Dr. Paul W. Mulvey is the Alumni Distinguished Undergraduate Professor of Human Resource Management and Director of Undergraduate Programs in Business Administration at North Carolina State University's Poole College of Management. He holds a PhD in Human Resource Management and Organizational Behavior from The Ohio State University and a Bachelors in Psychology from Lehigh University. His career includes teaching roles at Ohio State and the University of Connecticut before joining NC State. His research focuses on reward systems, work teams, leadership, recruitment, and retention. He has consulted with over 60 organizations and delivered executive education programs. Notable publications include works on organizational trust, compensation systems, and team dynamics. Mulvey is a recipient of multiple teaching awards, including NC State’s Outstanding Teaching Award and is a member of the Academy of Outstanding Teachers. Education: PhD (1991, Ohio State), BA (Lehigh) Expertise: Work team processes, compensation systems, organizational culture, leadership toxicity Labs/Initiatives: Faculty Director of BSBA Program, involved in the Enterprise Risk Management Initiative and Technology Commercialization Mulvey’s work has been featured in media such as NPR and USA Today. His research spans organizational behavior, leadership, and HRM, with over 30 years of academic and applied contributions.
Remco Breuker is a Professor of Korean Studies at Leiden University’s Humanities Institute for Area Studies (LIAS), specializing in medieval Korean and Northeast Asian history, North Korean affairs, and contemporary issues. His research bridges historical analysis with modern geopolitical challenges, particularly focusing on marginalized voices and historical narratives. He leads ERC-sponsored and LeidenAsiaCentre-funded projects on Manchurian histories and North Korean forced labor in the EU. Breuker holds a PhD from Leiden University and has held post-doctoral and visiting researcher roles at institutions like the Australian National University. Education: MA in Japanese Studies (Leiden University, 1997) MA in Korean Studies (Leiden University, 1997) MA in Korean History (Seoul National University, 2001) PhD in Korean History (Leiden University, 2006) Research Interests: Breuker’s work examines medieval Korea’s Koryŏ dynasty, Northeast Asian historiography, and modern North Korean political dynamics. He translates modern Korean literature into Dutch, emphasizing marginalized perspectives and cultural hybridity. Recent projects include analyzing North Korean forced labor networks and reinterpreting ancient Manchurian histories’ contemporary relevance. Awards: 2010 KNAW Heineken Young Scientist Award Academy of Korean Studies Translation Grants (2010, 2008) NWO VENI Research Grant (2008) Advisees & Grants: Supervises PhD candidates researching Korean-Vietnam War linkages, Japanese-Korean relations, and North Korean forced labor. Secured grants exceeding €600,000 for translation projects and interdisciplinary research. Leads LIAS initiatives and serves on Leiden’s Slavery Studies Association. Labs/Teams: Coordinates the History as Social Practice project and the Slavery Studies Leiden network, fostering collaborative research on historical narratives and modern exploitation systems.
Anshumali Shrivastava is an Associate Professor of Computer Science, Electrical and Computer Engineering, and Statistics at Rice University, affiliated with the George R. Brown School of Engineering. His research focuses on large-scale machine learning, randomized algorithms for big data, and graph mining. He holds a PhD from Cornell University (2015) and an MSc from the Indian Institute of Technology Kharagpur (2008). His research interests span scalable deep learning, efficient neural network inference, and probabilistic algorithms. He has pioneered techniques in compressed learning, hashing-based search, and distributed optimization for handling massive datasets. Notable contributions include methods for accelerating LLM inference, memory-efficient quantization, and graph processing algorithms. Teaching: Probabilistic Algorithms, Large-Scale ML, and Machine Learning Seminars Awards: Charles W. Duncan Jr. Achievement Award (2023), Young Faculty Research Award (2021), NSF CAREER Award (2017), and multiple best paper awards His work bridges algorithm design with practical applications in recommendation systems, genomics, and edge computing. Current efforts focus on sustainable AI, hardware-aware compression, and efficient training/inference pipelines for large models.
Joe Lockard is an Associate Professor of English at Arizona State University, affiliated with African & African American Studies and Jewish Studies. He holds a Ph.D. from the University of California, Berkeley (2000), and has taught at nine institutions across four countries, including UC Santa Cruz, UC Berkeley, and universities in Israel, Czech Republic, and China. His research focuses on antislavery literature, 19th-century American literature, and prison education advocacy. Lockard founded the Antislavery Literature Project (2003), which digitized abolitionist texts before transitioning into global translation initiatives, notably with Xi'an Jiaotong University. He co-edited three volumes of American slave narratives in Chinese translation. Current projects explore transatlantic slavery narratives and carceral literature. Lockard is a leading voice in prison pedagogies, co-authoring works on STEM education in prisons and death row literature's role in abolition movements. His work bridges literary scholarship with social justice activism, emphasizing global dialogue and educational equity.
