Liangming Pan is an Assistant Professor at the University of Arizona's College of Information Science. His research focuses on building trustworthy large language models (LLMs) with an emphasis on logical reasoning, truthfulness, and safety. He holds a PhD in Computer Science from the National University of Singapore (2022), a Master's from Tsinghua University, and a Bachelor's from Beihang University. Education : PhD in Computer Science, National University of Singapore (2022) Master of Engineering in Computer Science, Tsinghua University (2017) Bachelor of Engineering in Computer Science, Beihang University (2014) Research Interests : Dr. Pan's work centers on enhancing LLMs' reliability through: Logical reasoning mechanisms to ensure faithful deductions Truthfulness verification to combat misinformation Safety protocols to mitigate societal harm Key Contributions : Developed TART, an open-source framework for explainable table-based reasoning Created benchmarks like SCITAB and FactCheck-Bench for evaluating LLMs Advanced techniques for knowledge editing and causal reasoning Awards : Best Paper Runner-Up at NeurIPS Table Representation Workshop (2024) Area Chair Award for Question Answering (IJCNLP-AACL 2023) Service & Outreach : He serves as an Area Chair for EMNLP (2024), COLING (2025), and ACL (2024). He has delivered invited talks at Tsinghua University, Peking University, and other institutions.
Dr. Robert Lount, Jr. is a Professor in the Management & Human Resources Department at The Ohio State University's Fisher College of Business. His research focuses on optimizing collaboration outcomes through motivation, trust, and negotiation strategies. He holds a PhD from Northwestern University's Kellogg School of Management and has taught at institutions including Kellogg, Cornell’s Johnson School, and INSEAD. Lount specializes in negotiation courses and has been recognized for teaching excellence with the Westerbeck Pace Setter award. His work bridges academic journals and popular media like Harvard Business Review and The New York Times. Education: PhD and MS from Northwestern University, BS in Psychology from Michigan State University. Research emphasizes trust development, conflict resolution, and group dynamics. He contributes to programs like MSCM Mid-Program Experience, integrating negotiations training with healthcare and life sciences applications. Courses include Leadership in Health Sciences, Negotiations, and Advanced Organizational Behavior seminars.
Foteini Mourkioti is an Associate Professor at the University of Pennsylvania's Perelman School of Medicine , with a joint appointment in the Graduate Groups of Cell and Molecular Biology and Bioengineering . She co-directs the Musculoskeletal Regeneration Program at the Penn Institute of Regenerative Medicine and leads the McKay Orthopaedic Research Laboratory . Research Interests : Muscle Stem Cell Biology Mechanobiology Muscle Regeneration Telomere Biology in Muscular Diseases Fibrodysplasia Ossificans Progressiva (FOP) Cardiomyopathy and Aging Key Research Contributions : Developed the Pax7EGFP mouse model for real-time muscle stem cell tracking Discovered telomere shortening as a critical factor in Duchenne Muscular Dystrophy Elucidated the role of NF-κB in muscle stem cell dysfunction Identified Piezo1's role in stem cell morphological states Characterized fibro-adipogenic progenitor dynamics in FOP Scientific Awards : NIH/NHLBI R01 grant recipient (2019) NASA grant awardee (2020, 2017) American Heart Association grant (2017) Muscular Dystrophy Association grant (2019) University Research Foundation grant (2018) Publications & Collaborations : Over 25 publications in high-impact journals like Science Advances , Nature Protocols , and Cell Reports . Collaborates with Penn Cardiovascular Institute and Pennsylvania Muscle Institute.
