2015 and Pervasive 2010. Current research emphasizes immersive analytics, wearable visualization systems, and demographically diverse anthropographics. He collaborates with urban designers, neurologists, and environmental scientists to apply visualization in diverse domains like epilepsy surgery planning and air quality monitoring.
Jennifer Gibbs is a Professor and Graduate Director in the Department of Communication at the University of California, Santa Barbara. Her research focuses on collaboration in global teams, distributed work arrangements, and the impact of technologies like AI and digital media on organizational practices. She holds affiliated appointments in TMP and CITS. Education: Ph.D. (2002) in Organizational Communication from the University of Southern California; B.A. (1992) in Philosophy from Pomona College. Research interests include distributed work dynamics, global team management, remote work challenges, and technology's role in organizational transformation. Her work combines qualitative and quantitative methods, emphasizing real-world field studies to explore communication processes and technological impact. Recent studies address boundary management in remote work, well-being in virtual teams, and AI's role in legal and organizational contexts. Her articles highlight trends in global work dynamics, technological affordances, and equity perceptions among remote workers. Gibbs has served as Editor of Communication Research and on editorial boards of top-tier journals. She teaches Organizational Communication, Communication Technology, and Qualitative Research at both undergraduate and graduate levels. Her contributions bridge theory and practice, addressing critical issues like work-life balance in digital environments and the future of hybrid workplaces.
Dar Roberts is a Professor in the Department of Geography at the University of California, Santa Barbara, where he directs the Visualization & Image Processing for Environmental Research (VIPER) Lab. His research focuses on advanced remote sensing applications including: Imaging spectrometry for ecosystem analysis Wildfire fuel mapping and fire emissions modeling Drought impact assessment on vegetation Land use/land cover change detection Integration of remote sensing with climate modeling Roberts leads the Southern California Wildfire Hazard Center and has pioneered techniques for mapping wildfire fuels using remote sensing technologies. His work combines field measurements with satellite, airborne, and drone-based sensors to monitor environmental changes.
Piotr Winkielman is a Professor of Psychology at the University of California, San Diego (since 2007), with affiliations at Warwick Business School (UK) and the Warsaw School of Social Sciences and Humanities (Poland). His research focuses on the interplay of emotion, cognition, embodiment, and consciousness in social cognition, employing methods from social/cognitive psychology and neuroscience. Key interests include unconscious emotion processing, facial mimicry, decision-making under emotional influence, and the neural basis of social perception. Education: PhD in Social Psychology (1997), University of Michigan MSc in Psychology (1991), University of Bielefeld, Germany BSc in Psychology (1988), University of Warsaw, Poland Research Interests: Winkielman explores how fleeting affective reactions influence behavior without conscious awareness, studying facial feedback mechanisms, emotional contagion, and the role of physiological signals in decision-making. His work bridges theories like Affect-As-Information and Facial Feedback, while challenging assumptions about the necessity of conscious processes in emotion. Grants & Funding: Supported by NSF Grant BCS-0350687 for studies on unconscious emotion and physiological feedback. Collaborations include projects on mimicry, stress effects, and cross-modal perception. Labs & Teams: Leads research at UCSD on embodied cognition and social neuroscience, with studies involving EEG, EMG, and behavioral experiments. International collaborations span UK, Poland, and Germany.
