Lutz Schubert is a researcher at the Institute of Computer Science , University of Cologne. He focuses on efficient distributed and parallel execution environments for heterogeneous systems, notably the MyThOS operating system in collaboration with Brandenburg University of Technology, Cottbus-Senftenberg. His interdisciplinary work bridges computer science and digital archaeology , addressing modeling of non-deterministic events from sparse excavation data and exploring human behavior constraints in archaeological contexts. Research Interests Design of modular, scalable operating systems for distributed systems Optimization of execution environments for heterogeneous hardware Application of complex systems modeling to digital archaeology Statistical and probabilistic methods for archaeological interpretation Autonomic resource distribution and adaptation in computing Publication Trends : His work spans operating systems , parallel computing , and digital humanities , with recent emphasis on probabilistic reasoning in archaeology and adaptive OS design for multicore architectures. Labs & Collaborations : He collaborates with Brandenburg University of Technology on MyThOS and leads research in computational archaeology as chair of Computer Applications and Quantitative Methods in Archaeology (CAA) , Germany.
Steven Jackson is a Professor of Information Science and Science and Technology Studies at Cornell University's Bowers College of Computing and Information Science, with additional graduate field appointments in Communication and Public Affairs. Since July 2023, he has served as Vice-Provost for Academic Innovation at Cornell, and previously held leadership positions as Chair of Information Science and Dean of William Keeton House. His work bridges academic research with significant institutional leadership in higher education innovation. Dr. Jackson's research focuses on critical intersections of technology, society, and the environment, with three primary strands: technology ethics, law and policy; maintenance, repair and sustainability; and technology, inequality and global development. His work draws from American pragmatism, political economy, and science and technology studies, integrating methods from sociology, anthropology, philosophy, and media studies. He is particularly interested in how computing practices meet social and material worlds, with implications for infrastructure, collaboration, sustainability, and cultural practice. His recent publications reveal a strong emphasis on repair as both theoretical concept and practical methodology, exploring 'ordinary hope' as a framework for technological engagement and examining unmaking as a necessary counterpart to design. The research spans diverse geographical contexts from the global North to South, addressing caste dynamics in computing, digital authoritarianism, and infrastructure challenges in developing contexts. Dr. Jackson has received significant recognition including an NSF CAREER award and more than twenty paper awards at leading computing and information science venues. His research has been supported by major organizations including the U.S. National Science Foundation, Social Science Research Council, Ford Foundation, Sloan Foundation, World Bank, Intel Research, Atkinson Center for Sustainability, and the Canadian Social Science and Humanities Research Council. As an advisor, Dr. Jackson has mentored numerous graduate students who have gone on to prominent positions at institutions worldwide. He currently advises Jen Liu, Amy Cheatle, Daniel Mwesigwa, Johan Michalove, and Ritik Batra, while his former students include Palashi Vaghela (Assistant Professor at Simon Fraser University), Samir Passi (Responsible AI Researcher at Microsoft), Maggie Jack (Assistant Professor at NYU), and Ranjit Singh (Senior Researcher at Data and Society). Dr. Jackson convenes the Computing On Earth Lab, an experimental collaboration bringing together social scientists, humanists, artists, and engineers to rethink the material and planetary foundations of computing. The lab reflects his commitment to interdisciplinary approaches that address computing's environmental impacts and sustainability challenges.
