Alex Lombardi is an Assistant Professor of Computer Science at Princeton University, specializing in cryptography and theoretical computer science. His work explores cryptographic proof systems, post-quantum security, and quantum cryptography. Princeton University (Current) Simons-Berkeley Postdoctoral Fellow (Former) MIT (Graduate Training) Visiting Scientist, Cryptography 10 Years Later Program (2025) Education: PhD in Computer Science from MIT (advised by Vinod Vaikuntanathan) Master's Thesis on Provable Instantiations of Correlation Intractability and the Fiat-Shamir Heuristic Dr. Lombardi's research spans foundational cryptography, with a focus on indistinguishability obfuscation, worst-case assumptions, and quantum cryptographic protocols. His work on SNARGs and PPAD hardness has advanced cryptographic proof systems, while his recent projects address quantum verification and post-quantum security. He encourages prospective cryptography students to apply to Princeton's PhD program. His publications highlight advancements in LWE-based cryptography, quantum protocols, and complexity-theoretic foundations. Key themes include secure computation, hash function design, and cryptographic reductions under quantum assumptions. Scientific Awards: Simons-Berkeley Postdoctoral Fellowship Dr. Lombardi serves on program committees for STOC 2025, EUROCRYPT 2025, and other conferences. He has taught courses like COS 433/533 (Cryptography) and COS 533 (Advanced Cryptography) at Princeton.
Nedim Pervan is a Full Professor at the Faculty of Mechanical Engineering, University of Sarajevo, Bosnia and Herzegovina. His academic position focuses on mechanical engineering with emphasis on product design, structural analysis, and biomechanical applications. He maintains an active research profile with numerous publications and collaborations across various engineering disciplines, with office hours every workday from 09:00 to 10:00 in room 314. Professor Pervan's research interests span multiple domains of mechanical engineering. He has made significant contributions to additive manufacturing, particularly in polymer gear production and analysis. His work explores mechanical properties, failure mechanisms, and service life of polymer gears manufactured through additive processes. Additionally, he has conducted extensive research on external fixation devices used in orthopedic treatments, analyzing their biomechanical characteristics and structural stability under various loading conditions. His expertise extends to finite element analysis, structural optimization, and the application of 3D scanning technologies within Industry 4.0 contexts. His research demonstrates a strong connection between theoretical engineering principles and practical applications across automotive, medical devices, and manufacturing industries. His recent publication record reveals a strong trend toward interdisciplinary research bridging mechanical engineering with biomedical applications and advanced manufacturing technologies. A significant portion of his work focuses on polymer gears and additive manufacturing, examining material properties and performance characteristics. Another substantial research stream involves biomechanical engineering, particularly the analysis of external fixation devices. His publications demonstrate a methodological approach combining experimental testing with finite element analysis. More recently, his research has expanded into 3D scanning applications in manufacturing and the electrification of transportation systems in Bosnia and Herzegovina. Professor Pervan has been involved in numerous research projects that have advanced the capabilities of the Faculty of Mechanical Engineering. These include the "Integrated Intelligent CAD System for Interactive Design, Analysis and Prototyping of Compression and Torsion Springs" (2022), "Opremanje Laboratorije za razvoj i dizajn proizvoda" (2020), and "Modernizacija Laboratorije za ispitivanje mašinskih konstrukcija" (2019-2020). These projects have focused on developing advanced laboratory facilities, intelligent CAD systems, and equipment for mechanical design and analysis, with several specifically targeting 3D scanning technology implementation. His collaborative work extends across multiple research teams within the Department of Mechanical Constructions at the University of Sarajevo. He frequently collaborates with researchers including Adis Muminović, Elmedin Mešić, and Muamer Delić on projects related to additive manufacturing, biomechanical engineering, and structural analysis. His research group appears actively involved in both theoretical and applied engineering research with practical industrial and medical applications, contributing significantly to Bosnia and Herzegovina's engineering research landscape.
