Amanda Phillips is an Associate Professor at Georgetown University, affiliated with the Departments of English, Film and Media Studies, Women’s and Gender Studies, and American Studies. Their research focuses on feminist and queer theory in digital media, with a particular emphasis on critical game studies and digital humanities. Selected publications include Gamer Trouble: Feminist Confrontations in Digital Culture and co-editing the Queer/Trans/Digital book series. Their scholarship appears in journals such as ROMchip , Feminist Media Histories , and Games and Culture . Research Interests: Digital media and gender politics Queer theory in gaming contexts Decolonial and anti-racist digital humanities Critical analysis of game mechanics Digital labor and precarity Affective histories of gaming Scientific Awards: Mellon/ACLS Dissertation Completion Fellow Academic Leadership: Former chair of the American Studies Association Digital Humanities Caucus Co-founder of the #transformDH Collective Editorial work on special issues of Game Studies and Antares: Letras e Humanidades Previous Institutions: IMMERSe Postdoctoral Fellow at University of California, Davis Ph.D. recipient from University of California, Santa Barbara with emphasis in Feminist Studies
Joshua D. Angrist is the Ford Professor of Economics at the Massachusetts Institute of Technology, where he has been a faculty member since 1996. He is also a co-founder and director of MIT's Blueprint Labs and a Research Associate at the National Bureau of Economic Research. Angrist shares the 2021 Nobel Prize in Economic Sciences with David Card and Guido Imbens for their methodological contributions to the analysis of causal relationships. Angrist received his B.A. from Oberlin College in 1982 and completed his Ph.D. in Economics at Princeton University in 1989. Prior to joining MIT, he taught at Harvard University and the Hebrew University of Jerusalem. His academic journey began somewhat unconventionally, as he left high school early after 11th grade, worked for over a year, and only later discovered his passion for economics through an inspiring teacher at Oberlin. Angrist's research focuses on developing and applying innovative econometric methods to answer important economic questions using natural experiments. His work spans labor economics, education economics, and causal inference methodology. He is particularly known for his contributions to instrumental variables methods and the Local Average Treatment Effect (LATE) framework developed with Guido Imbens. His research explores the economics of education and school reform, the impact of social programs on labor markets, and the effects of immigration and regulation. His recent publications reveal a continued focus on causal inference methods applied to education policy questions, labor market issues, and health economics. The trend shows increasing sophistication in research design, with particular attention to addressing selection bias and developing methods for external validity. His work spans theoretical econometric contributions alongside empirical applications in education, labor markets, and health. Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel (2021) Fama Prize for Graduate Education (2018) Fellow of the American Academy of Arts and Sciences Fellow of the Econometric Society Angrist is deeply committed to teaching and mentoring. He has developed influential econometrics textbooks including 'Mostly Harmless Econometrics' and 'Mastering Metrics' with Jörn-Steffen Pischke. At MIT, he teaches courses including Labor Economics I (14.661), Econometric Data Science (14.32), and Labor Economics and Public Policy (14.64). He emphasizes selecting UROP students who have mastered foundational economics through courses like 14.64 and 14.32. Beyond MIT, Angrist co-founded Avela, a software startup using cutting-edge research to help schools improve enrollment and operations. Angrist co-founded and directs MIT's Blueprint Labs, which brings together researchers from economics, computer science, and education to develop innovative solutions for educational challenges. Through Blueprint Labs and Avela, his work bridges academic research with practical applications in education policy and technology.