Larry Heck is a Professor at the Georgia Institute of Technology with joint appointments in the School of Electrical and Computer Engineering and the School of Interactive Computing. He holds the Rhesa S. Farmer Advanced Computing Concepts Chair and is a Georgia Research Alliance Eminent Scholar. His research focuses on machine learning, deep learning, natural language processing, conversational systems, and speech/speaker recognition. He directs the AI Virtual Assistant (AVA) Lab, advancing next-generation AI assistants. Dr. Heck has held leadership roles in industry, including at Microsoft, Google, Samsung, and Viv Labs, and has over 50 U.S. patents. Education: BSEE from Texas Tech University (1986) MSEE and PhD in Electrical Engineering from Georgia Tech (1991) Research Interests: Dr. Heck’s work bridges machine learning and human-centric AI, with emphasis on conversational systems, multimodal interaction, and real-world applications. His AVA Lab develops AI assistants that integrate visual, auditory, and contextual cues for natural interaction. Recent projects include multimodal sensor integration, dialogue systems for caregiving networks, and embodied AI for avatar animation. Awards: IEEE Fellow (2020) Academy of Distinguished Engineering Alumni, Georgia Tech (2017) Distinguished Engineer Award, Texas Tech University (2017) Advising & Grants: While primarily focused on industry collaboration, Dr. Heck mentors students through Georgia Tech’s interdisciplinary programs. His research is funded by government agencies and corporate partnerships, including the NSA and DARPA. Labs & Teams: The AVA Lab collaborates with academia and industry to create AI systems that understand context, gestures, and environment. Current initiatives include multimodal dialogue datasets (e.g., OKCV, SensorQA) and reinforcement learning frameworks for real-time systems.
Karin Coifman is a Professor and Chair at Kent State University's Department of Psychological Sciences. She holds a Ph.D. from Columbia University (2008) and specializes in clinical psychology with a focus on emotion regulation, stress, and psychopathology. Her research examines emotion processing and regulation in relation to mental health adjustments during acute and chronic stress. This includes studying resilience, mental illness development, and the role of psychophysiological and behavioral indices in emotion regulation. She leads the Kent Clinical Affective Science Lab and frequently teaches courses in Psychological Interventions and Introduction to Psychotherapy. Dr. Coifman's recent publications analyze pandemic response behaviors, emotion differentiation, and gene-environment interactions in affective disorders. Her work combines experimental methodologies with community and clinical populations. Labs/Teams: Kent Clinical Affective Science Lab
Emma Martin is Senior Lecturer in Museology at the University of Manchester's School of Arts, Languages and Cultures, where she serves as Associate Director for Research (Impact and Knowledge Exchange). With over 25 years of professional experience including 17 years as Senior Curator for National Museums Liverpool (2003-2020), her work bridges academic research and museum practice. Her current research focuses on colonial-era Tibetan collections, contemporary museum activism, and dissident curatorial practices in exile contexts. Dr. Martin's research interests sit at the critical intersection of colonialism, Tibetan Studies, and material culture studies. She examines how colonial-era museum collections continue to shape contemporary representations of Tibet while exploring pathways for Tibetan agency in museum decision-making. Her practice-led research includes serving as curatorial advisor to the Dalai Lama Centre for Tibetan and Ancient Indian Wisdom (2024-25) and leading the development of the Tibet Museum for the Central Tibetan Administration (2017-2023). She co-convenes the international Tibetan Materiality Network, fostering cross-border collaboration on Himalayan material culture research. Her publication trends reveal a sustained focus on decolonizing museum practices through historical analysis of Tibetan material culture. Early work examined colonial collecting networks and diplomatic gift exchanges, while recent publications address contemporary issues like digital sovereignty, museum representation of diaspora communities, and dissident curatorial methodologies. Her scholarship consistently connects archival research with practical museum interventions, demonstrating how historical understanding can inform ethical contemporary practice. Fellow, Royal Asiatic Society Fellow, Higher Education Academy Dr. Martin has supervised four completed PhDs and currently mentors five doctoral students working on topics spanning South Asian, Himalayan, and Tibetan museology. Her research project "Object Lessons from Tibet and the Himalayas" involves international collaboration with institutions in Copenhagen and explores how material culture can challenge colonial narratives. Her impact work includes developing new museological approaches for representing Tibet, referenced in Wikipedia and cited by policy makers addressing cultural restitution. She leads the Tibetan Materiality Network connecting European and Asian researchers, and her current monograph "The Dissident Museum: Oppositional Curating at the Tibet Museum" (Routledge) documents innovative curatorial practices developed during the Tibet Museum project. Her external roles include curatorial advisory positions with Tibetan cultural institutions and examination duties at UCL and University of Westminster.