Julie C. Liu is an Associate Professor of Chemical Engineering at Purdue University, with a courtesy appointment in Biomedical Engineering. She joined Purdue in 2008 and holds a B.S.E. from Princeton University, M.S. and Ph.D. from Caltech, and completed a postdoc at the University of Massachusetts Medical School. Her research focuses on protein-based biomaterials for tissue engineering, regenerative medicine, and surgical adhesives, with a particular emphasis on recombinant proteins and natural matrix molecules like collagen and hyaluronic acid. Key awards include the Purdue Faculty Scholar (2019-2024), ELATES Fellowship (2019), and Outstanding Mentor Award (2018). Her work has been funded by NSF, NIH, and industry grants. She advises multiple graduate and undergraduate students, mentoring over 20 researchers. Her lab collaborates on outreach, including Introduce a Girl to Engineering Day, reaching 500+ students since 2014. Liu’s lab designs biomaterials with tailored properties for cartilage repair, drug testing models, and adhesives. Recent advances include mussel-inspired adhesives and redox-responsive hydrogels. She leads a team focused on translational biomedical innovations, bridging engineering and clinical applications.
Gang Wang is an Associate Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the Siebel School of Computing and Data Science. He also holds affiliate roles in the Department of Electrical and Computer Engineering, the Informatics Program (School of Information Sciences), and the Coordinated Science Laboratory (CSL). He joined UIUC in 2019, previously serving as an Assistant Professor at Virginia Tech. Education: Ph.D. in Computer Science from UC Santa Barbara (2016), advised by Ben Y. Zhao and Heather Zheng; B.E. from Tsinghua University (2010). Awards include the NSF CAREER Award (2018), Amazon Research Award (2021), and multiple best paper awards in top conferences like USENIX Security and ACM CCS. Research focuses on Security and Privacy, Internet Measurement, and Data Mining. Key areas include email spoofing vulnerabilities, adversarial machine learning, and AI-driven security tools. Recent projects involve explainable AI for phishing detection, benchmark contamination in LLMs, and mitigating deepfake disinformation. Publications span top venues like USENIX Security, IEEE S&P, ACM CCS, and IMC. He collaborates with industry partners and researchers in HCI and AI. Current roles include Associate Director of the Capital One Illinois Center for Generative AI Safety (ASKS) and leadership in NSF-funded initiatives like the ACTION AI Institute.
Juergen Schmidhuber is Associate Professor at the Faculty of Informatics of Università della Svizzera italiana and a leading researcher at the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI). He is also Chief Scientist at NNAISENSE, a company dedicated to building practical general-purpose AI. His work has profoundly influenced modern artificial intelligence, particularly through the development of Long Short-Term Memory (LSTM) networks in 1991, now deployed across billions of devices for speech recognition, machine translation, and virtual assistants. His research interests span Artificial Intelligence, Deep Learning, Recurrent Neural Networks, Universal AI, Meta-Learning, Algorithmic Information Theory, Artificial Curiosity, Robotics , and Low-Complexity Art . He has pioneered mathematically rigorous frameworks for self-improving AI systems and formal theories of creativity and beauty. His work bridges theoretical foundations with real-world applications in computer vision, natural language processing, and autonomous robotics. The recent articles reflect a consistent trajectory of innovation, combining deep theoretical insights with scalable machine learning architectures. His publications emphasize sequence modeling, universal learning, intrinsic motivation, and computational creativity , demonstrating both foundational contributions and industrial impact. From LSTM to Goedel machines, his work consistently targets the long-term goal of self-improving general AI. Scientific Awards: Numerous awards in AI and machine learning (specific names not listed) Schmidhuber leads a research group at IDSIA, where he mentors students and researchers in advancing the frontiers of AI. His lab has secured significant recognition and industrial collaboration, though specific grants are not detailed. He promotes the 'New AI'—general, sound, and relevant to physics—and continues to explore the convergence of intelligence, computation, and the universe. Labs and Teams: Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI) NNAISENSE (as Chief Scientist)
Shiqing Ma is an Assistant Professor in the Manning College of Information and Computer Sciences at the University of Massachusetts Amherst. Previously, he held a faculty position at Rutgers University from 2019 to 2023. He earned his Ph.D. in Computer Science from Purdue University (2019) and B.E. from Shanghai Jiao Tong University (2013). His research focuses on secure, intelligent, and transparent computing systems, particularly at the intersection of security, AI, and software systems. Key areas include integrating machine learning into software systems, ensuring algorithmic security through program analysis, and developing novel system architectures. Professor Ma's work has been recognized with prestigious awards, including the NSF CAREER Award (2023), and distinguished paper awards at USENIX Security (2017) and NDSS (2016). He actively contributes to the academic community through editorial roles and program committees in security, privacy, and software engineering. His research explores topics like backdoor attacks, AI safety, and bias mitigation in large language models. Recent articles emphasize defense mechanisms against adversarial attacks, watermarking techniques, and automated debugging systems for machine learning pipelines.
