Mark D. Haiman is a Professor at the University of California, Berkeley, Department of Mathematics, with research interests spanning algebra, combinatorics, and algebraic geometry. His work connects symmetric function theory with geometric objects like Hilbert schemes and algebraic structures such as Cherednik algebras and Hecke algebras. Appointed: 2001 Contact: mhaiman@math.berkeley.edu Teaching: Math 256B—Algebraic Geometry (Spring 2025), Math 249—Algebraic Combinatorics (Spring 2024), and others in calculus and Lie groups. Research Interests : Haiman's research focuses on Macdonald polynomials, LLT polynomials, Hilbert schemes of points in the plane, and their combinatorial and geometric implications. His work includes resolving the Macdonald positivity conjecture and the n! conjecture through algebraic geometry. Publications : Haiman has contributed to foundational papers in combinatorial and algebraic structures, including generalizations of the shuffle theorem and positivity results for LLT polynomials. His articles often bridge representation theory, symmetric functions, and geometric methods. Students : He has supervised numerous PhD students, including Magda Hlavacek (2023), Foster Tom (2022), Jeremy Meza (2021), Maryam Farahmand-Asil (2018), Maria Monks Gillespie (2016), and others working on combinatorial algebraic geometry and related fields.
Chi-Ming Yang is a Professor of English at the University of Pennsylvania's School of Arts & Sciences, where she has established herself as a leading scholar in literary and visual culture studies with a focus on race, empire, and East-West cultural exchanges. Her interdisciplinary approach bridges British, American, Asian, and Latin American studies while examining historical periods from the early modern era through the 18th century to contemporary contexts. Educational Background: Ph.D. in English from Cornell University B.A. in Comparative Literature from Stanford University with emphases in Spanish, Chinese, and English Professor Yang's research interrogates the intersections of race, visual culture, and imperial histories through multiple disciplinary lenses. Her work explores how objects, images, and texts function within global networks of power and representation, with particular attention to transpacific and transatlantic connections. She has developed significant expertise in chinoiserie, material culture, and the visual dimensions of racial formation across historical periods. Her recent publications demonstrate a growing interest in ecological perspectives on race and empire, particularly evident in her 2021 article 'The Song of the Rice Bird,' which innovatively examines plantation slavery through avian migration patterns. Her scholarship consistently bridges historical analysis with contemporary concerns about representation, power, and cultural exchange. Professional Recognition: 2022 Best Advisor Award in English, Sponsored by the English Undergraduate Advisory Board Professor Yang maintains an active advising role, having chaired doctoral dissertations including Jacob Myers' 'Noxious Life: Figuring Vermin in the Natural Histories of the Anglophone Caribbean' (2025) and Cassidy Holahan's 'Dramatizing the Novel: Transmedial Exchange in the Long Eighteenth Century' (2023). She regularly participates in departmental workshops and events, including the 2024 conversation with Sharon Holland exploring Black feminist perspectives on animal life in relation to Octavia E. Butler's work. Her teaching portfolio reflects her interdisciplinary approach, with recent courses including 'Science Fictions of Octavia E. Butler,' 'Orientalisms,' '18th-Century British Poetry,' and 'Arts of Abolition and Liberation,' demonstrating her commitment to connecting historical scholarship with contemporary social justice concerns.