Roberto Martin-Martin is an Assistant Professor of Computer Science at the University of Texas at Austin, where he leads the Robot Interactive Intelligence (RobIN) Lab. His research bridges robotics, computer vision, and machine learning to enable robots to operate autonomously in human-centric environments like homes and offices. Previously, he was a Postdoctoral Scholar at the Stanford Vision and Learning Lab working with Fei-Fei Li and Silvio Savarese, and an AI Researcher at Salesforce AI. Education: Ph.D. and M.Sc. in Robotics from Technische Universität Berlin (TUB), advised by Professor Oliver Brock B.Sc. from Universidad Politécnica de Madrid Dr. Martin-Martin's research focuses on developing AI algorithms that combine reinforcement learning and imitation learning with advanced planning and control to address core challenges in robot perception. His work spans mobile and whole-body manipulation, dexterous and contact-rich interactions, and long-horizon tasks in unstructured environments. He takes inspiration from human cognition through psychology and cognitive science to develop solutions for skills ranging from simple pick-and-place operations to complex tasks like cooking and furniture assembly. His recent publications demonstrate a strong trend toward enabling robots to learn from human demonstrations, particularly through video, and to safely adapt these demonstrations to their own morphology. There's significant emphasis on mobile manipulation, bimanual tasks, and developing hardware that supports robust robot learning through trial and error. His work shows increasing integration of large language models and vision-language models to enhance robot understanding and task execution. Scientific Awards: RSS Pioneer (2020) Winner of Amazon Picking Challenge (2015) RSS Best Systems Paper Award (2016) ICRA Best Paper Award IROS Best Mechanism Award Amazon Faculty Award AAAI Young Faculty IJCAI Early Faculty Nominated for Best Paper at IROS (2014, 2017) Dr. Martin-Martin advises PhD students including Arpit Bahety, who is working on mobile manipulation and learning. He serves as Chair of the IEEE Technical Committee on Mobile Manipulation and is a co-founder of QueerInRobotics. His research is supported by industry partnerships and academic funding sources that enable his lab to develop both hardware and software innovations in robotics. He directs the Robot Interactive Intelligence (RobIN) Lab at UT Austin, which takes a holistic approach to robot intelligence, developing both the hardware (like the BaRiFlex gripper) and software frameworks necessary for robots to learn from interaction. The lab's research addresses the full pipeline from perception to action, with particular emphasis on learning from human demonstrations, safe exploration, and adapting to novel objects and environments.
Rachit Agarwal is an Associate Professor in the Department of Computer Science at Cornell University, with research focusing on systems, networking, and theoretical problems arising in practical systems. He leads a research group working on resource disaggregation, host architecture, secure cloud storage, and datacenter design. PhD in Computer Science, Cornell University Undergraduate, IIT Kanpur His research spans three major directions: Resource Disaggregation (with $3M NSF and Google awards), Host Architecture (exploring terabit interconnects), and PANCAKE (secure oblivious cloud storage with $1M NSF award). He also contributed to foundational work in Near-optimal Datacenter Design and Data Plane Monitoring . Awards include the Sloan Fellowship, NSF CAREER, IRTF Applied Networking Prize, and multiple best paper awards. His recent publications focus on host network architecture, congestion control, oblivious data access mechanisms, and secure cloud storage systems. He has advised multiple Ph.D. and postdoctoral researchers who now hold faculty positions at leading institutions. Sloan Research Fellowship NSF CAREER award Kavli Fellowship IRTF Applied Networking Research Prize SIGCOMM Best Student Paper Award Usenix Security Distinguished Paper Award Tau Beta Pi Professor of the Year 2025 Rachit has advised numerous students including current Cornell advisees like Midhul Vuppalapati, Shreyas Kharbanda, and Omar Eqbal. Former advisees include Saksham Agarwal (UIUC), Qizhe Cai (UVA), and Mina Tahmasbi Arashloo (University of Waterloo). His research is supported by large NSF grants and industry awards, with deployments in real-world systems and open-source contributions.
