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Yao-Zhong LiuView profile

Associate Professor

• Next-generation sequencing data analysis
• Single-cell and bulk RNA-seq
• Spatial transcriptomics
• +5 more

Dr. Yao-Zhong Liu is an Associate Professor in the Department of Biostatistics and Data Science at Tulane University’s Weatherhead School of Public Health . With both an MD and a PhD, he brings deep biomedical insight to advanced statistical and computational methods for high-dimensional omics data, including next-generation sequencing, spatial transcriptomics, and digital pathology. Education & Training Postdoctorate, University of Texas Health Science Center, Houston, TX (2006) PhD, Creighton University, Omaha, NE, USA (2005) MD, Capital University of Medical Sciences, Beijing, China (1993) Research Interests Dr. Liu’s laboratory focuses on the intersection of genomics, computational biology, and clinical medicine. He develops and applies cutting-edge statistical and machine-learning frameworks for: Next-generation sequencing – bulk and single-cell RNA-seq data to dissect cellular heterogeneity in liver and pancreatic diseases. Spatial transcriptomics – mapping gene expression within intact tissue microenvironments to understand tumor–immune interactions. Digital pathology – AI-driven image analysis for precision oncology and gastrointestinal pathology. Meta-genomics – integrative study of host and microbial transcriptomes in infectious and chronic diseases. Publication Themes Across more than 50 peer-reviewed publications since 2009, Dr. Liu’s work has consistently leveraged multi-omics datasets to uncover molecular mechanisms in cancer, infectious disease, and skeletal disorders. Recent emphasis (2022-2025) has shifted toward pancreatic ductal adenocarcinoma , hepatocellular carcinoma , and spatial tumor microenvironment remodeling after neoadjuvant therapy, integrating single-cell RNA-seq with clinical outcomes. Scientific Awards Tulane-Xavier Center for Bioenvironmental Research Faculty Fellowship (2016-2017) Alice L. Jee Memorial Young Investigator Award, 33rd International Sun Valley Hard Tissue Workshop (2003) Teaching & Mentorship Dr. Liu teaches core biostatistics and data-science courses such as SPHL 6050 Biostatistics for Public Health , BIOS 6290 Data Management and Statistical Computing , and BIOS 7400 Clinical Trials . While specific advisees are not listed in the provided materials, his sustained publication record and course offerings indicate active graduate-level mentoring. Laboratory & Collaborations Operating within the collaborative ecosystem of the Weatherhead School of Public Health, Dr. Liu’s group maintains strong ties to clinicians at Tulane’s School of Medicine and to national consortia focusing on gastrointestinal oncology and infectious disease genomics.

Eric CorwinView profile

Professor

• Soft Condensed Matter
• Granular Materials
• Jamming
• +3 more

Eric Corwin is a Professor of Physics at the University of Oregon, College of Arts and Sciences. He has been at UO since 2010, conducting research in soft condensed matter physics with a focus on granular materials, jamming, and non-equilibrium statistical mechanics. Education: Ph.D., University of Chicago, 2007 Corwin employs experimental, simulational, and theoretical tools to study complex systems arising from simple interactions. His work addresses fundamental questions in the glass transition, jamming, and the behavior of granular materials, with implications for material design and biophysics. Analysis of his recent publications (2021-2025) reveals three dominant themes: (1) extreme diffusion and outlier statistics in many-particle systems, (2) mechanical stability of ultra-low density sphere packings (Dionysian packing), and (3) scaling relations in jamming critical phenomena, including high-dimensional prefactors. Leading the CORWIN LAB, Corwin explores how simple interactions generate complex behavior. Current projects include Dionysian Packing for lightweight materials, Extreme Diffusion frameworks for environmental fluctuations, and computational studies of jamming in high dimensions.

Gaurav MahajanView profile

Lecturer

• Machine Learning Theory
• Quantum Learning Theory
• Reinforcement Learning
• +3 more