Prof. Dr. Armido Studer is a Full Professor of Organic Chemistry at the Institute of Organic Chemistry, Faculty of Mathematics and Natural Sciences, University of Münster (WWU Münster), Germany. He has been serving as a Full Professor (W3) since November 2009, following his appointment as a Full Professor (C4) in 2004. Studer also serves as the Spokesman of the International Research Training Group IRTG 2678 'Functional π-Systems: Activation, Interaction and Application (pi-Sys)' since 2021 and previously led the Collaborative Research Center SFB 858 'Synergetic Effects in Chemistry - From Additivity towards Cooperativity' from 2010 to 2021. Studer received his education at ETH Zürich, where he completed his diploma thesis and doctoral studies under Prof. Dr. D. Seebach. He conducted postdoctoral research at the University of Pittsburgh with Prof. Dr. D. P. Curran before returning to ETH Zürich for his habilitation. His academic career includes positions as Associate Professor at Philipps-Universität Marburg (2000-2004) and subsequent professorships at WWU Münster. Professor Studer's research focuses on radical chemistry, particularly in the development of new synthetic methods using radical intermediates. His work spans free radical chemistry, electron catalysis, and the application of nitroxides in organic synthesis. Recent research directions include 'Radical Chemistry with the Hydrogen Atom Through Water Activation (H-dot)' and 'The Electron as a Catalyst: e-cat', both funded by ERC Advanced Grants. His group has made significant contributions to C-H functionalization, skeletal editing of heterocycles, and cooperative catalysis involving photoredox and N-heterocyclic carbene systems. The research has applications in pharmaceutical chemistry, materials science, and sustainable chemical synthesis. Studer's publication record shows a strong focus on heterocyclic chemistry, radical reactions, and catalytic methodologies. His recent work demonstrates expertise in meta-selective functionalization of heteroarenes, skeletal editing techniques, and the development of novel radical cascade reactions. The group has published extensively in high-impact journals including Nature, Science, JACS, and Angewandte Chemie. Adolf-von-Baeyer-Denkmünze (2025) Arthur C. Cope Late Career Scholars Award of the American Chemical Society (2024) ERC Advanced Grants (2024, 2016) Multiple Highly Cited Researcher designations (2017-2022) Elected member of multiple academies (European Academy of Sciences, Academia Europaea, German National Academy of Sciences Leopoldina) Pedler Award of the Royal Society of Chemistry (2019) Professor Studer has mentored over 100 PhD students and postdoctoral researchers who have gone on to successful careers in academia and industry worldwide. His research is supported by significant grants including multiple ERC Advanced Grants and funding from the German Research Council (DFG) for collaborative research centers. The Studer Group maintains numerous international collaborations, particularly with institutions in Japan, China, and the United States, reflecting his global impact in organic chemistry. The Studer Group operates state-of-the-art laboratories at the University of Münster, equipped for advanced organic synthesis, photochemistry, and materials characterization. The group is known for its collaborative culture and has been featured in numerous group photos documenting its evolution since the early 2000s, first at Philipps-Universität Marburg and then at WWU Münster.
Dr. Elisa Donati is a researcher and independent group leader at the Institute of Neuroinformatics , affiliated with both the University of Zurich and the Swiss Federal Institute of Technology Zurich . Her work bridges neuromorphic engineering, biomedical signal processing, and wearable healthcare technologies, with a focus on creating brain-inspired systems for neuroprosthetics and rehabilitation. Affiliation: Institute of Neuroinformatics, University of Zurich & ETH Zurich Email: elisa@ini.uzh.ch Elisa’s research emphasizes developing neuromorphic signal processing strategies for wearable and embedded systems, enabling real-time closed-loop interactions with the nervous system. She specializes in translating neuroscience insights into energy-efficient technologies for digital health applications, including neuroprosthetics and personalized biomedical devices using neuromorphic hardware. Her recent publications (2024–2025) highlight advancements in gesture recognition via EMG and event-based systems, neuromorphic heart rate monitoring , and spiking neural network architectures . These works span biomedical signal processing, low-power computing, and adaptive algorithms, reflecting her commitment to robust, real-time, and brain-inspired solutions for healthcare. Elisa’s contributions to neuromorphic computing are evident in her exploration of heterogeneous population encoding , event-driven processing , and ultra-low-power microcontrollers . Her projects often integrate wearable systems with neuroscience, aiming to improve prosthetic control and rehabilitation technologies .