Chandan J Vaidya is a Professor in the Department of Psychology at Georgetown University, directing the Developmental Cognitive Neuroscience Laboratory (DCNL). His research focuses on cognitive neuroscience mechanisms underlying adaptive behaviors, particularly implicit learning, executive control, and their dysfunction in ADHD, ASD, and other developmental disorders. Using multidisciplinary methods including fMRI, behavioral testing, and genetic analysis, he investigates how dopamine systems, brain connectivity, and environmental factors influence cognitive processes. Primary appointment: Professor, College of Arts and Sciences - Department of Psychology Education: Ph.D. from Syracuse University Research interests include neurodevelopmental disorders, neuroimaging of cognitive control, and translational neuroscience. Recent work examines striatal connectivity changes in ADHD due to stimulant use, executive dysfunction subtypes in autism, and brain correlates of reward processing in obesity. Key findings highlight hyperconnectivity in ASD, dopamine genotype influences on executive function, and age-related changes in default mode networks. Ongoing studies explore transdiagnostic models of psychopathology and precision medicine approaches in neurodevelopmental disorders. Lab activities focus on translational research bridging basic neuroscience with clinical applications. Collaborations involve pediatric neurology, psychiatry, and computational modeling.
Michio Honda is an Associate Professor (Reader) at the School of Informatics , University of Edinburgh , specializing in computer networking and operating systems . His research focuses on network stack designs, including co-design of networking and storage systems, and transport scale-out architectures. He has contributed to foundational work such as identifying TCP extensibility challenges (IMC'11) and pioneering TCP/IP stacks for persistent memory (NSDI'18). Research Trends : His 15 most recent works emphasize systems research, with keywords spanning Networking , Operating Systems , and High-Performance Computing . Sub-fields include TCP Protocol Design , Persistent Memory Optimization , and Network Scalability . Awards : Notable honors include the ISOC/IRTF Applied Networking Research Prize (2011), Facebook Research Award (2021), and Google Research Scholar Award (2022). Grants & Collaborations : Current projects involve network/storage co-design (HotNets'21) and transport scale-out (NSDI'21), often in collaboration with institutions like VMWare and Google.
Venkatesan Guruswami is a Chancellor's Professor in the Department of EECS and a Senior Scientist at the Simons Institute for the Theory of Computing at UC Berkeley . He also holds a Professor position in the Department of Mathematics . His academic journey began with a B.Tech in Computer Science from the Indian Institute of Technology, Madras (1997) , followed by a Ph.D. in Computer Science from the Massachusetts Institute of Technology (2001) . After a Miller Research Fellowship at UC Berkeley (2001–02), he held faculty roles at the University of Washington and Carnegie Mellon University before returning to UC Berkeley in January 2022. Education : B.Tech, IIT Madras (1997) Ph.D., MIT (2001) Professional Affiliations : Chancellor's Professor, UC Berkeley (EECS) Senior Scientist & Interim Director, Simons Institute Professor, UC Berkeley (Mathematics) Guruswami's research spans multiple domains within Theoretical Computer Science , focusing on Error-Correcting Codes , Approximation Algorithms , Randomness in Computing , Probabilistically Checkable Proofs , and Computational Complexity . His groundbreaking work in List Decoding has enabled codes with minimal redundancy for correcting worst-case errors, while recent advancements include Polar Codes , Deletion-Correcting Codes , and Constraint Satisfaction Problems . He has also contributed to Quantum Coding Theory , Locally Recoverable Codes , and Approximation Hardness in various computational contexts. His publications reflect a deep engagement with interdisciplinary topics. Key trends include: Quantum Information Theory : Quantum LDPC codes, transversal gates, and quantum storage. Algebraic Coding : Reed-Solomon codes, AG codes, and polynomial-based constructions. Computational Complexity : Hardness of approximation, CSPs, and parameterized intractability. Data Transmission : Polar codes, deletion channels, and feedback mechanisms. Algorithmic Techniques : Spectral methods, semirandom models, and Lasserre hierarchy applications. Guruswami has received numerous accolades, including the Simons Investigator Award , Presburger Award , Packard Fellowship , Sloan Research Fellowship , ACM Doctoral Dissertation Award , and the IEEE Information Theory Society Paper Award . He is an ACM Fellow (2017) and IEEE Fellow (2019) , with recent honors like the Guggenheim Fellowship (2023) and AMS Fellow (2023) . As an advisor, he has mentored over 25 PhD and postdoctoral researchers , including Atri Rudra , Prasad Raghavendra , and Peter Manohar , whose work has won awards like the Edmund M. Clarke Doctoral Dissertation Award and CRA Outstanding Undergraduate Researcher Award . His research is supported by grants from the National Science Foundation , Packard Foundation , and Sloan Foundation . He also serves as Editor-in-Chief of the Journal of the ACM and holds leadership roles in IEEE and arXiv moderation. Guruswami is actively involved in Simons Institute programs and co-organized workshops on Coded Computation and Information Theory . His work bridges theoretical advancements with practical applications in Cloud Storage , Quantum Computing , and Group Testing , including pandemic-era contributions like AC-DC: Amplification Curve Diagnostics for SARS-CoV-2 .