Gianluca Iaccarino is a Professor of Mechanical Engineering at Stanford University and the Robert Bosch Chairholder. He serves as Director of the PSAAP Center and leads large-scale computational research initiatives in uncertainty quantification, exascale computing, and multiphysics simulations. His academic journey includes a PhD in Mechanical Engineering from Politecnico di Bari (2005), postdoctoral work at Stanford's Center for Turbulence Research, and progression from Research Engineer to full Professor. Education : PhD (Politecnico di Bari), MS/BS in Aeronautical Engineering (University of Naples) Research : Computational engineering, turbulence modeling, uncertainty quantification, biomedical fluid dynamics, and exascale-ready algorithms Publications : 15+ recent articles focus on turbulence modeling, data-driven simulations, and uncertainty quantification across diverse applications in aerospace, biomedical, and energy systems Awards : PECASE (2010), APS Fellow (2019), multiple best paper awards (AIAA, ASME), Terman Fellow (2007) Students : Advises doctoral and master's students in mechanical engineering and computational methods Leadership : Director of PSAAP Center (2014-present), Chair of Mechanical Engineering Department (2024-present)
Mark Riedl is a Professor in the Georgia Tech School of Interactive Computing and Associate Director of the Georgia Tech Machine Learning Center (ML@GT). His research focuses on human-centered artificial intelligence, emphasizing the development of AI technologies that naturally interact with humans. Key areas include story understanding/generation, computational creativity, explainable AI, and ensuring AI safety. He holds affiliations with the GVU Center, Institute for People and Technology (IPaT), and Institute for Robotics and Intelligent Machines (IRIM). His work is supported by NSF, DARPA, ONR, and industry partners like Google and Meta. Notable awards include the DARPA Young Faculty Award and NSF CAREER Award, plus three Pulitzer Prizes (collaborative with Roko M. Bask). Riedl's recent projects include STORY2GAME (AI-driven game design) and ethical AI frameworks addressing transparency and accountability. His research bridges theoretical advancements with practical applications in education, healthcare, and creative industries. Research interests span AI ethics, narrative systems, and AI's societal impact. He explores how AI can be made more transparent through explainable mechanisms while maintaining creativity and safety. Collaborations with Roko Bask on futuristic culinary trends have produced influential works. His labs and teams focus on interdisciplinary approaches, combining computer science with social sciences to shape responsible AI development. Key grants and projects include NSF-funded initiatives on AI in education and DARPA-supported work on AI safety. His contributions to explainable AI challenge traditional XAI paradigms, advocating for human-centered approaches that prioritize user understanding and ethical implications. Current efforts emphasize adapting LLMs for world modeling and enhancing RL agents with causal reasoning capabilities.
Shreyas Sen is the Elmore Associate Professor of Electrical and Computer Engineering at Purdue University, jointly affiliated with the School of Biomedical Engineering. He directs the Center for Internet of Bodies (C-IoB) and leads the SPARC Lab, focusing on circuits/systems for secure, energy-efficient body-centric communication and biomedical applications. Education: B.E. (Jadavpur University, 2006), M.S. & Ph.D. (Georgia Tech, 2009-2011). His research spans Human Body Communication (HBC), hardware security, IoT/IoB systems, and low-power sensing. Notable innovations include Electro-Quasistatic HBC (EQS-HBC) technology, which enables covert body-wire communication with 100x lower energy than conventional methods. Research Themes: Secure communication for medical wearables Physical layer security in IoT Ultra-low-power biosensors Side-channel attack mitigation in cryptographic ICs Publications: Over 200 papers in top venues (ISSCC, DAC, CICC, HOST) with focus on HBC systems, electromagnetic security, and biomedical circuits. Recent work explores EQS-HBC privacy properties (Nature Scientific Reports, 2019) and 350x current-domain signature attenuation for AES security (ISSCC 2020). Awards: NSF CAREER Award (2020) AFOSR Young Investigator (2016) MIT TR35 India (2018) 9 Best Paper Awards Intel Outstanding Researcher (2020) He advises over 20 students and leads industry collaborations through Ixana Inc. (founded 2020), commercializing EQS-HBC technology. Current efforts include EQS-based authentication systems and radiation dosimetry wearables.