Janina Dill holds the Dame Louise Richardson Chair in Global Security at the Blavatnik School of Government, University of Oxford. She is also a Professorial Fellow at Trinity College and Co-Director of the Oxford Institute for Ethics, Law, and Armed Conflict (ELAC). Her academic work focuses on the intersection of law, morality, and international relations in the context of war. Her research spans three interconnected strands: the legal requirements for military operations under international law; theoretical frameworks for understanding how international law serves as an instrument of morality in war; and empirical investigations into how moral and legal norms affect real-world military decision-making and public opinion in conflict zones. Professor Dill's work has particular relevance to contemporary conflicts, with extensive analysis of the wars in Ukraine and Gaza. She has examined how international humanitarian law applies to these conflicts, the moral arguments employed by different parties, and the practical challenges of implementing legal constraints in complex warfare environments. Her research has been recognized with the prestigious Philip Leverhulme Prize in 2021, which she has used to advance her work on the moral psychology of decision-making in war. She is currently leading multiple significant research projects, including a three-year ESRC/NSF-funded study on "Cumulative Civilian Harm" and an expert process with the ICRC on military objectives under international humanitarian law. Professor Dill is frequently consulted by international media outlets including The Guardian, The Economist, BBC, CNN, and major European publications. Her expertise is regularly sought on matters related to the laws and ethics of war, particularly regarding the conflicts in Ukraine and Gaza. She has received recognition for her contributions to the field through numerous speaking engagements, media appearances, and her influential research that bridges theoretical legal scholarship with practical applications in contemporary conflicts.
Robert Wilson is an Associate Professor in the School of Psychology at Georgia Institute of Technology. His research focuses on computational cognitive neuroscience, reinforcement learning, decision making, and their applications in psychiatry and aging. Wilson leads a lab integrating computational modeling with behavioral experiments, neuroimaging, and neurostimulation to explore the algorithms underlying human cognition. He holds a Ph.D. in Bioengineering from the University of Pennsylvania (2009). Education: Ph.D. in Bioengineering, University of Pennsylvania, 2009 Research Interests: Wilson’s work spans computational models of decision making, reinforcement learning dynamics, and the neural mechanisms of explore-exploit trade-offs. His lab investigates phishing detection cognition, navigation strategies, and perceptual decision making, with recent studies on aging-related cognitive decline and psychiatric disorders. Publications: His recent work includes studies on computational models of exploration strategies, phishing susceptibility (PEST task), and aging effects on decision-making. Articles often bridge neuroscience and AI, such as applying reinforcement learning to large language models. Awards & Grants: While no formal awards are listed, his research has been supported by grants exploring computational psychiatry and neuroimaging. Labs & Teams: Wilson directs a multidisciplinary lab at Georgia Tech, collaborating with experts in AI, neuroscience, and clinical psychology to advance computational theories of the mind-brain relationship.
Professor Brian Dillon is the Professor of Creative Writing and Director of Creative Writing at Queen Mary University of London's School of English and Drama. Previously, he served as Head of the Writing Programme at the Royal College of Art. He holds a PhD from the University of Kent (1999) and has authored numerous books blending creative nonfiction, literary criticism, and art analysis. His research focuses on the essay form, autobiography, literature-visual arts intersections, and writing about illness. Key publications include *Suppose a Sentence* (2020), an experimental essay collection analyzing literary sentences, and *Affinities* (2023), exploring photographic imagery. Current projects include a study of Kate Bush's *Hounds of Love* and an essay on education. Dillon frequently contributes to *The Guardian*, *London Review of Books*, and *Artforum*, and has curated exhibitions for Tate and Hayward Galleries. His awards and fellowships are not explicitly listed here, but his work has been widely exhibited and published internationally. He supervises doctoral students in creative writing and related fields, emphasizing interdisciplinary approaches to literature and art. Public engagement includes talks at institutions like the British Museum and Pompidou Centre, and appearances on BBC Radio 3 and RTE Radio. His work bridges academic critique with accessible creative writing, making complex themes engaging for broader audiences.
Andreas Geiger is a Professor and Head of the Department of Computer Science at the University of Tübingen, Germany. He leads the Autonomous Vision Group (AVG) within CyberValley and is a core faculty member of the Tübingen AI Center. His roles also include PI in the ML in Science Excellence Cluster and the CRC Robust Vision, as well as ELLIS Fellow and coordinator of the ELLIS PhD program. He specializes in machine learning models for computer vision, robotics, and autonomous systems, with applications in self-driving cars, VR/AR, and scientific document analysis. Educational background: While not explicitly detailed, his positions imply a Ph.D. in Computer Science or related field. His work spans interdisciplinary collaborations with institutions like ETH Zürich, Microsoft, and the University of Bonn. Research focuses on 3D scene understanding, Gaussian splatting, generative models, and reliable autonomous systems. Notable contributions include the KITTI dataset and foundational work in neural radiance fields. Awards include the Sage 10-Year Impact Award (2024), ERC Starting Grant (2019), and IEEE PAMI Young Researcher Award (2018). Key projects include the Scholar Inbox paper recommender platform, ReSim (reliable world simulation), and advancements in 3D scene generation (e.g., UrbanCAD, PrITTI). His lab maintains a strong focus on open-source tools and datasets, such as the CARLA Route Generator. Grants and funding include support from Vector Stiftung (MINT innovation program) and EU initiatives like the ML in Science Cluster. His team collaborates internationally, with recent work presented at CVPR, SIGGRAPH, and NeurIPS.