Mischa Billing is a Senior Lecturer at Örebro University specializing in Culinary Arts and Meal Science. She is actively involved in research on sensory experiences, wine studies, and food pairing. Her work spans across multiple disciplines including haptics, olfaction, and culinary traditions. Her research interests focus on the intersection of sensory perception and culinary practices. Billing explores how sound affects taste perception, develops haptic attribute models for food design, and investigates improved sensory experiences for the elderly. Her work in sommelier training and critical attribute techniques bridges traditional culinary knowledge with scientific approaches to sensory evaluation. Analysis of her publications reveals a strong focus on practical applications of sensory science in culinary contexts. Her work spans from theoretical explorations of wine tasting as embodied knowledge to practical guides for food and beverage pairing. The recurring themes include sensory integration, cultural contexts of food consumption, and innovative methods for enhancing meal experiences. Gastronomic Academy's Silver Medal Wine Profile of the Year Nose of the Year Honorary Truffle of the Year Billing has served as general secretary of the International Sommelier Association (ASI) and is a member of the Wine Academy in Sweden. She has extensive experience in evaluating diverse products including Swedish tap water and apple juice. Her media presence includes serving as a jury member on TV4's Sweden's Master Chef and delivering radio talks for Sveriges Radio. She leads several research initiatives including the Sense Lab, which focuses on future sensory experiences, and participates in research groups examining meals from social and cultural perspectives. Her projects like 'Rewine The World' demonstrate interdisciplinary approaches to reducing food waste through innovative culinary methods.
Aman Arora is an Assistant Professor at Arizona State University's Ira A. Fulton Schools of Engineering, specializing in the School of Computing and Augmented Intelligence. His research focuses on reconfigurable computing, hardware acceleration of machine learning, and non-traditional computing paradigms like Processing-In-Memory. With over a decade of semiconductor industry experience, he bridges academic research and industrial applications. PhD in Computer Science from The University of Texas at Austin Research interests emphasize domain-specific acceleration through FPGA optimization , compute-in-memory architectures , and machine learning for CAD/EDA . His work addresses critical challenges in energy efficiency and throughput for AI workloads. Recent publications demonstrate trends toward compute-in-memory systems , FPGA-based deep learning acceleration , and sustainable hardware design . Key contributions include frameworks like SAF, CSR, and GAMA for dynamic hardware optimization. Laboratory Website: ADVENT Lab Teaching includes courses on digital hardware design (CSE 320) and advanced topics in machine learning acceleration (CEN 524/CSE 524). Industry experience informs his practical approach to research and education.