Associate Professor Sunny-Boy Ahmar Mahboob is a distinguished linguist at the University of Sydney, where he serves as Degree Coordinator for the Master of Crosscultural and Applied Linguistics program within the Department of Linguistics, Faculty of Arts and Social Sciences. With extensive experience in applied linguistics and language education, Dr. Mahboob has established himself as a leading expert in World Englishes, TESOL, and language variation research, both nationally and internationally. Dr. Mahboob's educational background includes: BA from Karachi MA from Karachi MA from Indiana University MEd from Sydney PhD from Indiana University (2003) Dr. Mahboob's primary research focuses on language variation in global contexts, with particular attention to World Englishes, the NNEST (Non-Native English Speaking Teachers) movement, language policy, and decolonial approaches to linguistics. His work critically examines how language policies and practices affect educational outcomes and social justice, especially in postcolonial contexts like Pakistan and the Middle East. He pioneered 'appliable linguistics' - an approach that bridges theoretical linguistics with practical applications in education and policy, emphasizing the need for linguistic theories to address real-world problems. His recent publications reveal a strong trajectory toward decolonial linguistics, with increasing focus on subaltern perspectives, environmental connections to language diversity, and critical examinations of colonial legacies in language education. Dr. Mahboob's work consistently addresses power dynamics in language teaching and the need for more inclusive approaches that value linguistic diversity across educational contexts from primary schools to universities. Dr. Mahboob has received numerous prestigious awards: 2019: Australia's Research Field Leader in English Language and Literature (The Australian's Research magazine) 2012: Fellow of the National Talent Pool; President's Programme for Highly Qualified Overseas Pakistanis 2006: Faculty of Arts and Social Sciences Teaching Award, University of Sydney 2005: Teaching Initiative Award and Fellow of the Association of Pacific Rim Universities 2004: ECU Research and Creativity Award 2002: 'Distinguished President Award' from INTESOL, Indianapolis As an academic mentor, Dr. Mahboob supervises research students including Ruohong CAO (Developing Mandarin Learning Materials for Young Learners in Australia through Positive Discourse Analysis) and Tracy GAO (Evaluating Chinese Language Textbooks: A Sociosemiotic Perspective). His editorial work includes serving as Editor of TESOL Quarterly (2014-2017) and Associate Editor for multiple linguistics journals. Dr. Mahboob has secured significant research funding for projects including the SLATE (Scaffolding Literacy in Academic and Tertiary Environments) project and indigenous language funding initiatives in Australia. Dr. Mahboob founded and leads the International Free Linguistics Conference series, which has become an important platform for critical and alternative approaches to linguistics. His 'SLATE project' focuses on genre-based pedagogy for academic writing, and he actively collaborates with researchers across multiple continents through the World Englishes research network. His recent work increasingly explores the connections between language diversity and environmental sustainability, positioning linguistic ecology as a critical component of broader ecological concerns.
Beatrice Lerma is an Associate Professor at the Polytechnic University of Turin , affiliated with the Department of Architecture and Design and serving as Deputy Coordinator of the Doctoral School of Design and Technology: People, Environment, Systems . Research focuses on Innovative Materials , Sensory Design , and Design for Cultural Heritage Key skills in Environmental Engineering , Industrial Design , and Circular Economy Her recent work explores the intersection of Artificial Intelligence and Material Innovation , particularly in sustainable polymer systems and transparent wood technology. She leads the BIOMAPS (2025-2028) and AI-TRANSPWOOD (2024-2026) projects. 2025: AI applications in biobased materials 2024: Cultural heritage signage solutions 2024: Circular material taxonomic frameworks Scientific recognitions include ADI Design Index Selection Award (2015) and Young & Design (2013). She supervises PhD candidates Noemi Emidi and Eva Vanessa Bruno , and serves on the OFFICINA Scientific Committee since 2014.