Dominique Chen is a Professor at Waseda University's School of Culture, Media and Society since 2022, previously serving as Associate Professor from 2017-2022. A French national born in 1981, he holds a Ph.D. in Interdisciplinary Informatics from the University of Tokyo (2013). His work bridges technology, art, and human experience with a focus on digital well-being and more-than-human relationships. Chen's research interests include human-microbe interaction, neo-cybernetics, and the design of systems that foster mutual care between humans and non-human entities. His work with the Nukabot project exemplifies this interdisciplinary approach, exploring how fermentation processes can serve as metaphors for communication and relationship building. He leads the Ferment Media Research group, investigating how fermentation principles apply to digital cultures and communication systems. His recent publications reveal a consistent focus on designing for well-being in digital societies, with particular attention to translation processes, human-microbe relationships, and the creation of systems that support co-adaptive interaction. The Nukabot research series demonstrates how traditional fermentation practices can inform novel interaction paradigms that acknowledge and incorporate more-than-human perspectives. Best Paper Honorable Mention (2024) - ACM Synlogue with Aizuchi-bot ACM SIGGRAPH Special Prize (2023) - Nukabot Best of AppStore 2015/2016 - Picsee/Syncle applications Good Design Award (2008) - Creative Commons Japan Super Creator certification (2009) - IPA Exploratory IT Program Chen has advised numerous projects through his leadership of Ferment Media Research and has served on various committees including the Good Design Award jury (2016-), Yomiuri Shimbun Reading Committee, and advisory boards for art and design institutions. His work extends beyond academia through his founding of Divideal Inc. (acquired by Smart News in 2018) and Creative Commons Japan (now Commonsphere). His laboratory, Ferment Media Research, explores interdisciplinary connections between fermentation processes, digital systems, and human relationships, creating installations like Nukabot that facilitate human-microbe interaction and Last Words/TypeTrace that examines writing processes and communication.
Georg Martius is a Full Professor in the Department of Computer Science at the University of Tübingen's Faculty of Science and a Max Planck Research Group Leader at the MPI for Intelligent Systems. Since April 2023, he has been a core member of the DFG-funded Cluster of Excellence 'Machine Learning: New Perspectives for Science,' which received extended funding through 2032 for its mission to integrate machine learning into fundamental scientific discovery processes. His academic foundation includes a PhD from the University of Göttingen and Bernstein Center for Computational Neuroscience (2005), a Diploma in Computer Science from the University of Leipzig (2003), and a visiting research period at the University of Edinburgh's Division of Informatics. Postdoctoral positions followed at the Max Planck Institutes for Dynamics and Self-Organization (Göttingen, 2009), Mathematics in the Sciences (Leipzig, 2010), and IST Austria (2015). Professor Martius's research pioneers the intersection of reinforcement learning, robotics, and tactile sensing, with emphasis on developing autonomous systems capable of natural locomotion, dexterous manipulation, and physical-world understanding. His work bridges theoretical machine learning with practical hardware applications, particularly in creating differentiable simulators, superresolution tactile sensors, and biologically plausible learning frameworks for robotic control. Analysis of his 2024-2025 publications reveals dominant trends in offline reinforcement learning (especially goal-conditioned and diversity-maximization techniques), object-centric representation learning for video understanding, and tactile sensing innovations. A strong thread connects foundation models to world model construction, while his work on differentiable physics engines enables precise collision handling and contact dynamics for real-world robotic control. His leadership roles include directing the Distributed Intelligence research team at Tübingen and contributing to major collaborative initiatives like the Real Robot Challenge and Myochallenge 2022. The Cluster of Excellence appointment represents recognition of his contributions to transforming scientific methodology through machine learning, particularly in automating hypothesis generation and experimental design. Current projects focus on integrating large-scale machine learning with embodied intelligence, advancing tactile perception systems like the Minsight vision-based sensor, and developing neuroplasticity-inspired approaches for robust out-of-distribution detection. His work directly impacts fields requiring physical interaction intelligence, from autonomous navigation to medical robotics, with emphasis on sample-efficient learning from limited real-world data.