Prof. Matthias Nießner is a Professor at the Technical University of Munich, leading the Visual Computing Lab. His research intersects computer graphics, vision, and AI, focusing on 3D reconstruction, semantic understanding, and AI-driven video synthesis. He holds a PhD from the University of Erlangen-Nuremberg (2013) and was a Visiting Assistant Professor at Stanford University (2013–2017). Notable awards include the ERC Starting Grant (2018), Nvidia Professorship Award, and Eurographics Young Researcher Award (2019). His work has been featured in mainstream media and led to startups like Synthesia Inc. Research spans Gaussian splatting, neural radiance fields, and generative AI for 3D avatars. Over 150 publications include SIGGRAPH, CVPR, and ECCV, with best paper awards. Projects like Face2Face and ScanNet have driven innovation in facial reenactment and 3D scene datasets. Education: PhD in Computer Science, University of Erlangen-Nuremberg (2013) Diploma in Computer Science, University of Erlangen-Nuremberg (2010) Research Interests: 3D digitization, neural rendering, generative AI, non-rigid reconstruction, and applications in AR/VR. Awards: ERC Starting Grant (2018) Nvidia Professorship Award (2018) Google Faculty Award (2018) SIGGRAPH Best Emerging Tech Award (2016) Grants: Over €1.5M from ERC and industry partnerships. Labs/Teams: Visual Computing Lab at TUM and Synthesia Inc. (co-founder). Key projects include ScanNet (large 3D indoor dataset), Face2Face (real-time facial reenactment), and Gaussian-based 3D avatars. Current work focuses on diffusion models, neural radiance fields, and AI-generated media detection.
Anette Mikes is an Associate Professor of Accounting at the University of Oxford’s Saïd Business School and a Hertford College Fellow. She specializes in risk management, corporate governance, and sustainability, with a focus on the intersection of ethics and organizational control systems. Her research explores how risk frameworks shape corporate decision-making, particularly in climate change and decarbonization contexts. Education: PhD in Accounting from the London School of Economics (2005) Pre-doctoral work in the City of London (2006–2007) studying Chief Risk Officer roles Research Interests: Behavioral approaches to risk management Management control systems for sustainability Ethics in corporate governance Decarbonization strategies in heavy industries Her 2012 Harvard Business Review article (with Robert Kaplan) on risk frameworks remains influential, while her documentary on the Kursk submarine disaster highlights crisis management failures. Awards: 2025 Honorary Doctorate from Uppsala University 2017 ACA Prize for Risk Management Contributions 2014 Global Risk Forum Film Award Key Contributions: Co-developed Harvard’s Risk Management executive program Leads research on ‘Values at Risk’ and corporate purpose Published widely on climate risk governance and ethical leadership Her recent work emphasizes decarbonization strategies and moral accountability in business, bridging accounting practices with environmental and ethical imperatives.
Gary Fedder is the Howard M. Wilkoff Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with courtesy appointments in Biomedical Engineering, Mechanical Engineering, and Robotics. He serves as Faculty Director of the Manufacturing Futures Institute (MFI) and previously held roles such as Vice Provost for Research and Interim CEO of the Advanced Robotics for Manufacturing (ARM) Institute. Fedder’s research focuses on MEMS, advanced manufacturing, and implantable microsystems. He earned his B.S., M.S., and Ph.D. in EECS from MIT and UC Berkeley, respectively. Education: Ph.D., Electrical Engineering and Computer Science, UC Berkeley (1994) M.S., Electrical Engineering and Computer Science, MIT (1984) B.S., Electrical Engineering and Computer Science, MIT (1982) Research Interests: Microelectromechanical systems (MEMS), digital twins, aerosol jet printing, stretchable electronics, and manufacturing innovation. His work integrates MEMS with CMOS processes, emphasizing low-cost, high-performance systems. Key Contributions: Co-founded the ARM Institute; developed MEMS-based sensors and actuators; pioneered methods for manufacturing innovation through projects like America Makes. His research spans over 300 publications and 21 patents. Awards: IEEE Fellow (2007), Ross Tucker Award (1993), NSF CAREER Award (1996), and leadership roles in Manufacturing USA initiatives. Leadership & Outreach: Directed the Institute for Complex Engineered Systems and led national initiatives to advance U.S. manufacturing competitiveness. Active in editorial roles for journals like IoP Journal of Micromechanics .