Michael Carbin is the Jamieson Career Development Assistant Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT) and leads the MIT Programming Systems Group. His research focuses on programming systems that address system uncertainty to enhance performance, energy efficiency, and resilience, particularly in environments involving neural networks , approximate computing , and unreliable hardware . His work spans probabilistic programming , quantum computing , and machine learning systems . Articles highlight contributions in pruning neural networks , quantum data structures , and compiler optimization , reflecting trends in deep learning , formal verification , and language-driven systems . Scientific Awards : MIT Frank E. Perkins Award (2020) Sloan Research Fellowship (2020) Facebook Research Award (2019) NSF CAREER Award (2018) Best Paper Awards at OOPSLA (2013, 2014) He has advised numerous graduate students and postdocs including Eric Atkinson, Cambridge Yang, and Charles Yuan, and served on program committees for conferences like POPL, OOPSLA, and ICLR. His group collaborates with institutions such as MIT CSAIL and explores applications in quantum algorithms and probabilistic inference .
Greg Durrett is an Associate Professor in the Department of Computer Science at University of Texas at Austin, leading the TAUR Lab (Text Analysis, Understanding, and Reasoning ). His research focuses on advancing Large Language Models (LLMs) for knowledge-intensive tasks in medical information processing scientific discovery legal reasoning . He received his B.S. in Computer Science and Mathematics from MIT (2010) and Ph.D. in Computer Science from UC Berkeley (2016). His work develops techniques to train LLMs with new capabilities augment models for reliability assess model outputs improve reasoning frameworks . His 15 most recent publications (2021-2025) span knowledge propagation in LLMs chain-of-thought reasoning code generation benchmarks multi-modal reasoning fact verification discourse analysis . Scientific honors include NSF CAREER Award (2024) NSF grants (2018, 2024) Bloomberg Data Science Grant (2017) Facebook Fellowship (2014) Best Paper Finalist (EMNLP 2013) . Teaching: CS388: Natural Language Processing (graduate) CS371N: NLP (undergraduate) High school NLP module .
Dr. François Soyer is an Associate Professor at the University of New England's School of Humanities, Arts, and Social Sciences, specializing in Early Modern History. He holds a PhD from the University of Cambridge (2007) and has held academic positions at the University of Southampton and the University of Adelaide. His research focuses on anti-Semitism, the Spanish and Portuguese Inquisitions, gender/sexuality history, and colonial empires. He has authored multiple books and articles, including Popularizing anti-Semitism in early modern Spain and its empire (2014) and Antisemitic conspiracy theories in the early modern Iberian world (2019). His work often examines how religious persecution intersected with medical, artistic, and legal practices. Education: PhD in History, University of Cambridge (2007) MPhil in History, University of Cambridge (2003) MA Honours, University of St. Andrews (2002) Postgraduate Certificate in Academic Practice, University of Southampton (2011) Research Interests: Anti-Semitic propaganda and conspiracy theories Inquisitorial archives and legal practices Gender transgression and queer histories Censorship of art and religious imagery His recent publications explore the Blood Libel legend, the trial of Catalan cross-dresser Maria Duran, and the emotional dimensions of religious conversion. He has been awarded fellowships from the Royal Historical Society and the Parkes Institute. His current projects include tracing the origins of anti-Jewish iconography in colonial Peru and analyzing the role of emotion in early modern religious trials.
Karthik R. Narasimhan is a Professor at Princeton University's School of Engineering and Applied Science in the Department of Computer Science. Previously, he earned his PhD from MIT under Regina Barzilay and served as a visiting research scientist at OpenAI during 2017-18. His research focuses on the intersection of language and decision-making, building autonomous agents that learn from both experience and human knowledge. His research spans multiple high-impact areas including language agents (Text-DQN, CALM, ReAct, Tree of Thoughts), reinforcement learning (h-DQN, Multi-Objective RL), and AI safety (Toxicity in ChatGPT, DataMUX). He has developed critical datasets and benchmarks such as WebShop, InterCode, SWE-bench, and SILG that have become standard evaluation tools in the field. Current work emphasizes agent capabilities, software engineering automation, and multimodal interaction. His publication trends show strong focus on practical agent deployment (SWE-agent, Tree of Thoughts), safety evaluation (Probing AI Safety), and efficiency improvements (DataMUX). Recent work increasingly addresses real-world challenges in software engineering, security, and human-AI collaboration through rigorous benchmarking. Co-author of foundational GPT (2018) paper Key developer of Text-DQN (2015), CALM (2020), ReAct (2022), Tree of Thoughts (2023) Creator of influential benchmarks: WebShop (2022), SWE-bench (2023), InterCode (2023) He actively advises students through Princeton's computer science program, with research supported by multiple grants focused on autonomous agent development and language-based decision systems. His GitHub repositories (nlp-datasets, text-world-player) demonstrate strong community engagement in open-source research tools. Current projects include advancing language agent capabilities through Reflexion (2023) and Tree of Thoughts (2023) frameworks while addressing critical safety and efficiency challenges.