LU Wen Feng is an Adjunct Associate Professor in the Department of Mechanical Engineering at the National University of Singapore (NUS), affiliated with the College of Design and Engineering. His research focuses on advanced manufacturing technologies, including additive manufacturing, robotics, and AI-driven systems. He explores sustainable design methodologies, smart manufacturing innovations, and bioprinting applications. Key areas include optimizing material processes, enhancing mechanical properties of printed materials, and developing autonomous robotic solutions for industrial tasks. Contact: mpelwf@nus.edu.sg , located at E3-02-07. Research Interests : His work bridges AI and manufacturing, emphasizing Knowledge graph integration for additive manufacturing, Autonomous robotic systems in industrial settings, Bioprinting for tissue repair with smart bioinks, Topology optimization for lightweight and sustainable structures, Material characterization and process engineering for 3D-printed composites. Recent Article Trends : LU Wen Feng's 2025 articles highlight advancements in AI-augmented manufacturing systems (e.g., MaViLa, AutoMEX) and sustainable design workflows. His 2024 studies address material anisotropy, corrosion behavior, and topology optimization strategies for lattice structures. These trends reflect his interdisciplinary approach to solving challenges in additive manufacturing, robotics, and biomedical applications. Awards : No scientific awards explicitly mentioned. Advising & Grants : No current graduate students or grants listed. His research likely integrates industry-academia collaborations given the focus on applied manufacturing technologies. Labs/Teams : Not explicitly detailed, but his work suggests involvement in advanced manufacturing labs and AI-robotics teams at NUS.
Dr. Darryl Dickerson is an Assistant Professor in the Department of Mechanical and Materials Engineering at Florida International University (FIU), part of the College of Engineering. His research focuses on mechanical characterization of biological interfaces, design of bioinspired materials, and advancing inclusive engineering education practices. He holds a Ph.D. (details not explicitly provided in text). Research Interests: Dr. Dickerson’s work bridges biomechanics and biomaterials engineering with social equity in education. Key areas include: Mechanical properties of biological interfaces (e.g., bone-cartilage junctions) Development of biomaterials for tissue repair using 3D printing and electrospinning Anti-marginalization strategies in engineering education, particularly for Black and Brown students Publications Trends: Recent work emphasizes dual themes: (1) Biomedical innovation through advanced material fabrication and (2) Inclusive pedagogy addressing systemic inequities in STEM education. Notable contributions include scaffold designs for osteochondral repair and frameworks for reducing microaggressions in team-based learning. Grants and Advising: No specific grants or advisees listed in the provided text. His work appears to be grant-funded through NIH/National Science Foundation pathways common in biomaterials and education research. Labs and Teams: While not explicitly stated, his research likely involves collaborations with FIU’s Center for Engineering and Computing’s diversity initiatives and biomaterials labs focusing on tissue engineering applications.