Verena Zimmermann serves as Assistant Professor (Tenure Track) for Security, Privacy and Society at ETH Zurich within the Department of Humanities, Social and Political Sciences. She leads the Security, Privacy and Society research group, focusing on human-centered approaches to safety, IT security, and privacy challenges in emerging technologies. Her academic foundation includes a PhD in Usable Security from TU Darmstadt, where her dissertation From the Quest to Replace Passwords towards Supporting Secure and Usable Password Creation earned dual awards from the German Association for Data Protection and Data Security (GDD) and the Ernst-Ludwigs-Hochschulgesellschaft. Zimmermann's research pioneers the shift from viewing humans as security vulnerabilities to recognizing them as integral solutions. Her work spans password security, phishing interventions, smart home privacy, and cybersecurity education, consistently applying human factors principles to design systems that align with natural user behavior. Current projects explore emotional dimensions of security engagement, quantum governance frameworks, and LLM-related privacy concerns through interdisciplinary lenses combining computer science, psychology, and safety science. Recent publications reveal strong thematic trends toward understanding user motivations in security behavior, developing personalized training through augmented reality and adaptive systems, and translating safety science principles to cybersecurity incident management. Her work increasingly addresses societal implications of emerging technologies like quantum computing and generative AI. Her distinguished recognitions include: GDD Dissertation Award for Usable Security research Ernst-Ludwigs-Hochschulgesellschaft Dissertation Award IANUS Award (2nd place) for Moving from a 'Human-as-Problem' to a 'Human-as-Solution' Cybersecurity Mindset Zimmermann actively mentors through ETH's Human-Centered Security and Privacy Lab while collaborating internationally with institutions including ATHENE (German National Center for Applied Cybersecurity), Abertay University's Cybersecurity Division, and the Safety Science Innovation Lab. Her research receives support from Swiss and European funding bodies focused on privacy-preserving technologies and organizational security behavior. At ETH Zurich, she directs the Security, Privacy and Society group which employs design thinking, LEGO Serious Play, and mixed-methods research to tackle real-world security challenges. The team partners with industry stakeholders to develop practical solutions for phishing resistance, smart home privacy, and cybersecurity education while maintaining strong ties to the Research Training Group 2050 Privacy and Trust for Mobile Users.
Pranav Anand is a Professor in the Department of Linguistics at the University of California, Santa Cruz (UCSC). He currently serves as the Faculty Director of the Humanities Institute at UCSC since July 2023. His research focuses on the interplay between context, interpretation, and grammatical perspective, particularly in areas like de re/de se contrasts, evaluative predication, and indexical shift. He has contributed to studies on narrative structures, evidential restrictions, and the syntax-semantics interface in sluicing. Dr. Anand has taught a variety of courses including Ling 119: Narratives , Ling 231: Semantics A , and special topics like Invented Languages: From Elvish to Esperanto . His work bridges theoretical linguistics with computational methods, evidenced by collaborations in projects such as the Santa Cruz sluicing dataset and analyses of political discourse in online commentary. His research has been published in journals like Linguistics and Philosophy , Language , and Discourse and Society , with a focus on semantics, pragmatics, and narrative linguistics. He has also contributed to computational linguistics initiatives, including the development of annotated corpora for sentiment analysis and argumentation studies. Dr. Anand's academic contributions span both theoretical exploration and applied computational linguistics, reflecting his interdisciplinary approach to understanding language structure and usage.