Anthony Rowe is the Siewiorek and Walker Family Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU) and a Chief Scientist at Bosch Research. His primary affiliation is with the CyLab and the Wireless, Sensing and Embedded Systems (WiSE Lab) at CMU. He specializes in networked embedded systems, sensor networks, and extended reality (XR) technologies. His research emphasizes energy-efficient sensing, real-time localization, and XR integration with physical systems. Research Focus: His work spans XR systems (e.g., AR/VR edge networking in ARENA), mmWave radar for sensing (e.g., tire wear monitoring via Osprey), distributed edge computing (Silverline), and low-power wide-area networking (OpenChirp). Recent efforts include AI-integrated XR platforms (XaiR) and radar tomography (DART). Grants & Projects: Leads the CONIX Research Center ($27.5M NSF/DARPA grant), Bosch-funded edge computing projects, and DOE initiatives on microgrids. Notable projects include ARENA (XR edge architecture), GridBallast (smart grid control), and rural microgrid deployments in Haiti. Awards: Best Student Paper (ISMAR 2024), Best Paper (IPSN 2020), and the Steven J. Fenves Research Award (2015). Recognized for innovations in localization (MobiCom 2021), radar (ICRA 2023), and energy systems (BuildSys 2010). Teaching: Teaches courses on embedded systems (18-349/18-449), real-time systems, and mixed reality (18-453). Courses emphasize hands-on design and real-world applications. Labs & Teams: Directs the WiSE Lab, collaborating with Bosch Research and industry partners. The lab develops open-source frameworks like ARENA and OpenChirp, and contributes to standards for edge computing and sensing.
Tomas Palacios is a Professor of Electrical Engineering at the Massachusetts Institute of Technology (MIT) , where he directs the Center for Graphene Devices and 2D Systems and leads the Microsystems Technology Laboratories (MTL). His research focuses on pushing the boundaries of microelectronics through novel semiconductor materials and device architectures, including Gallium Nitride (GaN) and 2D materials like graphene and molybdenum disulfide (MoS2). Professor, MIT Electrical Engineering and Computer Science Director, MIT Center for Graphene Devices and 2D Systems Clarence J. LeBel Professor, MIT Faculty Director, Northeast Microelectronics Internship Program (NMIP) Research Interests span multiple cutting-edge domains: High-frequency electronics (>300 GHz) for 6G and quantum applications High-voltage power devices (600V–10kV) for energy conversion Post-silicon logic devices using 2D materials High-temperature electronics (e.g., Venus rover applications) Distributed neural networks on large-area 2D materials Graphene-based biosensors and chemical detection systems Scientific Contributions include: Double recipient of the IEEE George Smith Award for groundbreaking GaN transistor work Co-invented first MoS2 electronic circuits Developed world’s first Wi-Fi-to-electricity conversion antenna Led MIT’s Microsystems Technology Laboratories since 2021 Advising Philosophy emphasizes cross-layer expertise, with students gaining experience from materials synthesis to system-level prototyping. His lab has incubated startups like Vertical Horizons , focused on GaN power devices for AI and EVs.
Anca Dragan is an Associate Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, where she runs the InterACT Lab focused on algorithms for human-AI and human-robot interaction. Currently on leave from Berkeley, she leads AI Safety and Alignment at Google DeepMind, overseeing safety for Gemini models and preparing for future advancements. Dragan has been a co-PI of the Center for Human-Compatible AI and served on the steering committee for the Berkeley AI Research (BAIR) Lab. B.Sc. in Computer Science from Jacobs University Bremen, Germany Ph.D. from Carnegie Mellon University Dr. Dragan's research focuses on enabling AI agents to work effectively with, around, and in support of people. Her work bridges robotics, machine learning, and game theory to create systems that better understand human preferences and coordinate with users. Key areas include AI alignment (ensuring AI does what people actually want), learning reward functions from diverse human feedback forms, and developing algorithms for human-AI collaboration across domains like autonomous vehicles, brain-machine interfaces, and recommender systems. Her research emphasizes maintaining uncertainty about human preferences and accounting for the plurality of human values. Dr. Dragan's recent publications reveal a strong focus on addressing fundamental challenges in AI safety and alignment. Her work spans theoretical foundations of reward learning, practical implementations for human-AI coordination, and critical examinations of limitations in current approaches. There's a clear trajectory toward more robust, safe, and value-aligned