Aura Istrate is a Lecturer/Assistant Professor in Urban Planning & Sustainable Urbanism at the School of Architecture, Planning and Environmental Policy at University College Dublin (UCD). With an international background spanning multiple continents, she conducts interdisciplinary research on sustainable urban development, focusing on active mobility, nature-based solutions, and climate-neutral cities. She teaches GIS and urban planning modules while coordinating several significant research projects across European and Asian contexts. University College Dublin, School of Architecture, Planning and Environmental Policy Primary Coordinator of C-NEWTRAL (Horizon MSCA-DN 2024-2028) Co-Leader of REALLOCATE (Horizon Europe project 2023-2027) Principal Investigator for BIODIVERSA+ projects (NatureScape and NBS4AQUAMISSION) Educated at the University of Architecture and Urban Planning 'Ion Mincu' in Bucharest (BA and MA) and the University of Liverpool (PhD), Dr. Istrate further enhanced her teaching credentials with a Professional Certificate in University Teaching & Learning from UCD. Her academic journey reflects a strong foundation in architectural and urban planning principles combined with specialized expertise in sustainable urbanism. Dr. Istrate's research focuses on smart and sustainable urbanism, particularly examining active mobility, livable streets, green public spaces, and nature-based solutions in urban planning. Her work employs participatory, geospatial, and mixed methods to inform smart communities and the transition to climate-neutral cities. She has practical international experience in urban design and planning, with ongoing collaborations spanning European and Asian countries, currently teaching and researching across cultures in UCD and UCD's International Colleges (CDIC). Her recent publications reveal a strong focus on street vitality, urban heat adaptation, and nature-based solutions. The research demonstrates methodological diversity combining quantitative spatial analysis with qualitative community engagement approaches. Her work spans multiple geographic contexts, with particular expertise in Chinese urban environments and European cities, showing how urban planning concepts need to be contextualized for different cultural settings. The articles consistently address climate adaptation challenges through innovative approaches like urban nature games and fine-grained street classification systems. Dr. Istrate serves as a PhD thesis supervisor and is actively involved in major research initiatives including C-NEWTRAL (as Primary Coordinator), REALLOCATE (as Co-Leader), and BIODIVERSA+ projects (as PI for NatureScape and NBS4AQUAMISSION). Her grant portfolio includes Horizon Europe projects and other significant funding that supports interdisciplinary research on climate-neutral urban development. She has coordinated multiple teaching modules including Planning Design & Development, GIS & Planning, Intro to Spatial Planning, and Local Planning Studio. She leads international research collaborations and maintains active partnerships across various European and Asian countries. Her work bridges academic research with practical urban planning applications, particularly through her focus on research-by-design approaches and participatory methods that engage communities in the planning process. She has served as a lecturer, tutor, or teaching assistant across departments of Architecture, Planning, Environmental Studies, Global Studies, and Human Geography in Ireland, the UK, Czechia, Sweden, China, and Romania since 2010.