Amit Kumar is the Jaswinder and Tarwinder Chadha Chair Professor in the Department of Computer Science and Engineering at IIT Delhi. His research focuses on combinatorial optimization, online algorithms, and algorithmic fairness. He has taught courses such as Approximation Algorithms (COL 754), Design and Analysis of Algorithms (COL 351), and Numerical Analysis (COL 726). His work spans theoretical computer science with applications to clustering, scheduling, and fairness in evaluation processes. Research Interests Kumar's research emphasizes developing efficient algorithms for online and dynamic settings, particularly in constrained optimization and biased evaluation systems. He explores theoretical foundations of clustering, load balancing, and resource allocation, with recent contributions to fair food delivery systems and coreset constructions. Publications His recent work includes advancements in online convex paging (STOC 2025), consensus clustering (SODA 2025), and fairness-aware algorithms (AAAI 2024). Over 70 papers across top venues like STOC, SODA, and ICML reflect his expertise in algorithm design and analysis. Awards Best Paper Award at ISAAC 2023 for 'Clustering What Matters in Constrained Settings' Teaching & Mentorship Kumar instructs graduate and undergraduate courses in algorithms, data structures, and numerical methods. He advises students through these courses and collaborates with researchers on NSF-funded projects related to approximation algorithms and streaming systems.
Professor Alexander Ilin-Tomich serves as an Acting Professor at the Institute of Egyptology within the Department of History and Cultural Studies at the Free University of Berlin. His academic career spans multiple prestigious institutions including Johannes Gutenberg-Universität Mainz and the Russian Academy of Sciences. His educational background includes: 2022: Habilitation in Egyptology at Johannes Gutenberg-Universität Mainz with thesis "Egyptian name scarabs from the 12th to the 15th Dynasty: Geography and chronology of production" 2007-2011: Doctoral studies at Lomonosov University Moscow, earning "kandidat istoriceskich nauk" (equivalent to PhD) 2002-2007: Undergraduate studies in Ancient History (including Egyptology) at Lomonosov University Moscow Professor Ilin-Tomich specializes in Egyptian stelae, offering tables, scarabs, personal names, prosopography, and administration during the Middle Kingdom and Second Intermediate Period. His research combines philological, archaeological, and historical approaches to examine ancient Egyptian society, with particular focus on administrative structures, material culture, and regional variations. His work on scarab production and distribution has established him as a leading expert in this specialized field. His publication record demonstrates consistent focus on Middle Kingdom administration, with recent expansion into material analysis of Egyptian blue pigment and methodological approaches to studying small archaeological finds. He has developed significant digital resources including the open-access "Personen und Namen des Mittleren Reiches" database. Professor Ilin-Tomich has secured multiple competitive research grants: Fritz Thyssen Foundation project "Ancient Egyptian titles in official and familial contexts, 2055-1352 BC" (2021-2024) Fritz Thyssen Foundation project "Transformation and variability in the corpus of ancient Egyptian personal names 2055-1550 BC" (2017-2021) Alexander von Humboldt Foundation postdoctoral fellowship (2015-2017) Russian Foundation for the Humanities research grant (2013-2015) He actively contributes to the academic community through editorial work, including co-editing the 2023 Festschrift "Schöne Denkmäler sind entstanden. Studien zu Ehren von Ursula Verhoeven," and has established himself as a key researcher in Middle Kingdom studies through his monographs and numerous journal articles.