AI systems that can handle complex human preferences while avoiding both present-day harms and potential catastrophic risks. IEEE RAS Early Academic Career Award in Robotics and Automation (2021) McEntyre Award for Excellence in Teaching (2020) PECASE (Presidential Early Career Award for Science and Engineering) (2019) Sloan Fellowship (2018) NSF CAREER Award (2017) Okawa Foundation Award (2017) MIT Tech Review 35 Innovators Under 35 (2017) Multiple best paper awards at top robotics and AI conferences Dr. Dragan has mentored numerous successful students who have gone on to faculty positions at MIT, Stanford, CMU, and Princeton, as well as industry roles at DeepMind, Waymo, and Meta. Her advising philosophy emphasizes both technical rigor and consideration of broader societal impacts. She has secured significant research funding including NSF CAREER, ONR Young Investigator, and Okawa Foundation awards, supporting work on human-AI interaction and alignment. Dragan has also consulted for Waymo for six years, helping develop roadmaps for deploying increasingly learning-based safety-critical systems. Dr. Dragan leads the InterACT Lab at UC Berkeley, which has produced influential work on Cooperative Inverse Reinforcement Learning, Inverse Reward Design, and other foundational concepts in human-AI interaction. The lab's research has significantly shaped the field of AI alignment, with applications spanning autonomous vehicles that coordinate with human drivers, brain-machine interfaces that adapt to user needs, and language models that better understand human preferences. Current work focuses on scaling safety approaches as AI capabilities advance, ensuring alignment keeps pace with technological progress.
Haijun Xia is an Assistant Professor at the University of California, San Diego (UCSD), where he directs the Foundation Interface Lab and contributes to the Cognitive Science and Design Lab. His work focuses on Human-Computer Interaction (HCI) and Human-AI Collaboration , emphasizing the development of dynamic, malleable interfaces that integrate human cognition with intelligent systems to enhance thinking and working paradigms. Education: Bachelor's, Tsinghua University Master's and PhD, University of Toronto His research spans generative AI , interface design , and creative collaboration , with applications in data visualization, programming, and scholarly work. He advocates for treating information as a malleable material that can be flexibly manipulated by users and AI agents. Recent publications highlight advancements in: 2025 CHI Conference - Generative user interfaces, malleable overview-detail designs, and compositional structures for human-AI co-creation 2024 CHI Conference - Structured design space exploration with LLMs, ASCII diagram analysis, and adaptive presentation systems 2023 CHI/UIST Conferences - Data particle visualization, contextual logging tools, and metaphor generation for science communication Scientific recognitions include: Multiple Best Paper Awards and Honorable Mentions at CHI and UIST Hellman Fellowship and grants from NSF , Microsoft , Google , Meta , Apple , and Adobe He actively recruits undergraduate and graduate interns and has an upcoming postdoc position in early 2025 for researchers interested in foundational interface development.
Mary Bucholtz is a Professor in the Department of Linguistics at the University of California, Santa Barbara (UCSB). She holds affiliations with multiple departments including Anthropology, Feminist Studies, Spanish and Portuguese, the Gevirtz Graduate School of Education, Comparative Literature, and Latin American and Iberian Studies. Her research integrates sociocultural linguistics with anthropological, gender, and social justice frameworks. Education: PhD in Linguistics, University of California, Berkeley (1997) Bucholtz's work examines how language shapes and is shaped by social identities, particularly among youth, through dimensions like race, gender, and cultural practices. She emphasizes community-centered research , linguistic activism , and interdisciplinary methodologies to address systemic inequalities. Recent publications explore affective agency in Latinx youth, educational equity, and antiracist linguistics. Her collaborative projects often involve partnerships with educational institutions and youth communities in California, focusing on translanguaging , Black language justice , and raciolinguistic ideologies . Grants from the National Science Foundation, Spencer Foundation, and Wenner-Gren Foundation support her research. She co-edited the open-access volumes Decolonizing Linguistics and Inclusion in Linguistics (Oxford University Press, 2024), alongside authoring White Kids: Language, Race, and Styles of Youth Identity (Cambridge, 2011) and Talking College: Making Space for Black Language Practices in Higher Education (Teachers College Press, 2022).