Naomi Rogers, Ph.D. (She/Her) is Professor of the History of Medicine in the Section of the History of Medicine and the Program in the History of Science and Medicine at Yale University. She holds courtesy appointments in the History Department and the Women's, Gender and Sexuality Studies Program, and serves on Yale's Dean's Advisory Council for LGBTQI Affairs. Professor Rogers teaches undergraduate, graduate, and medical students, regularly lecturing on the history of AIDS, reproduction, health economics, eugenics, nutrition, disability, and health activism. Professor Rogers' educational background includes: PhD in History from University of Pennsylvania (1986) MA from University of Pennsylvania (1986) BA in Music from Melbourne University (1980) BA with Honors from Melbourne University (1979) Her research focuses on 20th and 21st century history of medicine with emphasis on health inequities and social justice. Professor Rogers' historical interests span gender and health, disease and public health, disability studies, feminism, alternative medicine, health policy, and health activism. Her work critically examines the intersection of medical practices with social movements, particularly how marginalized communities have challenged medical orthodoxy throughout American history. She has published extensively in journals such as American Journal of Public Health, Bulletin of the History of Medicine, Journal of Medical Humanities, Radical History Review, Social History of Medicine, and Women and Health. Professor Rogers' recent scholarship demonstrates a consistent focus on the historical dimensions of contemporary health issues, particularly vaccine politics, abortion history, and community health activism. Her publications reveal patterns of resistance to medical authority, the role of race and gender in shaping health outcomes, and the historical roots of current health justice movements. Her work bridges academic history with public engagement, as evidenced by her frequent media commentary on COVID-19 and other health issues in outlets including BBC Radio, CNN, Huffington Post, National Public Radio, New York Times, Wall Street Journal, and Washington Post. Among her notable recognitions: AAHN's Lavinia L. Dock Award for Exemplary Historical Research for 'Polio Wars: Sister Kenny and the Golden Age of American Medicine' (2014) Presenter of the AAHM's Garrison Lecture: 'Radical Visions of American Medicine: Politics and Activism in the History of Medicine' (2017) Professor Rogers has been actively involved in academic leadership and mentoring. She has served as Director of Graduate Studies for the 2022-23 academic year, Chair of the Women's Faculty Forum, and Liaison to the Committee on Status of Women in Medicine. Her service extends to editorial boards including the Journal of the History of Medicine and Allied Sciences since 2018. She has also contributed to public understanding of medicine through consultations for documentaries including 'The Polio Crusade' (PBS), 'On the Basis of Sex' (Focus Features), and 'War on Science' (in process). Currently, Professor Rogers serves on the Medical School's OBGYN 'Dobbs' Sessions Planning Committee, which has organized webinars for the Yale community, and was co-organizer of the history-themed session 'Rooted in History: Abortion, Law and American Health Care.' She is working on her book project 'Health Radicalism and the Humanization of American Medicine' (under contract with Oxford), examining critics of medical orthodoxy since 1945 including civil rights, consumer, and feminist activists. She also conducts ongoing research on antisemitism in American medicine in the decades before and after World War II.
Mohamed F. Mokbel is a Distinguished McKnight University Professor in the Department of Computer Science and Engineering at the University of Minnesota - Twin Cities , where he also serves as the Director of Graduate Studies. He is recognized as an IEEE Fellow and ACM Distinguished Member for his contributions to spatially- and privacy-aware systems. His research focuses on database systems , spatial data management , and GIS (Geographic Information Systems) , with significant work in spatiotemporal data, location-based services, and machine learning for spatial applications. His most recent publications address scalable BERT-based trajectory imputation , spatial logistic regression frameworks , and spatiotemporal big data decay techniques . Key Awards: Distinguished McKnight University Professor (2023) ACM SIGSPATIAL 10-Year Impact Award (2022) IEEE Fellow (2020) ACM Distinguished Member (2017) NSF CAREER Award (2010) Selected Conference Papers: Recathon (2015, IEEE MDM Best Paper) ST-Hadoop (2017, SSTD Best Paper) KAMEL (2023, ACM SIGMOD Demo) Academic Service: Editor-in-Chief, ACM Transactions on Spatial Algorithms and Systems (2024–) General Co-Chair, ACM SIGSPATIAL 2025 Past Chair, ACM SIGSPATIAL (2014–2017)
Ravid Shwartz-Ziv is an Assistant Professor and Faculty Fellow at NYU's Center for Data Science, with a dual role as Senior Research Scientist at Wand AI. His research bridges theoretical foundations and practical applications in artificial intelligence, focusing on Large Language Models (LLMs), information theory, and neural network interpretability. Ph.D. in Computational Neuroscience, Hebrew University of Jerusalem (2021) B.Sc. in Computer Science and Computational Biology, Hebrew University of Jerusalem (2014) His research spans: Developing min-p sampling for LLM text generation Preventing representation collapse in Transformers Creating contamination-free LLM benchmarks like LiveBench Advancing information-theoretic frameworks for neural networks Exploring representation learning and model adaptation Recent publications demonstrate expertise in LLM efficiency, self-supervised learning, and multi-agent systems. Notable awards include the Google PhD Fellowship, Moore-Sloan Fellowship, and multiple best paper recognitions. He has led research initiatives at Intel and Google AI, focusing on neural network compression, XGBoost comparisons for tabular data, and innovative benchmarking frameworks.