Vatsal Sharan is an Assistant Professor in the Thomas Lord Department of Computer Science at the University of Southern California's Viterbi School of Engineering. He maintains affiliations with the Theory Group, Machine Learning Center, and the Center for AI in Society at USC. Education: Ph.D. in Computer Science from Stanford University, advised by Greg Valiant Postdoctoral research at MIT, hosted by Ankur Moitra Vatsal Sharan's research centers on the theoretical foundations of machine learning, positioned at the intersection of machine learning, theoretical computer science, and statistics. His work investigates fundamental limits for solving learning and estimation tasks under computational and information-theoretic constraints, with the goal of developing practical algorithms that are efficient, fair, and robust. His research spans memory-efficient learning, algorithmic fairness, robustness in deep learning, and the theoretical underpinnings of transformers and large language models. A significant portion of his work explores how memory constraints affect learning algorithms and whether memory can serve as a distinguishing factor between 'efficient' and 'expensive' techniques in machine learning. His recent publications demonstrate a strong focus on multicalibration, transformer interpretability, and trustworthy AI systems. Scientific Awards: Amazon Research Award (2021 and 2023) SoCal NLP Symposium 2023 Best Paper Award COLT 2022 Best Paper Award Vatsal Sharan advises a diverse group of Ph.D. students including Siddartha Devic, Bhavya Vasudeva, Julian Asilis, Deqing Fu, Devansh Gupta, Spandan Senapati, and Tianyi Zhou. His research is supported by multiple prestigious grants from the NSF, Amazon Research, Google Research, and the Okawa Foundation. He is an active participant in the Learning Theory Alliance (LeT-All), a community-building and mentorship initiative for the learning theory community. His teaching portfolio includes advanced courses on machine learning theory and trustworthy machine learning at USC, where he shapes the next generation of researchers in theoretical aspects of artificial intelligence.
Abhinav Shrivastava is an Associate Professor in the Department of Computer Science at University of Maryland, College Park, with a joint appointment in the Institute of Advanced Computer Studies (UMIACS). Previously, he served as an Assistant Professor at the same institution from August 2018 to June 2024, and spent one year as a Visiting Research Scientist at Google Research from September 2017 to August 2018. His educational background includes: PhD in Robotics and Artificial Intelligence from Carnegie Mellon University (2017), advised by Abhinav Gupta, with thesis titled 'Discovering and Leveraging Visual Structure for Large-scale Recognition' MS in Artificial Intelligence from Carnegie Mellon University (2011), supervised by Alyosha Efros and Martial Hebert BTech in Computer Science and Engineering from Jaypee Institute of Information Technology (2010) Professor Shrivastava's research focuses on computer vision and machine learning, with particular expertise in object detection, image recognition, and neural representations. His work bridges theoretical advances with practical applications, exploring how visual systems can discover and leverage structure in large-scale recognition problems. He has made significant contributions to understanding the role of supervision in vision transformers, developing novel approaches for object-state composition recognition, and creating efficient neural representations for videos and 3D scenes. His research often addresses fundamental challenges in visual recognition, including handling novelty in open-world environments and improving the efficiency of visual systems. An analysis of his recent publications reveals a strong emphasis on neural representations, particularly for dynamic content like videos and 3D scenes. His work demonstrates increasing sophistication in handling open-world vision problems, with research spanning object discovery, localization, and representation learning. The publications show a clear progression toward more efficient and scalable models, with recent work focusing on model compression, sparse representations, and addressing the challenges of working with limited annotations. His scientific contributions have been recognized with several prestigious awards: Best Paper Award (Applications) at IEEE Winter Conference on Applications of Computer Vision (2020) Microsoft Research PhD Fellowship (2014-2016) Best Student Paper Award at IEEE Winter Conference on Applications of Computer Vision (2014) Outstanding Reviewer Award at IEEE CVPR (2015) Professor Shrivastava has successfully mentored numerous graduate students, many of whom have become prominent researchers in computer vision. His Amazon Research Awards (2020 and 2023) have supported innovative projects including 'The pursuit of knowledge: discovering and localizing new concepts using dual memory' and 'Audio-conditioned Diffusion Models for Generating Lip-synchronized Videos.' He has served as Area Chair for major conferences including ICCV, CVPR, and AAAI, demonstrating his leadership in the computer vision community. His research has attracted significant funding from both academic and industry sources, supporting his exploration of fundamental questions in visual recognition and representation learning.