Christopher Thomas Sege, PhD is an Assistant Professor in the Department of Psychiatry and Behavioral Sciences at the Medical University of South Carolina (MUSC) College of Medicine. His research focuses on the neurophysiological mechanisms underlying anxiety disorders, particularly examining escape, avoidance, and approach behaviors in the anxiety disorder spectrum. Dr. Sege's primary research interests include: Anxiety Disorders and Emotional Processing Defensive Behaviors and Coping Mechanisms Neurophysiological Correlates of Emotional Anticipation Startle Response and Autonomic Nervous System Functioning Transcranial Magnetic Stimulation (rTMS) Applications His work bridges clinical psychology with neuroscience to understand how individuals with anxiety disorders process and respond to emotional stimuli. Dr. Sege leads the research study "Modeling and Modulating Mechanisms of Escape, Avoidance, and Approach in the Anxiety Disorder Spectrum" which investigates whether repetitive transcranial magnetic stimulation (rTMS) can alter how people with anxiety cope with emotional situations. This study involves measuring brain activation while participants view emotional pictures and undergo rTMS procedures. His publication record demonstrates expertise across multiple domains: Neurophysiological mechanisms of defensive behaviors Emotional anticipation and perception Startle modulation in anxiety disorders Borderline personality disorder research Development of experimental paradigms for emotional processing studies His research employs multiple methodologies including psychophysiology, event-related potentials, and neurostimulation techniques. Dr. Sege collaborates with researchers including Lisa McTeague, Bernadette Cortese, Carla Danielson, Thomas Uhde, and Aicko Schumann. His work appears in journals such as Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, Biological Psychology, and Psychophysiology.
Andy Pavlo is an Associate Professor with Indefinite Tenure in the Computer Science Department at Carnegie Mellon University's School of Computer Science. He is an active member of the CMU Database Group and the Parallel Data Laboratory, where he leads research in database management systems with a focus on self-driving architectures, transaction processing, and large-scale analytics. His work bridges academic research and industry applications through projects like NoisePage, OtterTune (which he co-founded and served as CEO before it ceased operations), and Peloton. Dr. Pavlo's research interests span database management systems with particular emphasis on autonomous database architectures that can self-tune and optimize without human intervention. His work explores transaction processing systems that can handle high-throughput workloads while maintaining consistency, and large-scale data analytics techniques that efficiently process massive datasets. He has made significant contributions to query optimization, database extensibility, and automatic database tuning using machine learning techniques. His recent work on database extensibility revealed critical issues in PostgreSQL's extension ecosystem, showing that approximately 16% of extensions are incompatible with at least one other extension due to API violations and memory errors. His research output demonstrates a consistent focus on practical database systems challenges, with recent publications examining database extensibility, user-defined function optimization, and the cyclical nature of database research. The articles show a strong trend toward making database systems more autonomous, with increasing integration of machine learning techniques for automatic tuning and optimization. His work often combines deep theoretical analysis with practical implementation in open-source systems. Dijkstra Award 2024 for contributions to database systems research Dr. Pavlo actively mentors graduate students, with current advisees including Wan Shen Lim, William Zhang, and Sam Arch (co-advised with Todd Mowry). His former students have gone on to successful careers in both industry and academia. He has secured significant research funding through CMU's affiliate program with major database companies including ClickHouse, DataStax, dbt, Firebolt, MotherDuck, RelationalAI, SingleStore, Spiral, PingCAP/TiDB, Yellowbrick, and Yugabyte. His research is supported by these industry partnerships and likely includes NSF funding given his active participation in the database research community. At CMU, Dr. Pavlo leads the Database Group and organizes several seminar series including "SQL or Death," "Database Building Blocks," and "ML⇄DB Technical Talks." These seminars bring together researchers and practitioners to discuss cutting-edge developments in database systems. He also runs a summer research internship program that has attracted students for multiple consecutive years, indicating a strong research group with ongoing projects and funding.