Ion Stoica is a Professor in the Electrical Engineering and Computer Sciences Department at the University of California, Berkeley, where he holds the Xu Bao Chancellor Chair. He serves as Director of the Sky Computing Lab and is Executive Chairman of both Databricks and Anyscale. His research spans distributed systems, cloud computing, and AI systems, with significant contributions to large-scale data processing frameworks. Stoica's research interests focus on the intersection of AI and systems, with emphasis on developing practical implementations that bridge theoretical foundations with real-world deployability. His work addresses fundamental challenges in distributed computing, resource management, and large-scale machine learning systems. Current projects include Ray (a distributed execution framework), vLLM (a high-throughput inference engine for LLMs), Chatbot Arena (an open platform for human preference evaluations), and SkyPilot (a framework for running AI workloads across clouds). His research output demonstrates a consistent trajectory toward more efficient, scalable systems for modern AI workloads, particularly focusing on optimizing inference performance, resource utilization, and cross-cloud deployment. Recent publications reflect growing interest in large language model serving, video generation optimization, and agent-based systems. ACM Fellow SIGOPS Hall of Fame Award (2015) SIGCOMM Test of Time Award (2011) ACM Doctoral Dissertation Award (2001) Member of National Academy of Engineering Honorary Member of the Romanian Academy Stoica has advised an extensive number of doctoral students who have gone on to prominent positions in academia and industry, including assistant professorships at Stanford, MIT, Carnegie Mellon, and other top institutions. He has received significant research funding through his lab activities and startup ventures. His research group has been particularly successful in translating academic research into widely adopted open-source technologies and commercial products. Stoica leads the Sky Computing Lab at UC Berkeley, which focuses on developing systems for AI workloads across multiple clouds. His research group has produced numerous influential open-source projects including Apache Spark, Apache Mesos, and Alluxio, which have become industry standards for large-scale data processing. The lab maintains strong industry partnerships while pursuing fundamental research in distributed systems and AI infrastructure.
Dr. Valerie Hebert is a Professor of History and Interdisciplinary Studies at Lakehead University, specializing in Holocaust photography, genocide studies, transitional justice, and human rights. She joined Lakehead in 2010 and previously held a SSHRC Post-Doctoral Fellowship at York University. Ph.D., University of Toronto (2006) M.A., McGill University (1999) H.B.A., McGill University (1997) Her research intersects 20th-century European history , legal historiography , and visual analysis , with a focus on post-atrocity justice (Nuremberg, Rwanda) and the role of photography in documenting human rights violations. She has presented internationally at conferences in Canada, the U.S., U.K., and Europe. Dr. Hebert has received multiple fellowships, including from the German Historical Institute , US Holocaust Memorial Museum , and Martin Buber Society . Her SSHRC Insight Grant -funded monograph project Five Shots from Sdolbunow examines Holocaust photography.
Desmond Elliott is an Associate Professor in the Natural Language Processing section at the Department of Computer Science, University of Copenhagen (UCPH). His research focuses on multimodal and multilingual models with specific emphasis on vision-language integration and tokenization-free NLP approaches. He teaches Bachelor and Master's level courses including Advanced Topics in Natural Language Processing (since 2019), Grundlæggende Data Science (since 2023), and previously Data Science (2021-2023). His research interests center on building and understanding multimodal and multilingual models , particularly exploring vision and language interactions through billion-parameter systems. Current work investigates cultural representation disparities in vision-language models, parameter-efficient captioning, and multimodal distributional semantics across diverse domains including food culture and medical imaging. His methodology emphasizes real-world applicability in non-English contexts and ethical considerations in multimodal systems. Elliott's recent publications (2025) demonstrate leadership in multimodal NLP, with significant contributions to vision-language pretraining, multilingual evaluation frameworks, and clinical NLP applications. His work spans theoretical advancements in model architectures and practical implementations addressing challenges in low-resource languages and domain adaptation. Best Long Paper Award at EMNLP 2021 Best Poster Award at COLING 2019 As an active educator, Elliott contributes to courses on Fair and Transparent Machine Learning and previously taught Information Retrieval. His research collaborations span international institutions with particular focus on European and non-English language contexts, reflecting UCPH's recognition as Europe's #1 institution for HCI research over the past decade.