Theresa Raimondo is the Manning Assistant Professor of Engineering at Brown University, with a secondary appointment in the Division of Biology and Medicine. She joined the Brown Engineering faculty in January 2024 after completing her postdoctoral training at MIT's Koch Institute. Dr. Raimondo leads the Raimondo Research Lab, which focuses on chemically modifying RNA and designing nanoparticles for therapeutic delivery to the body, an immunotherapy concept that holds immense promise in the field of immunoengineering. Her educational background includes: PhD in Engineering Sciences – Bioengineering from Harvard University (2019) MEng from Harvard University (2019) Sc.B. in Chemical and Biochemical Engineering from Brown University (2011) Dr. Raimondo's research is broadly focused on the design of targeted drug-delivery vectors and novel RNA-based therapeutics for applications in cancer, immunotherapy, and tissue regeneration. Her work primarily centers on developing novel lipid nanoparticles (LNPs) for RNA-based therapies, contributing to adjuvanted mRNA-based vaccines and siRNA-based cancer immunotherapies. By optimizing LNP formulation and modulating RNA constructs, she seeks to understand how RNA-LNPs modulate immunity and develop new therapeutic approaches. Her expertise spans biomaterials, drug delivery, biomolecular engineering, nanomedicine, tissue engineering, and regenerative medicine. Analysis of Dr. Raimondo's recent publications reveals a strong focus on RNA delivery systems and lipid nanoparticle technology. Her work spans from fundamental studies on nanoparticle design to applications in cancer immunotherapy, vaccine development, and tissue regeneration. A significant portion of her research involves optimizing lipid formulations for improved mRNA delivery and exploring how these systems interact with the immune system. Her publications demonstrate a trajectory from basic biomaterials research to increasingly translational work with therapeutic applications. Dr. Raimondo has received numerous prestigious awards: 2025 NAE Symposium selection (Grainger Foundation Frontiers of Engineering) 2025 appointment to the inaugural Early Career Board of ACS Applied Bio Materials 2024 selection as MIT Faculty Founder Initiative finalist 2022 Convergence Scholar fellowship from MIT's Marble Center for Cancer Nanomedicine National Science Foundation graduate research fellowship Harvard's Smith family graduate fellowship Dr. Raimondo is actively involved in mentoring students through courses including ENGN 0931L - Biomedical Engineering Design and Innovation II, ENGN 1490 - Biomaterials, and ENGN 1931L - Biomedical Engineering Design and Innovation II. Her research program is supported by various grants, though specific funding sources aren't detailed in the provided text. The Raimondo Research Lab represents a dynamic environment where engineering principles are applied to solve complex biological challenges in drug delivery and regenerative medicine. The Raimondo Research Lab at Brown University serves as a hub for innovation in RNA delivery and biomaterials design. The lab brings together expertise in chemical engineering, molecular biology, and immunology to develop next-generation therapeutic platforms. Current research directions include optimizing lipid nanoparticle formulations, exploring novel RNA modifications, and investigating immune responses to RNA therapeutics across various disease contexts.
James Carroll is a Professor in the Department of Electronic & Electrical Engineering (EEE) at the University of Strathclyde, where he also serves as Director and Principal Investigator of the Wind and Marine Energy Systems and Structures CDT (2019–2027) and the Strathclyde lead for the EnerHy Wind and Hydrogen CDT (2024–2032). He is Co-Lead of the Wind Energy and Control (WEC) Group, one of the largest university-based wind energy research groups in the UK, comprising 8 academics and over 35 researchers. His research interests are centered on wind energy systems, with a focus on: Novel wind turbine concept development Wind turbine reliability and maintenance modeling Cost of energy and O&M cost modeling Drive train selection impact on reliability Condition monitoring and failure prediction of wind turbine components Data-driven machine learning and physical modeling for remaining useful life prediction SCADA and vibration data analytics The recent articles highlight a consistent trend in offshore and onshore wind energy innovation, with strong emphasis on predictive maintenance, cost reduction, digital twins, and novel turbine design. His work bridges engineering, data science, and sustainability, contributing significantly to renewable energy advancement. Scientific recognition includes: 2nd Place, Future Energy Competition (2019) James Carroll has been actively involved in major research projects, including EPSRC-funded CDTs and industry collaborations, focusing on hydrogen integration, digital twins for powertrains, and offshore wind maintenance optimization. He has also contributed to professional activities such as keynote speaking at the Wind Energy Science Conference 2019 and participation in EPSRC scoping workshops. He supervises research students and leads a dynamic team within the WEC Group, driving innovation in wind and marine energy systems. His research group, the Wind Energy and Control (WEC) Group, is a leading UK academic team in wind energy, fostering interdisciplinary collaboration and training the next generation of energy engineers through doctoral training programs.