Tuuli Toivonen is a Professor of Geoinformatics at the Department of Geosciences and Geography, University of Helsinki. She leads the transdisciplinary Digital Geography Lab , which addresses human-scale spatial analytics for sustainable societies. She serves as Vice-Director of Geography Degree Programs (post-2022) and previously held the Director role (2020-2022). After receiving the ERC Consolidator Grant in 2022, she continues advancing open science through active memberships in HELSUS and URBARIA . PhD in Geography (University of Turku, 2006) Specialist Vocational Qualification in Leadership (2023) Life Member, Clare Hall, University of Cambridge (since 2021) Her research focuses on Human-Place Interactions through accessibility/mobility lenses, combining Open Data , Machine Learning , and Spatial Analytics . Key application areas include Urban Geography , Conservation Science , and Governance Policy . Recent publications address Dynamic Cities (2018), Social Media for Conservation (2019), and Environmental Exposure During Travel (2021). Her lab produces datasets like the Helsinki Region Travel Time Matrix series (2014-2023). Scientific Awards: European Open Data Champion (2017) Open Science Price (2017) University of Helsinki Geography Award (2018) She supervises Master's thesis work and serves as Opponent for doctoral defenses across Europe. Her teaching portfolio includes Advanced Geoinformatics and Digital Geographies courses.
Cecilia O. Alm is a Professor in the Department of Psychology within the College of Liberal Arts at Rochester Institute of Technology (RIT), where she serves as the Artificial Intelligence Program Director. She holds multiple leadership roles including Director of the Center for Human-aware AI and Director of the Computational Linguistics and Speech Processing Lab (CLaSP). Her institutional affiliations span the School of Information, Ph.D. Programs in Cognitive Science and Computing and Information Sciences, Department of Computer Science, and MS in Data Science program. Dr. Alm earned her Ph.D. from the University of Illinois at Urbana-Champaign. Her research focuses on human-centered artificial intelligence with particular emphasis on linguistic and multimodal sensing, affective computing, and natural language processing. She investigates how AI systems can better understand and respond to human communication through multimodal dialogue processing, with applications in accessibility, education, and healthcare. Her recent publications demonstrate a strong trend toward developing inclusive AI systems, particularly through projects addressing Deaf community needs (MULTICOLLAB-ASL), subtle emotion recognition (FUSE corpus), and bias mitigation in NLP. The work consistently integrates multimodal data streams (speech, gaze, gesture) to create more responsive human-AI interaction frameworks. Current research directions emphasize diversity in AI education, visual prosody in sign languages, and human-in-the-loop AI development. Dr. Alm leads several significant NSF-funded initiatives including the AWARE-AI program, IRES AI-PROWIL international research experience, and collaborative projects with Gallaudet University focused on Deaf scientist-centered AI research. She has secured over $2.5 million in external funding for her work on human-aware AI systems. She directs the CLaSP lab which provides research opportunities for PhD, MS, and undergraduate students, with graduates employed at major technology companies including Amazon, Apple, Microsoft, and Facebook. The lab focuses on real-world AI applications in accessibility, human-robot interaction, and multimodal communication systems.
Gregory Paradis is an Assistant Professor in the Department of Forest Resources Management at the University of British Columbia (UBC) Faculty of Forestry. His research focuses on sustainable forest management, integrating operations research, mathematical optimization, and systems modeling to address complex interactions between ecosystems, industries, and society. He works with the FRESH Lab and collaborates with the Integrated Remote Sensing Studio, emphasizing ecological and economic integration in forest planning. Sustainable Forest Management Operations Research Forest Economics Data Science Risk Assessment GIS-based Methods His research spans forest inventory optimization, climate change adaptation strategies, wildfire risk modeling, and decision support systems for invasive species. He develops computational frameworks to enhance wood supply planning, carbon management, and ecological resilience. Recent work includes machine learning applications for fire safety in timber structures and automated road planning tools for wildlife conservation. Paradis’s publications highlight trends in applying optimization methods to sustainable forestry, with a focus on biodiversity, climate adaptation, and value chain innovation. He advocates for interdisciplinary approaches that bridge silviculture, industrial engineering, and data science to tackle emerging challenges in forest ecosystems. As an educator, he seeks motivated students with quantitative and creative problem-solving skills. His lab collaborates on remote sensing integration, risk assessment models, and policy-relevant forest management strategies, ensuring plans account for uncertainties like insect infestations or windthrow events.