Gaurav Mahajan serves as a Postdoctoral Associate in Yale University's Department of Computer Science under Dan Spielman's mentorship, concurrently holding lecturer appointments for specialized courses including CPSC 648: Quantum Codes (Fall 2024) and the ICTS Reinforcement Learning Theory Bootcamp (Fall 2025). His academic journey includes a PhD from UCSD's Theory Group advised by Sanjoy Dasgupta and Shachar Lovett, with research summers at Microsoft Research, Institute for Advanced Study, and Simons Institute. His research spans machine learning theory with dual emphases on quantum learning (quantum error correction applications to complexity theory) and reinforcement learning (computational-statistical gaps, sample complexity). Recent publications in COLT, ALT, and NeurIPS reveal a trajectory from foundational PAC learning theory toward quantum-enhanced complexity analysis, featuring collaborations with leading theorists including Sham Kakade, Shachar Lovett, and Daniel Kane. Teaching activities demonstrate specialized expertise: his Quantum Codes course progresses from basic stabilizer codes to quantum Tanner codes using chain complex formalisms, while the RL Bootcamp bridges PyTorch implementations with theoretical complexity analysis. Though not leading a formal lab, his work connects Yale's quantum initiative with theoretical computer science communities through institutes like Simons. Current research shows increasing focus on quantum-classical connections—applying quantum information tools (e.g., classical shadows) to classical learning problems—while maintaining rigorous theoretical standards evidenced by consistent publications in top theory venues. Future directions likely involve deeper quantum complexity applications and expanding the quantum-RL interface.

Catherine HardingView profile

Associate Professor

• Late Medieval and Early Renaissance Art
• Gothic Art and Architecture
• Medieval Cosmographical Drawings
• +4 more

Catherine Harding is an Associate Professor and Acting Associate Dean in the Department of Art History and Visual Studies at the University of Victoria. She holds a BA from McGill University and MA/PhD from University College London. Her career spans teaching roles at McGill University, Queen’s University (1992 and earlier), and the University of Victoria since 1992, with a focus on Medieval Studies and late medieval/early Renaissance art. Education: BA (McGill), MA/PhD (London) Affiliations: University of Victoria, Queen’s University, McGill University Her research explores Gothic Art and Architecture in Europe, medieval cosmographical diagrams, pilgrimage relics in Italy, and the material culture of doubt. She investigates how images functioned as information systems in pre-modern Europe and contributes to pre-modern feminist theory. Her teaching includes the capstone 4th-year course and AHVS Undergraduate Research Poster Fair. Her publications analyze text-image relations in works by Brunetto Latini and Francesco da Barberino, façade mosaics in Rome and Orvieto, and comparative Mediterranean material culture. Current projects examine doubt and belief in medieval Orvieto. She served as President (2005-2010) and Past President (2011) of the Universities Art Association of Canada (UAAC) and as Editor-in-Chief of RACAR (2012-2014). Scientific Awards: President, UAAC (2005-2010) Past President, UAAC (2011) Editor-in-Chief, RACAR (2012-2014) Editor, RACAR (2014-2016) Grants Facilitator, Faculty of Fine Arts (2009-2014)

• Theoretical Computer Science
• Computational Complexity
• Data Structures
• +3 more

Prof. Michal Koucký is a faculty member at the Institute of Informatics, Faculty of Mathematics and Physics, Charles University in Prague. His research focuses on theoretical computer science, particularly computational complexity, data structures, algorithms, and combinatorics. He leads significant research projects including EPAC (supported by GA CR) and LBCAD (funded by ERC). His educational background includes a Ph.D. from Rutgers University (2003) and a Master's degree from Charles University (1998). Prof. Koucký's research spans multiple areas of theoretical computer science with emphasis on computational complexity , data structures , algorithms , and combinatorics . His work explores fundamental questions about computational efficiency, lower bounds, and algorithmic techniques. He has made significant contributions to edit distance algorithms, string processing, and circuit complexity. His research often bridges theoretical foundations with practical algorithmic applications, particularly in areas like dynamic data structures and approximation algorithms. An analysis of his recent publications (2019-2024) reveals a strong focus on string algorithms, particularly edit distance problems. His work develops novel approximation techniques, sketching methods, and sublinear-time algorithms for pattern matching. There's also significant work on data structure lower bounds and connections to popular complexity conjectures. His research demonstrates a consistent pattern of tackling fundamental problems with innovative approaches that push theoretical boundaries while maintaining practical relevance. Antonin Svoboda award for best dissertation in 2014 (awarded to Jan Bulánek) Best paper award at SAGT 2016 for 'The Big Match in Small Space' Best paper award at FOCS 2018 for 'Approximating Edit Distance Within Constant Factor in Truly Sub-Quadratic Time' He has successfully advised numerous graduate students including Pavel Dvořák, Karel Král, Debarati Das, and Jan Bulánek who have gone on to positions at prestigious institutions like Bristol, Google (Zurich), and Penn State. His research is supported by significant grants including the EPAC project (GA CR) and LBCAD project (ERC), demonstrating the impact and relevance of his work in theoretical computer science. Prof. Koucký is an active member of the theoretical computer science community, regularly presenting at major conferences including STOC, FOCS, ICALP, and SODA. His work often involves collaborations with researchers from institutions worldwide, contributing to a vibrant research environment at Charles University's Institute of Informatics.