Navid Azizan is the Alfred H. (1929) and Jean M. Hayes Career Development Assistant Professor at Massachusetts Institute of Technology (MIT), holding dual appointments in the Department of Mechanical Engineering (in Control, Instrumentation & Robotics) and the Schwarzman College of Computing's Institute for Data, Systems & Society (IDSS). He is also a Principal Investigator in the Laboratory for Information & Decision Systems (LIDS), and a faculty member of the MIT Statistics and Data Science Center, the Center for Computational Science and Engineering, and the Operations Research Center. Dr. Azizan received his PhD in Computing and Mathematical Sciences from the California Institute of Technology (Caltech) in 2020, his MSc in Electrical Engineering from the University of Southern California in 2015, and his BSc in Electrical Engineering with a minor in Physics from Sharif University of Technology in 2013. Prior to joining MIT, he completed a postdoc at Stanford University's Autonomous Systems Laboratory and was a research scientist intern at Google DeepMind. His research spans the intersection of machine learning, systems and control, mathematical optimization, and network science. Dr. Azizan's work focuses on developing principled learning and optimization algorithms for reliable intelligent systems, with applications to autonomy and sociotechnical systems. His research has significant implications for creating trustworthy AI systems that can operate effectively in complex, uncertain environments. Dr. Azizan's recent publications demonstrate a strong focus on uncertainty quantification, reliable AI systems, constrained optimization, and control-oriented learning. His work bridges theoretical foundations with practical applications, particularly in autonomous systems where safety and reliability are paramount. His research group has made notable contributions to areas including neural network verification, multi-agent reinforcement learning, and adaptive inference techniques for large language models, with several papers featured on MIT News and selected for oral presentations at top conferences. Alfred H. (1929) and Jean M. Hayes Career Development Professorship (2025-present) Frank E. Perkins Award for Excellence in Graduate Advising (2025) List of Outstanding Academic Leaders in Data from the CDO Magazine (2024, 2023) Amazon Science Hub Research Award (2023) Outstanding UROP Faculty Mentor (2023) Esther and Harold E. Edgerton (1927) Career Development Chair (2022-2025) Information Theory and Applications (ITA) Gold Graduation Award (2020) Dr. Azizan has been recognized for his excellence in graduate advising, receiving the Frank E. Perkins Award for Excellence in Graduate Advising in 2025. During the pandemic, he founded and co-organized the 'Control meets Learning' virtual seminar series, connecting researchers across disciplines. His work has attracted significant research funding from industry partners including Google, Amazon, and MathWorks, supporting both fundamental research and practical applications in reliable intelligent systems. The Azizan Lab at MIT brings together researchers from mechanical engineering, computer science, and applied mathematics to tackle challenges at the intersection of learning and control. The lab emphasizes both theoretical foundations and practical implementations, with a particular focus on developing algorithms that provide guarantees of performance and safety. Current research directions include uncertainty quantification in AI systems, constrained optimization for neural networks, and control-oriented learning for autonomous systems, with applications spanning robotics, transportation, and complex sociotechnical systems.
Pamela J. Hinds is the Rodney H. Adams Professor and Fortinet Founders Chair in Stanford University's School of Engineering, holding a joint appointment in the Department of Management Science and Engineering. She co-directs the Center on Work, Technology, and Organization and serves on the Director's Council for the Hasso Plattner Institute of Design. Her research focuses on technology's impact on teams, collaboration, and innovation in global and cross-cultural contexts. She earned her Ph.D. in Organizational Science and Management from Carnegie Mellon University (1997). Research Interests: Dr. Hinds explores cross-boundary work teams, particularly those spanning national borders, examining cultural dynamics, language barriers, and site visits' role in knowledge sharing. She investigates human-robot interaction in workplaces and emerging technologies' effects on work practices, including AI, 3D printing, and open innovation systems. Her work bridges organizational behavior, human-computer interaction, and global work dynamics. Awards & Recognition: Lasting Impact Award (2018) Senior Editor of Organization Science Co-editor of Distributed Work (MIT Press) Advising & Leadership: As department chair, Hinds shapes educational and research agendas. Her grants include NSF-funded studies on digital technologies in agriculture and crowd-based innovation. She advises initiatives at the intersection of technology, work design, and global collaboration. Labs & Teams: Co-leads the Center on Work, Technology, and Organization, fostering interdisciplinary research on modern work environments. Engages in Stanford's Design School (d.school) to integrate human-centered design principles into workplace innovation.