Dominik Schörkhuber is a PreDoc Researcher at the Vienna University of Technology (TU Wien) in the Computer Vision department. With a background in Informatics (BSc, Dipl.-Ing.), he focuses on computer vision applications for autonomous driving, robotics, and human-machine interaction. His work spans driver action recognition, pedestrian prediction, and adaptive lighting systems. Current projects: Empathic Vehicle (2024–2026), SyntheticCabin (2021–2025), SmartProtect (2020–2025) Research themes: Video transformers, synthetic data transfer learning, multi-task learning, and sensor-lighting integration Specializes in 3D sensing, nighttime driving analysis, and mobile video creation tools
Dr. Kaitlyn Zhou is an incoming Assistant Professor in the Department of Information Science at Cornell University's Bowers College of Computing and Information Science, commencing August 2026. Her research focuses on human-language model interaction dynamics, with recognition at premier NLP and HCI conferences. Education: PhD in Computer Science, Stanford University (Advised by Dan Jurafsky) B.Sc., B.Se., M.S. in Computer Science and Human Centered Design and Engineering, University of Washington Research Focus: Her work investigates how language models shape human decision-making through three pillars: (1) identifying model overconfidence risks, (2) developing context-aware evaluation frameworks, and (3) reimagining interactions for marginalized user groups. This spans NLP, HCI, and AI ethics with emphasis on trust calibration and inclusive design. Publication Trends: Recent work examines human reliance on unreliable language models (NAACL 2025 Best Paper Runner-Up), uncertainty expression failures (ACL 2024), and evaluation metric limitations. Collectively, these advance responsible AI through human-centered methodologies across 12 major publications from 2017-2025. Scientific Awards: NAACL Best Paper Runner-Up (2025) MIT EECS Rising Star (2024) Stanford Graduate Fellowship College of Engineering Dean's Medal School of Engineering Dean's Medal of Excellence (UW) Advising & Grants: Supported by Stanford Graduate Fellowship and research internships at Microsoft Research FATE (hosted by Olteanu/Blodgett) and Allen Institute for AI (hosted by Sap/Hwang/Ren). Will recruit NLP/HCI students at Cornell starting 2026. Appointed by Washington Governor to UW Board of Regents, advocating for educational equity. Research Ecosystem: Collaborates with Stanford's NLP group, Microsoft's FATE team, and Allen Institute researchers. Features in NYT/WSJ for methods impacting real-world AI deployment.
Laura Solt, Ph.D. is an Associate Professor in the Department of Immunology and Microbiology at the Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology in Jupiter, Florida. She also serves as Associate Dean of the Skaggs Graduate School of Chemical and Biological Sciences. Dr. Solt began her independent research career at Scripps Florida in 2013 and has established herself as a leading researcher in nuclear receptor biology within the immune system. Her research focuses on understanding the biologically relevant roles of nuclear receptors, particularly RORα and REV-ERBs, in the immune system with emphasis on TH17 cell development and autoimmune disease. Her lab employs a multidisciplinary approach combining molecular biology, genetic techniques, and chemical biology coupled with mouse models of autoimmunity and chronic inflammation. Dr. Solt's laboratory has made significant contributions to understanding how nuclear receptors regulate immune cell function, particularly in TH17-mediated inflammation. Her work has demonstrated roles for RORα and REV-ERBs in TH17 cell development and has developed synthetic ligands to these receptors for potential therapeutic applications in autoimmune diseases. Her extensive publication record shows a clear trajectory of research focused on nuclear receptor signaling in immunity, with recent work expanding into applications for cancer immunotherapy, neuroimmunology, and metabolic aspects of immune cell function. Her articles demonstrate expertise in both basic nuclear receptor mechanisms and translational applications. Ruth L. Kirschstein National Research Service Awards (2010-2013) Dr. Solt actively mentors graduate students including Adrianna Wilson (recipient of NIDDK F31 and Scheller Graduate Student Fellowship) and Sarah Mosure (recipient of NIH NRSA F31 award and Wendy Havran award). Her laboratory receives substantial funding from multiple NIH institutes (NIDDK, NCI, NIAID, NIGMS) as well as the Crohn's & Colitis Foundation. Current research directions include investigating the roles of NR2F6 in TH17 cells, exploring RORα function in CD8 T cells, and developing novel nuclear receptor modulators for therapeutic applications.