Babak Falsafi is a Full Professor at the School of Computer and Communication Sciences (IC) at EPFL, leading the Parallel Systems Architecture Laboratory (PARSA). He is a renowned expert in computer architecture, datacenter systems, and cloud-native server design. His research focuses on post-Moore era computing, emphasizing heterogeneous architectures, energy efficiency, and scalable IT infrastructure. Falsafi is the founder of EcoCloud, an EC-sponsored industrial-academic consortium investigating sustainable information technology. He holds ACM and IEEE fellowships, a Sloan Research Fellowship, and has contributed to major projects like Optimus Prime (data transformation acceleration), AstriFlash (flash-based online service systems), and Midgard (virtual memory re-design). His work spans hardware-software co-design, memory systems, and security. Falsafi advises numerous PhD students and collaborates with industry partners such as Google and Cavium. Key achievements include pioneering scalable multiprocessor architectures, snoop filters in IBM BlueGene, and spatial memory streaming in ARM cores. His lab develops open-source tools like QFlex for server simulation. He frequently presents at top conferences (HPCA, ISCA, MICRO) and chairs workshops on post-Moore infrastructure. Teaching roles include leading courses in computer architecture and parallel systems across multiple EPFL departments (SIN, EDIC, SSC, SMA). His work addresses datacenter challenges like the 'data tax' and mitigating latency through specialized accelerators.
Professor Valeska Ferrer Usó is a canon lawyer and theologian at Comillas Pontifical University, specializing in abuse prevention in ecclesiastical environments. She coordinates the UNIJES-funded Jordán research project (since 2021) and teaches subjects including 'Christianity and Social Ethics' and 'State Ecclesiastical Law' since 2022/23. Education: Doctorate in Canon Law (2022), Law Degree (2002), Ecclesiastical Studies (2012), Expert in Neuropsychology (2017), Specialist in Spiritual Exercises (2008). Her research focuses on canonical criminal law, restorative justice, and structural analysis of abuse mechanisms in religious institutions. Recent publications address procedural reforms, memory spaces for reconciliation, and interdisciplinary abuse prevention frameworks. She practices law at Madrid's Ecclesiastical Tribunal in marriage annulment cases and contributes to the Society of Jesus' Safe Environment System team (since 2024). Her work integrates theological, legal, and neuropsychological perspectives.