Martin WeichboldView profile

Associate Professor

• Empirical Social Research
• Cross-Cultural Research
• Data Quality
• +3 more

Martin Weichbold is an Associate Professor of Sociology and Empirical Social Research at the University of Salzburg, Austria. He serves as Vice Rector of Academic Affairs and holds leadership roles in international academic networks, including General Secretary of ISA RC 33 (Logic and Methodology of Sociology). His work bridges sociological theory with methodological innovation, focusing on data quality and cross-cultural research challenges. Studied sociology, political science, and psychology Expertise in empirical research methods and digital data analysis His research explores data quality in surveys, cross-cultural methodology, and social inequalities. Recent publications address Big Data classification, nursing home populations, and migrant sampling frameworks. He has contributed to interdisciplinary fields including healthcare, cultural studies, and historical social research. Notable roles include past presidency of the Austrian Sociological Association (2017-2019) and leadership in designing methodological solutions for hard-to-reach populations. He collaborates internationally through the International Sociological Association.

Boris MordukhovichView profile

Professor

• Variational Analysis
• Optimization
• Control Theory
• +2 more

Boris Mordukhovich serves as Distinguished University Professor of Mathematics at Wayne State University, where he leads groundbreaking research in variational analysis and optimization with significant theoretical and applied impact across engineering and medical fields. Education: Ph.D. in Applied Mathematics, Belarus State University, Minsk, Belarus Honorary Doctorates: National Sun Yat-sen University (Taiwan), Alicante University (Spain), University of Messina, Babes-Bolyai University (Romania), Vietnam Academy of Science and Technology, Vasile Goldis University (Romania) His research centers on variational analysis and optimization theory , specializing in generalized differential properties, convex/nonconvex optimization frameworks, and real-world applications including proton therapy treatment planning and energy exchange modeling. His theoretical contributions form foundational tools for modern optimization algorithms. Recent 2025 publications reveal continued innovation in differential properties of optimal value functions and multiobjective optimization for medical physics, demonstrating sustained leadership in bridging abstract mathematics with practical engineering solutions. Scientific Awards: Board of Governors Faculty Recognition Award, Wayne State University (2025) Inaugural ScholarGPS Highly Ranked Scholar in Mathematical Optimization (2024) Principal Lecturer, International School on Variational Analysis, China (2024) SIAM Fellow (2011), AMS Fellow (2012) Corresponding Member, Accademia Peloritana dei Pericolanti (2016) Foreign Member, National Academy of Sciences of Ukraine (2021) Multiple honorary doctorates from international institutions Secured major research funding including National Science Foundation grant DMS-22045519 (2022-2026) as Principal Investigator for "Variational Analysis: Theory, Algorithms and Applications" and Australian Research Council Discovery Project DP250101112 (2025-2028) as Principal Foreign Investigator for "Taming Hard Optimization in Measure Spaces for Modern Applications", reflecting sustained research leadership despite no student listings provided. Directs international research collaborations evidenced by 2024 lectures in China and upcoming 2026 workshops in Bulgaria and Chile, with active participation in global optimization communities through special journal issues and conference leadership.

Andrej KuznetsovView profile

Professor

• Semiconductor Physics
• Quantum Technology
• Solid-state Physics
• +5 more

Andrej Kuznetsov is a Professor of Solid-state Physics and Quantum Technology at the University of Oslo (UiO), Norway. He holds a PhD in Physics from the National Research Nuclear University (MEPhI, Moscow) and a Docent (habilitation) in Solid State Electronics from KTH Royal Institute of Technology (Stockholm). His research focuses on semiconductor materials, particularly defects in gallium oxide (Ga2O3), radiation phenomena, and functionalization of semiconductors via ion implantation. He has held visiting professorships at institutions including Korea University, Chinese Academy of Sciences, and Aix-Marseille Université. Education: PhD (1992, MEPhI), Docent (2000, KTH) Affiliations: Department of Physics, UiO; Co-founder of International Conference on Radiation and Emission in Materials (ICREM) Research Themes: Ga2O3 polymorphs, radiation tolerance, defect engineering, semiconductor devices Key Contributions: Pioneering work on self-assembly of Ga2O3 multilayers, defect annealing mechanisms, and quantum memory platforms His >220 publications span Nature Communications , Physical Review Letters , and Advanced Materials , with 4,900+ citations (h-index 36). He actively organizes conferences like ICDS and ICREM, and advises on radiation-resistant materials for energy and sensor applications. Current projects include GO-POW (gallium oxide power electronics) and QuTe (quantum emitters in semiconductors). His lab focuses on combining ion beam techniques with defect engineering to create next-generation semiconductor materials.