Nathan W. Hudson is an Associate Professor in the Department of Psychology at Southern Methodist University (SMU) in Dallas, Texas. Previously, he received his Ph.D. in Psychology from the University of Illinois at Urbana-Champaign in 2016. His research focuses on personality psychology, particularly how people's personalities change across time and how individuals function in romantic relationships. He leads the Δ Lab at SMU, which investigates individual differences in human personality. Education: 2016 – Ph.D., Psychology, University of Illinois at Urbana-Champaign 2011 – M.A., Psychology, University of Illinois at Urbana-Champaign 2009 – B.A., Purdue University Nathan Hudson's primary research area is volitional personality change—people's desires and attempts to change their own personality traits. His groundbreaking research has shown that approximately 90% of people want to change aspects of their personality traits, and moreover, they may be able to find some degree of success in doing so. He also studies adult attachment styles and how people function in close relationships. Hudson's work suggests that attachment anxiety is linked to false memories, and that people's attachment styles can change over time. His research integrates both theoretical and applied perspectives, with implications for therapeutic interventions and personal development. Hudson's recent publications demonstrate a clear trajectory toward understanding the mechanisms of personality change and developing effective interventions. His work spans across multiple domains of personality psychology, with a particular emphasis on the Big Five personality traits, attachment theory, and well-being. A consistent theme throughout his research is examining how people's desires for change translate into actual personality growth. His work has increasingly focused on the practical applications of personality science, including developing measures and interventions that can help people achieve their desired personality changes. Scientific Awards: Goss-Lucas Award for Excellence in Teaching James Davis Fellowship Foundation for Personality and Social Psychology Heritage Dissertation Award Hudson actively mentors students in the Δ Lab at SMU, where they conduct research on personality change, attachment, and well-being. He has secured multiple grants to support his research on volitional personality change and the development of personality assessment tools. His lab has developed several psychological measures, including the Change Goals Big Five Inventory (C-BFI2) and its variants, which are freely available for academic research. Hudson also engages with the public through his TEDx talk "You Can Change Your Personality" and has been featured in Olga Khazan's book "Me, But Better," which applies his research to real-life settings. The Δ Lab, led by Hudson, is dedicated to understanding individual differences in personality and how people can intentionally change aspects of themselves. The lab values all individual differences among humans, recognizing that variance in human thoughts, feelings, and behaviors is adaptive and makes humanity resilient. The lab wholeheartedly supports the LGBTQ+ community and emphasizes that individual differences between humans are what personality science is all about.
Lan Wei is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Canada. She leads the Waterloo Emerging Integrated Systems Group, focusing on device-circuit co-optimization, cryogenic CMOS for quantum computing, and emerging technologies like GaN, RRAM, and low-dimensional materials. Her work bridges nanoelectronics and system-level applications, with notable contributions to the MIT Virtual Source GaN HEMT (MVSG) compact model, an industry-standard tool. Education: B.S. in Microelectronics and Economics, Peking University (2005) M.S. and Ph.D. in Electrical Engineering, Stanford University (2007, 2010) Research Interests: Nanoelectronic devices Cryogenic CMOS for quantum computing GaN-based circuits and systems RRAM-based neuromorphic computing Device-circuit interactive design Publications reflect her expertise in GaN modeling, quantum computing hardware, and RRAM applications. Recent work emphasizes scalable quantum control circuits and error-resilient neural networks using emerging technologies. Awards include the 2019 Ontario Early Researcher Award and the 2020 UWaterloo President's Excellence Award in Research. She has served on technical committees for IEDM, DATE, and ICCAD, and contributed to the ITRS roadmap. Teaching includes courses like ECE 240 (Electronic Circuits) and ECE 730 (Solid State Devices). Her group actively seeks graduate students with interest in integrated systems and nanoelectronics.