Chao Liu is a Research Scientist at CNRS (French National Center for Scientific Research) since 2008, affiliated with the DEXTER team and the Department of Robotics, LIRMM at University of Montpellier, France. He earned his Ph.D. in Electrical & Electronic Engineering from Nanyang Technological University, Singapore (2006). Current research focuses on surgical robotics , haptics , teleoperation , and nonlinear control theory with applications in computer vision. His work addresses challenges in robotic-assisted telesurgery, including: Stable and transparent human-robot interaction through wave variable compensators and passivity filters Physiological motion compensation using spatio-temporal LSTM and dual Kalman filters EMG-based motion recognition for surgical skill assessment 3D soft-tissue reconstruction with stereo-endoscopes and deep learning Dr. Liu leads European and French projects like: TS2RT (CNRS-funded): Safer teleoperation with motion compensation ROBACUS (ANR-funded): Needle positioning with MPC control HaTUMoCo (CNRS-funded): Haptic teleoperation with uncertainty handling ARAKNES (EU-funded): Microrobotic systems for endoluminal surgery Scientific honors include Senior Member of IEEE and Member of Sigma Xi . He supervises Ph.D. and Master's students working on topics such as concentric tube robot optimization, haptic teleoperation, and EMG-based force estimation. Dr. Liu serves on IEEE Technical Committees for Telerobotics and Haptics , and as Technical Editor of IEEE/ASME Transactions on Mechatronics.
Jeremy Blackburn is an Associate Professor in the Department of Computer Science at Binghamton University. He co-founded the International Data-driven Research for Advanced Modeling and Analysis Lab ( iDRAMA Lab ) and leads its Binghamton satellite. His research focuses on large-scale measurement and analysis of social media, particularly the behavior of malicious actors and disinformation campaigns.
Richard Eberhardt serves as Program Manager for the MIT Game Lab and instructor for MIT Game Lab classes at the Massachusetts Institute of Technology, where he aligns research projects with staff, equipment, and funding while mentoring student game development initiatives. His operational leadership supports the lab's mission to advance game literacy through interdisciplinary collaboration. His academic credentials include: Bachelor of Arts from the College of William & Mary Serious Games MA Certificate from Michigan State University Professional certifications: Certified Scrum Master PMI Agile Certified Practitioner Eberhardt's research investigates historical representation in games, analyzing how mechanics model historical systems and which narratives are amplified or marginalized in gaming communities. His scholarship spans serious games for mental health awareness, educational applications of VR/AR technologies, and inclusive game jam methodologies, consistently addressing public literacies through civic systems and emotional intelligence frameworks. Analysis of his 2013-2023 publications reveals sustained focus on game-based educational tools across STEM and humanities domains. His work pioneers VR simulations for photonics education, examines historical accuracy in commercial games, and develops inclusive frameworks for collaborative design events. This output demonstrates strategic integration of game mechanics with learning objectives while addressing representation gaps in historical gaming. Notable recognition includes an award for elude , the depression awareness game developed in 2010 for patients' support networks. As a mentor, Eberhardt directs student projects like elude and hosts game jams fostering community collaboration. His Agile-certified project management approach facilitates resource allocation across educational initiatives, though specific grant details remain undisclosed in available materials. The MIT Game Lab operates as his primary research ecosystem, connecting students, faculty, and community partners to explore games' transformative potential in education and social contexts through its Civic Systems, Media & Emotional Intelligence pillar.