Ryan M Hebert, MD, is an Assistant Professor of Neurosurgery at the Yale School of Medicine, affiliated with the Neurosurgery department. He specializes in neurovascular disorders, including open and endovascular treatments for intracranial aneurysms, arteriovenous malformations, carotid disease, and dural arteriovenous fistulas. He also focuses on interventions for ischemic and hemorrhagic strokes. His practice locations include Yale New Haven Hospital and Lawrence and Memorial Hospitals in Connecticut. Education & Training: Bachelor’s in Molecular, Cellular, and Developmental Biology from the University of Colorado – Boulder (Howard Hughes Undergraduate Research Grant recipient) MD from Yale School of Medicine (NIH-funded thesis on CCM3 in cerebral cavernous malformations) 7-year Neurosurgery Residency at Yale New Haven Hospital, including enfolded neuro-interventional training CAST-accredited fellowship in Endovascular Neurosurgery and Neurovascular Critical Care at Thomas Jefferson University Hospital (2016) Research Interests: Dr. Hebert’s work centers on emerging surgical and endovascular techniques for neurovascular disorders, risk stratification in carotid disease, vasospasm prediction/post-subarachnoid hemorrhage treatment, and outcomes of minimally invasive spine surgery. His studies often integrate clinical practice with translational research, emphasizing patient outcomes and procedural optimization. Key topics include flow diverters, cranial nerve palsies, hospital frailty risk scores, and immune mechanisms driving aneurysm rupture. Publications Trends: His recent articles emphasize clinical outcomes of endovascular procedures, stroke interventions, and immune mechanisms in aneurysm rupture. He frequently collaborates on meta-analyses and systematic reviews to evaluate treatment efficacy and complication rates, particularly involving cranial nerve recovery and thrombectomy volumes. Awards & Grants: He secured an NIH-funded thesis and a Howard Hughes Undergraduate research grant. No explicit scientific awards are listed, but his work has been recognized via peer-reviewed publications and contributions to clinical guidelines. Advising & Grants: While no students are listed, he collaborates with prominent researchers like Charles Matouk, Kevin Sheth, and Joseph Antonios on NIH-funded projects. His research addresses healthcare resource utilization and procedural volume impacts on mortality, indicating a focus on translational and clinical studies. Labs & Teams: Active in interdisciplinary teams at Yale School of Medicine, particularly in neurovascular critical care and endovascular surgery. Collaborates with the Stroke Center and Janeway Society for physician-scientist development.
Olle Sköld is a Senior Lecturer at the Department of ABM (Archives, Libraries, and Museums) at Uppsala University. He is also the Head of the Department of ABM and holds an Associate Professor position in Library and Information Science. His research spans digital humanities, documentation practices, knowledge production, and digital preservation, with a particular focus on archaeological data processes and virtual world communities. Archaeological data documentation and reuse Digital game preservation Paradata theory and applications Information practices in social media His recent publications explore paradata in data papers, literacy challenges in research data management, and trust technologies like blockchain in digital archives. Olle is involved in the CAPTURE project, investigating documentation workflows for archaeological data. He has contributed to the Master's Programme in Digital Humanities at Uppsala University, blending digital humanities with library and information science education.
Andrew Yonelinas is a Professor in the Department of Psychology at the University of California, Davis, where he directs the Human Memory Lab. He holds additional leadership roles as Associate Director of the Center for Mind and Brain and is an affiliated faculty member with the UC Davis Center for Neuroscience. His research bridges cognitive psychology and neuroscience to investigate fundamental memory mechanisms and their neural substrates. His educational background includes a Ph.D. in Experimental Psychology from McMaster University (1995) and a B.S. in Cognitive Science from the University of Toronto (1990). These foundational studies established his expertise in experimental methodologies and cognitive theory. Yonelinas specializes in dual-process models of memory, distinguishing between recollection (detailed contextual retrieval) and familiarity (vague recognition). His lab employs process dissociation, remember/know procedures, and ROC modeling alongside neuroimaging (fMRI, ERP) and clinical studies with amnesic and Alzheimer's patients. Recent work expands into auditory working memory, multisensory integration, and the impact of mental illness on cognitive processes, revealing hippocampal roles across memory systems. His research consistently addresses how memory fails in clinical conditions while developing unified theoretical frameworks. Analysis of his 2024-2025 publications shows a strong focus on memory mechanisms across sensory modalities, with increasing emphasis on clinical applications. Key trends include hippocampal contributions to visual/auditory working memory, EEG-based biomarkers for mental illness, and the interplay between schema knowledge and memory distortion in aging populations. His work demonstrates methodological innovation through model-based EEG phenotyping and multisite clinical collaborations. His scientific recognition includes: American Psychological Society’s Shahin Hashtroudi Memorial Award University of California Chancellor’s Fellow Award European Brain and Behavior Society International Lecture Award Yonelinas actively shapes his field through editorial roles at top journals including Proceedings of the National Academy of Sciences and Journal of Experimental Psychology, while serving as a grant reviewer for NIH, NSF, and international funding bodies. His Human Memory Lab trains next-generation researchers in memory theory and methodology, with recent projects examining stress effects on memory precision and neural mechanisms of action slips. The Human Memory Lab operates within UC Davis's neuroscience ecosystem, collaborating closely with the Center for Mind and Brain on projects involving clinical populations and neuroimaging. Current initiatives include the CNTRACS Consortium for EEG standardization in mental illness and investigations into how stress modulates memory binding through hippocampal mechanisms.