Mathias Payer is an Associate Professor at EPFL's School of Computer and Communication Sciences (IC), leading the HexHive Laboratory . His work focuses on software security, particularly addressing memory corruption and type violations through binary analysis and compiler-based techniques. He contributes to research in secure system design, fault isolation, and fuzzing methodologies. Current PhD students : Di Bartolomeo Luca, Feng Zhiyao, Hofhammer Florian, Lyu Tao, Mao Philipp Yuxiang, Zhang Chibin, Zheng Han Past EPFL PhD students: Badoux Nicolas Daniel, Bhattacharyya Atri, Hazimeh Ahmad His research explores software security in areas like: Protecting applications from vulnerabilities Binary exploitation and mitigation Compiler-driven security hardening Strong sanitization and privilege separation Memory corruption detection The HexHive group develops tools and frameworks for: Automated fuzz driver generation Gradual compartmentalization State inference for feedback optimization Secure cell architectures Recent publications highlight advancements in: Fuzzing hybrid approaches (e.g., DUMPLING, MendelFuzz) Memory safety validation (QMSan, Pacmem) Compiler-assisted defenses (Gradient, Type++)
Carlo Alberto Furia is an Associate Professor and Vice Dean at the Faculty of Informatics, Università della Svizzera italiana (USI). He is affiliated with the Software Institute, where he leads the ATOM research group. His academic journey includes prior roles as an Associate Professor at Chalmers University of Technology and a Senior Researcher at ETH Zurich’s Chair of Software Engineering. PhD in Computer Science, Politecnico di Milano Master of Science in Computer Science, University of Illinois at Chicago Laurea in Computer Science and Engineering, Politecnico di Milano His research centers on formal methods for software engineering, aiming to enhance software correctness, reliability, and quality through rigorous techniques. Key areas include automated program verification, contract-based development, loop invariant inference, and empirical evaluation using Bayesian data analysis. He emphasizes practical applicability and automation in formal methods. His recent publications reflect a strong focus on program analysis at the bytecode level, multilingual software analysis, automated repair of Android security issues, and empirical methodologies. These works span topics such as JVM substitutability, exception behavior in Java bytecode, and information flow security, demonstrating a consistent thread in improving software robustness through formal and automated techniques. He is actively involved in the software engineering research community as an Associate Editor of the Empirical Software Engineering (EMSE) journal and as a Program Committee member for major conferences including FASE, FM, ASE, ICSE, and CauSE. Carlo Furia has advised multiple research projects and supervised student theses. He has led and contributed to funded research initiatives, particularly in program analysis and verification. His group has developed tools such as AutoProof and other software artifacts available through the ATOM software page. He regularly teaches courses such as Software Analysis, Programming Fundamentals, and Software Design & Modeling. He leads the ATOM research group, which focuses on advancing automated techniques for software testing, analysis, and verification. The group develops practical tools and conducts empirical studies to validate research outcomes.
Joshua D. Rabinowitz is a Professor of Chemistry and the Lewis-Sigler Institute for Integrative Genomics at Princeton University, where he also serves as Director of the Ludwig Princeton Branch. His research focuses on achieving a quantitative, comprehensive understanding of cellular metabolism, with applications in both basic science and medical research. Dr. Rabinowitz's research interests span multiple areas of metabolism and systems biology: Quantitative analysis of metabolic networks and regulation Metabolomics and measurement of metabolite concentrations and fluxes Cancer cell metabolism and therapeutic targeting Metabolic regulation in microbes (E. coli, Saccharomyces cerevisiae) Biofuel production (focusing on Clostridium acetobutylicum) Metabolic impact of pathogen infection (viral infection of human cells) His laboratory has developed innovative methods for measuring cellular metabolites using state-of-the-art mass spectrometry technology and approaches for quantitating metabolic fluxes through isotope-labeling data interpretation. Analysis of recent publications reveals a strong focus on NAD+ metabolism, cancer metabolism, metabolic adaptations in disease states, and the intersection of metabolism with immunology and neuroscience, particularly in areas like T cell metabolism, Alzheimer's disease, and cardiac function. Dr. Rabinowitz has received recognition as a Highly Cited Researcher by Web of Science, indicating significant impact in his field. He advises several graduate students and has mentored numerous alumni, including Michel I. Nofal, Edmundo Leiva III, and Sean Hackett. His research is supported by multiple programs including NIH NHGRI Training Program and QCB Graduate Program. The Rabinowitz Lab operates at the intersection of chemistry, biology, and computational science, with all projects involving a mix of biological experiments, metabolomics, and computation to achieve their goal of a holistic understanding of cellular metabolism.