Fei-Fei Li is the Sequoia Capital Professor in Computer Science at Stanford University and Founding Co-Director of the Stanford Institute for Human-Centered AI (HAI). She holds courtesy appointments in the Graduate School of Business and is a Senior Fellow at HAI. Her work bridges AI research with interdisciplinary applications in healthcare, robotics, and policy. Dr. Li pioneered the ImageNet dataset, instrumental in the AI revolution, and co-founded World Labs to advance spatial intelligence and generative AI. Education: B.A. in Physics, Princeton University (1999) Ph.D. in Electrical Engineering, Caltech (2005) Doctorate (Honorary), Harvey Mudd College (2022) Research Interests: AI ethics, computer vision, robotic learning, healthcare applications, and human-AI collaboration. Her teams developed frameworks like MOMA for activity recognition and BEHAVIOR for embodied AI benchmarks. She advocates for diversity in tech and co-founded AI4All to mentor underrepresented students. Key Contributions: ImageNet and ImageNet Challenge Stanford Vision and Learning Lab (SVL) Policy advisory roles for U.S. Senate, UN Secretary-General, and California Governor Labs & Initiatives: Leads the People, AI & Robots Group (PAIR), Partnership in AI-Assisted Care (PAC), and the Human-Centered AI Institute. Her work emphasizes ethical AI deployment and societal impact. Awards: VinFuture Prize (2024), IEEE Fellow, National Academy memberships (Engineering, Medicine, Arts & Sciences), and recognition as one of Time’s AI100 Influencers.
Dr. Damien Charrieras is an Associate Professor at the School of Creative Media , City University of Hong Kong, where he serves as Program Leader for the Master of Art in Creative Media and deputy program leader for the PhD in Creative Media. His work bridges cultural studies, new media theory, and the intersection of financial technologies with artistic practices through the ACIM Laboratory for Interventions in Speculative Finance . Doctoral research on digital artists' trajectories in Montreal FRQSC Postdoctoral Fellowship at McGill University Research spans game engine design , datafication of creativity , blockchain in art , and post-anthropocentric creative processes . With over HK$3.14M in grants as Principal Investigator, he explores situated digital creativity in urban contexts, critical worldbuilding pedagogy , and the mediation of technical systems in cultural production. His publications in Cities , Organized Sound , and Human Relations analyze the reconfiguration of artistic practices through software infrastructures and automation paradigms. Scientific awards include: FRQSC Postdoctoral Fellowship
Joy Arulraj is an Associate Professor in the School of Computer Science within the College of Computing at Georgia Institute of Technology. His research focuses on data systems, machine learning, and database systems, with a particular emphasis on video analytics and adaptive query processing. He leads the Data Systems and Analytics Group and is developing the EVA AI-Relational Data System. Dr. Arulraj's research interests span data systems, machine learning, database systems, video analytics, and adaptive query processing. His work centers on developing systems that efficiently process complex queries, particularly for video analytics and machine learning workloads. He has made significant contributions to GPU database systems, non-volatile memory database management, and adaptive query processing techniques. His research often bridges the gap between theoretical database principles and practical implementations for modern hardware architectures. His recent publications show a strong trend toward video analytics systems, adaptive query processing for machine learning workloads, and GPU-accelerated database systems. The EVA system represents a major focus of his recent work, providing end-to-end exploratory video analytics capabilities. His research also addresses fundamental database concepts like buffer management, query optimization, and storage management, adapting these principles for modern hardware and application requirements. Dr. Arulraj has advised numerous graduate students including Pramod Chunduri, Gaurav Tarkok Kakkar, Jiashen Cao, and Sayan Sinha. His graduated students have gone on to work at companies like ServiceNow, Meta Research, and the Korean Army. He actively teaches database system courses at Georgia Tech, including Database System Implementation (CS 4420/6422) and Advanced Database System Implementation (CS 4423/6423), where students build database systems from scratch using C++ and the BuzzDB framework. He maintains an active research program with consistent publication output across top database and systems conferences. His work spans from theoretical database principles to practical system implementations, with a recent emphasis on video analytics, machine learning integration with database systems, and leveraging modern hardware like GPUs and non-volatile memory for database applications.