Dr Fiona Hum is a Senior Lecturer at Monash University's Faculty of Law, where she conducts research and teaches. Admitted as a solicitor and barrister of the Supreme Court of Victoria, she previously practiced commercial litigation, criminal law, and personal injury law while consulting for major insurers and the Victorian police force. Her doctorate from the University of Melbourne focused on Northern Territory euthanasia laws. Education: Doctorate in Law, University of Melbourne (thesis on euthanasia laws) Admitted Solicitor and Barrister, Supreme Court of Victoria Research Focus: Dr Hum's work centers on Evidence Law , Wrongful Convictions , and Gender/Race Relations in Law , with pioneering studies on compassion training for law students now expanding into climate change law. Her research directly supports UN Sustainable Development Goals for justice, equality, and well-being through interdisciplinary approaches connecting legal theory with psychological and social frameworks. Publication Trends: Recent work (2022-2025) analyzes high-profile cases like Kathleen Folbigg and Cardinal Pell while advancing evidence law pedagogy through her Cambridge University Press textbook. Earlier scholarship (2010) established foundational critiques of gender bias in evidentiary processes, particularly regarding women complainants and pregnant patients. Scientific Awards: Faculty Teaching Award for Teaching Excellence (2010) Certificate of Recognition for S1 Unit Performance (2015) Certificate of Recognition for S2 Unit Improvement (2016) Nominee: Inspiring Woman Award (2021) Nominee: Australian Legal Education Award (2023) Advising & Professional Impact: Accepting PhD students, Dr Hum actively shapes legal education through curriculum innovation and peer review for top journals ( University of New South Wales Law Journal , Sydney Law Review ). Her external collaborations include specialist lectures for Monash's Faculty of Medicine and keynotes at national conferences like the Women's Lawyers Conference on 'Justice for All'. Institutional Roles: Current member of the Australasian Law Academics Association (2025-2028) and former Honorary Fellow at the University of Melbourne (2019-2021), she bridges academic rigor with real-world legal practice through ongoing consultancy work.
Chantal Pellegrini is a Lecturer and PhD student at the Chair of Computer Aided Medical Procedures (Prof. Navab) at Technical University of Munich (TUM). Her research focuses on Deep Learning applications in medical imaging, including explainable AI for radiology report generation and Vision-Language Models for clinical decision support. She actively contributes to the DHM, NARVIS Lab, and RobUSt research groups. Teaching responsibilities include courses such as 'Computer Aided Medical Procedures', 'Medical Augmented Reality', and 'Surgical Robotics'. She supervises student projects in medical AI and healthcare innovation, with recent projects involving multimodal report generation and graph pretraining for medical applications. Education: BSc/MSc Computer Science (TUM), current PhD student since 2022 Labs: DHM (German Heart Center), NARVIS Lab, RobUSt Robotics & Ultrasound Research Keywords: Medical Image Understanding, Radiology Reports, LLMs in Healthcare Her publications span surgical OR dataset development, reinforcement learning for clinical decisions, and explainable X-ray diagnosis systems. She mentors MA/BA students in medical AI and project management for healthcare applications.