Zohreh Sharafi is an Assistant Professor of Software Engineering in the Department of Computer and Software Engineering (GIGL) at Polytechnique Montréal. Previously, she served as a Senior Research Fellow in the Department of Electrical and Computer Engineering at the University of Michigan, Ann Arbor, where she worked with Dr. Westley Weimer and was awarded the prestigious NSERC Postdoctoral Fellowship. Prior to her academic career, she worked as a software engineer at Morgan Stanley, contributing to the firm's electronic trading platform and serving as principal architect of SURF, a market data simulator. Her educational background includes a Ph.D. in Computer Engineering from École polytechnique de Montréal under the supervision of Dr. Giuliano Antoniol and Dr. Yann-Gaël Guéhéneuc, a Master of Applied Science in Software Engineering from Concordia University, and a Bachelor of Computer Engineering from the University of Tehran. Dr. Sharafi leads the SENSE Lab, a multidisciplinary software engineering research laboratory focused on understanding problem-solving strategies developers use during software development, with particular attention to human factors such as gender and native language. Her research combines human-centric design with experimental methodologies, investigating cognitive processes involved in software development using biometric measures including eye tracking and neuroimaging. Current active projects include evaluating trustworthiness perceptions of software artifacts and studying the role of creativity in software engineering tasks. She has made significant contributions to understanding how gender influences program comprehension and code review processes. Her publication record demonstrates a strong focus on empirical methods in software engineering, particularly eye tracking and neuroimaging techniques to study developer cognition. Her work spans program comprehension, code review, requirements engineering, and the impact of human factors on software development processes. She has developed methodological frameworks for conducting eye tracking studies in software engineering and has made notable contributions to understanding how visualization techniques affect software development tasks. NSERC Postdoctoral Fellowship NSERC Discovery Grant Program and Launch Supplements (Sep 2024-Sep 2029) IVADO Startup & Operation Fund (Jan 2022-Jan 2023) Scholarship for Doctoral Studies from Fonds de Recherche du Quebec Distinguished Reviewer Awards from IEEE ICPC 2020 and ACM FSE 2024 Dr. Sharafi actively mentors students including Mahta Amini (PhD Candidate, IVADO Scientifique en résidence 2024 Laureate), Cameron Cherif (PhD Candidate), Sara Yabesi (Master's Student), and Anthonia Njoku (Graduate research intern). She serves on numerous conference organizing committees including as Local Arrangement Chair for SANER 2025, Program Co-chair for SEMLA 2024, and as a reviewer for top-tier journals including IEEE Transactions on Software Engineering and ACM Computing Surveys. Her research is supported by multiple grants focused on understanding human factors in software engineering through empirical methods. At Polytechnique Montréal, Dr. Sharafi directs the SENSE Lab which brings together computer scientists, cognitive scientists, and software engineering researchers to investigate the cognitive aspects of software development. The lab employs advanced methodologies including eye tracking, functional near-infrared spectroscopy (fNIRS), and functional magnetic resonance imaging (fMRI) to study how developers comprehend, navigate, and modify software systems. Current projects examine trustworthiness perceptions in code review, the role of creativity in software engineering tasks, and gender differences in software development processes.