• Machine Learning
• Computational Neuroscience
• Natural Language Processing
• +3 more

Michael Hahn is a Tenure-Track Professor (W2) at Saarland University's Saarland Informatics Campus, directing the Language, Computation, and Cognition Lab (LaCoCo). He holds dual affiliations with the Department of Language Science and Technology and the Department of Computer Science. Hahn earned his PhD from Stanford University in 2022, advised by Judith Degen and Dan Jurafsky. Education: PhD in Computational Linguistics, Stanford University (2022) Research Interests: His work bridges machine learning and cognitive science, focusing on information processing in machines and the brain. Key areas include understanding transformer architectures, computational cognition, and the theoretical foundations of neural networks. He investigates how models like GPT-2 simulate human cognitive limitations, explores biases in perception, and develops methods for mechanistic interpretability. Recent Achievements: Best Paper Award at ACL 2024 for 'Why are Sensitive Functions Hard for Transformers?' Outstanding Area Chair at EMNLP 2024 Recipient of the Second Prize at ICML 2024's Mechanistic Interpretability Workshop Lab & Collaborations: The LaCoCo Lab focuses on advancing theoretical and applied research in NLP and machine learning, with recent work on chain-of-thought reasoning limits, state space models, and evolutionary pressures in word order.

Gaétane DeliensView profile

Professor

• Cognitive Neuropsychology
• Autism Spectrum Disorder
• Neurodevelopmental Disorders
• +5 more

Gaétane Deliens is a Professor of Cognitive Neuropsychology at the Faculty of Psychology, Université Libre de Bruxelles. She co-leads the interdisciplinary ACTE (Autism in Context: Theory and Experiment) research group, the first dedicated to autism in French-speaking Belgium. Her research focuses on communication impairments and language delays in neurodevelopmental disorders, particularly Autism Spectrum Disorder (ASD). Key Research Areas: Language acquisition in autism Sensory integration and pragmatics Sleep-dependent memory consolidation Neurocognitive mechanisms in communication disorders Methodological innovations for hard-to-test populations Labs: UR2NF (Neuropsychology and Physiological Research Unit) ACTE autism research group Her recent publications emphasize sleep's role in memory reconsolidation, theta-band brain connectivity in autistic children, and audiovisual integration challenges in nonverbal autistic populations. She employs novel methods to study low-functioning and motor-impaired individuals, expanding traditional autism research boundaries.

• Neurophysiology of speech and language processing
• Bilingual language development
• Pediatric language disorders
• +3 more

Karen Garrido-Nag, Ph.D., CCC-SLP, is an Associate Professor in the Department of Hearing, Speech, and Language Sciences at Gallaudet University. She directs the Developmental Neurolinguistics and Cognition Lab, focusing on neurophysiological mechanisms of language processing in bilingual and disordered populations. Her teaching spans pediatric language development, speech sound disorders, and clinical practicum training. Dr. Garrido-Nag has advised over 100 graduate students in Speech-Language Pathology and Audiology programs since 2008. Her research explores vowel discrimination in bilingual infants, ERP correlates of language processing, and bilingual assessment methodologies for deaf populations. Notable contributions include developing ASL-administered cognitive tests and advancing interprofessional clinical training models. She holds grants from the National Science Foundation (NSF) and Department of Education, supporting work on brain interfaces and bilingual clinical practices. Professional service includes leadership in the Council on Academic Programs in Communication Sciences and Disorders (CAPCSD), editorial roles for the Journal of the American Academy of Audiology, and global collaborations with institutions like the University of Santo Tomas in the Philippines. Her work emphasizes culturally-responsive practices for deaf and hard-of-hearing populations in educational and clinical settings.

Aleksei UdovenkoView profile

Researcher

• Symmetric Cryptography
• Cryptanalysis Techniques
• White-box Cryptography
• +4 more

Aleksei Udovenko is a post-doctoral researcher at the Laboratory of Algorithmics, Cryptology and Security (LACS) within the Security and Trust (SnT) interdisciplinary center and the Department of Computer Science (CSC) at the University of Luxembourg. His research focuses on symmetric cryptography, cryptanalysis techniques, and white-box cryptography, with notable contributions to projects like Equihash (a memory-hard proof-of-work scheme used in cryptocurrencies) and the SPARX family of lightweight block ciphers. Education: PhD in Cryptology under Prof. Alex Biryukov (2019), MSc from ITMO University (2013). Research Interests: Symmetric-key algorithms, cryptanalysis methodologies, white-box cryptography, blockchain technologies, and lightweight cryptographic primitives. He actively participates in information security competitions (CTFs) and collaborates on projects related to cryptocurrency protocols and hardware-software security. Recent Work: Authored/co-authored papers on cryptanalysis of ARX-based ciphers, LPN attacks in white-box settings, and secure obfuscation techniques. Notable publications include work on Equihash (NDSS 2016), SPARX (ASIACRYPT 2016), and advancements in meet-in-the-filter cryptanalysis techniques (SAC 2022, CHES 2023). Professional Affiliations: Member of the CryptoLUX research group, contributing to interdisciplinary projects at the University of Luxembourg. Involved in conferences such as CRYPTO, CHES, and FSE.

• Computer Systems
• Functional Programming
• Hardware Description
• +3 more

John O'Donnell is an Honorary Lecturer at the University of Glasgow's School of Computing Science. His research spans functional programming, hardware description languages, parallel computing, and computer science education, with notable applications in music technology. Key research areas: Functional approaches to hardware design and simulation Parallel data structures and algorithms for specialized architectures Programming misconception identification and pedagogical tools Computational modeling of musical performance techniques Publications demonstrate consistent innovation in applying functional programming paradigms to diverse domains, from circuit design to music pedagogy. Recent work focuses on educational aspects of computer systems and programming.

• Liquid Crystals
• Condensed Matter Physics
• Elasticity Theory
• +3 more

Epifanio Virga is a Professor in the Department of Mathematics at the University of Pavia, Italy. His research focuses on the mathematical modeling of condensed matter systems, particularly liquid crystals, with an emphasis on elastic phenomena, topological defects, and phase behavior. He leads the 'Mathematical Models for Condensed Matter' research group, applying advanced theoretical and computational methods to study soft materials. Virga's work bridges pure mathematics and applied physics, addressing challenges such as geometric frustration in nematic shells and the dynamics of chromonic liquid crystals. He has contributed extensively to understanding the interplay between molecular ordering, elastic energy, and external stimuli like light or confinement. His recent studies explore novel material behaviors, such as photoresponsive nematic elastomers and the mechanical properties of soft shells. Virga collaborates internationally, publishing in top journals and advancing interdisciplinary approaches in condensed matter physics.

Atakan AltınkaynakView profile

Associate Professor

• Additive Manufacturing
• Finite Element Analysis
• Mechanical Engineering
• +3 more

Atakan Altınkaynak is an Associate Professor in the Department of Mechanical Engineering at Istanbul Technical University (ITU), affiliated with the College of Engineering. His research focuses on additive manufacturing, finite element analysis, polymer processing, and vibration analysis. Key areas include Fused Deposition Modeling (FDM), fluid-structure interaction, and origami-inspired mechanical systems. Research Interests: Additive Manufacturing (3D Printing Technologies) Finite Element Analysis and Numerical Methods Mechanical Vibration and Dynamic Systems Polymers Extrusion and Material Processing Fluid-Structure Interaction Modeling Awards: Doctoral Finishing Fellowship (2010) İTÜ Bitirme Tasarım Projesi Birincilik Ödülü (2016) Lew Erwin Memorial Scholarship (2007) Advising/Grants: Supervised 23 research works and led 8 projects including: "FDM Yazıcılarda Çoklu Şerit Basımının Sayısal Analizi" (2023-2024) "Polimer-Metal Temas Yüzeylerinde Sürtünme Kaynaklı Gürültünün Sayısal Modellenmesi" (2018-2019) "Filament Beslemeli 3 Boyutlu Yazıcıların Performans Karakteristiğinin Belirlenmesi" (2017-2019) His work bridges computational modeling with experimental validation in advanced manufacturing and mechanical systems.