Find Academic Supervisors

• Structural Bioinformatics
• Protein Structure Prediction
• Immunoinformatics
• +3 more

Professor Charlotte Deane is a leading academic in structural bioinformatics, holding the position of Professor at the University of Oxford's Department of Statistics and Executive Chair of the Engineering and Physical Sciences Research Council (EPSRC). She leads the Oxford Protein Informatics Group (OPIG), focusing on protein structure prediction, immunoinformatics, and AI-driven drug discovery. Her research integrates computational methods with biological insights, developing tools widely used in academia and industry. Prior roles include Head of the Department of Statistics, Deputy Head of the Mathematical, Physical and Life Sciences (MPLS) Division at Oxford, and Chief Scientist of Biologics AI at Exscientia. During the COVID-19 pandemic, she served on SAGE and as UKRI's COVID-19 Response Director. In 2022, she was awarded an MBE for her contributions to pandemic research. Her research group's work spans antibody design, T-cell receptor analysis, and small molecule discovery, with a focus on open-source software development. Current projects include advancing AI methods for protein structure prediction and therapeutic antibody engineering. Recent publications highlight innovations in computational drug design, antibody developability, and machine learning applications in structural biology.

Lifeng ZhouView profile

Assistant Professor

• Robotics
• Algorithms
• Combinatorial Optimization
• +4 more

Lifeng Zhou is an Assistant Professor in the Department of Electrical and Computer Engineering at Drexel University, where he leads the Zhou Lab focused on advancing robustness and reliability in multi-robot systems through integration of foundation models. His research addresses real-world challenges in environmental monitoring, disaster response, and urban mobility. Education PhD, Electrical and Computer Engineering, Virginia Tech, 2020 MS, Control Science and Engineering, Shanghai Jiao Tong University, 2016 BS, Automation, Huazhong University of Science and Technology, 2013 Research Focus Dr. Zhou's work integrates robotics, algorithms, game theory and machine learning to develop secure and scalable autonomous systems. Primary research thrusts include: Resilient multi-robot coordination in adversarial environments Large language model integration for robotic decision-making Game-theoretic resource allocation strategies Risk-aware planning for autonomous vehicles Publication Trends Recent work (2024-2025) demonstrates strong focus on large language model applications in multi-robot systems, with 12/15 articles exploring LLM integration for flocking, scene segmentation, and decision-making. Additional emphasis includes adversarial robustness in target tracking (5 articles) and autonomous driving applications (4 articles). Awards and Recognition Best Paper Award, WACV 2025 LLVM-AD Workshop Professional Service Associate Editor, ICRA Conference Editorial Board Laboratory Focus The Zhou Lab develops foundational algorithms for secure and scalable multi-robot systems, with current projects spanning environmental monitoring drones, disaster response coordination, and autonomous vehicle perception systems.

Xinjie (Cynthia) MaView profile

Assistant Professor

• Financial Accounting
• Corporate Disclosure
• Human Capital
• +3 more

Xinjie (Cynthia) Ma is an Assistant Professor in the Department of Accounting at the University of Iowa's Tippie College of Business. Previously, she held a Visiting Assistant Professor position at the University of Iowa in 2025. Her research bridges financial accounting with advanced technologies, focusing on corporate disclosure mechanisms, human capital valuation, and AI/NLP applications in capital markets. She earned her PhD in Accounting from Temple University in 2021. Research Expertise : Financial accounting, CSR strategy alignment, human capital analytics, and machine learning applications Publications : 2023 Review of Accounting Studies paper on CSR-performance alignment, 2022 The Accounting Review article on text-based investment opportunity sets Teaching : Instructed graduate Financial Statement Analysis at National University of Singapore (2021-2025), undergraduate Managerial Accounting at Temple University (2019) Academic Affiliation : Tippie College of Business Her recent work analyzes how textual disclosures in 10-K filings inform investment decisions and explores labor demand dynamics through real-time market data. Currently, she's developing machine learning models to predict startup innovation potential and examining managerial communication patterns in earnings calls. Email: xinjie-ma@uiowa.edu

Chien-Ming HuangView profile

Assistant Professor

• Human-Computer Interaction
• Robotics
• Artificial Intelligence
• +3 more

Dr. Chien-Ming Huang is the John C. Malone Assistant Professor in the Department of Computer Science at Johns Hopkins University. He leads the Intuitive Computing Laboratory and is affiliated with the Malone Center for Engineering in Healthcare, Laboratory for Computational Sensing and Robotics, Institute for Assured Autonomy, and Data Science and AI Institute. His research focuses on human-robot interaction, human-computer interaction, and artificial intelligence applications in healthcare and education. BS in Computer Science, National Chiao Tung University (2006) MS in Computer Science, Georgia Institute of Technology (2010) PhD in Computer Science, University of Wisconsin–Madison (2015) Postdoctoral Research, Yale University (2015-2017) Dr. Huang's work bridges human-robot interaction, robotics, and AI to develop technologies that enhance social, physical, and behavioral support for diverse populations. His research includes adaptive robot systems for autism intervention, aging care technologies, and explainable AI frameworks for medical decision support. Current projects focus on end-user robot programming, socially aware navigation, and conversational agents for health management. His publications span major venues like Science Robotics , HRI, CHI, and ICRA, with recent emphasis on robot error awareness, small talk in collaboration, and AI explanation design for healthcare. Dr. Huang has received numerous accolades including the NSF CAREER Award and John C. Malone Endowed Chair. 2022 NSF CAREER Award John C. Malone Endowed Chair 2013 RSS Best Paper Runner-Up 2012 Human-Robot Interaction Pioneer Dr. Huang mentors PhD, postdoctoral, and undergraduate researchers, emphasizing interdisciplinary collaboration and technical rigor. He serves as Associate Editor for ACM Transactions on Human-Robot Interaction and has organized key conferences including HRI and ICMI. His lab develops systems for robotic assistance in surgical training, home healthcare, and educational contexts.

HaoYu WangView profile

Assistant Professor

• Parameter-efficient Learning
• Data-efficient Deep Learning
• Natural Language Processing
• +4 more

HaoYu Wang is an Assistant Professor of Computer Science at SUNY Albany. His research focuses on parameter-efficient and data-efficient deep learning, particularly in natural language processing and machine learning, aiming to democratize AI access. He holds a Ph.D. from Purdue University's School of Electrical and Computer Engineering, a B.Eng. from the University of Electronic Science and Technology of China, and an MS from SUNY Buffalo. His work includes innovations like RoseLoRA (sparse low-rank adaptation for knowledge editing), LightLT (lightweight quantization for long-tail data), and FedKC (federated knowledge composition for multilingual NLU). He has received awards such as the Future Leaders in Data Science (2024) and Bilsland Dissertation Fellowship. Key research areas include parameter efficiency, cross-lingual NLU, and model fairness. Recent publications span topics like federated learning optimization, robust retrieval-augmented generation, and mitigating token overfitting in LLMs. He advises students on Ph.D. and intern roles, emphasizing CVs and research interests in applications.

John HastingsView profile

Professor

• Machine Learning
• Artificial Intelligence
• Natural Language Processing
• +5 more

Dr. John Hastings is a Professor in the Department of Computer Science at Dakota State University, part of the Beacom College of Computer & Cyber Sciences. With nearly 35 years of experience, he specializes in teaching and curriculum development in computer science, combining academic rigor with industry insights from his roles as an AI/ML engineer, team leader, and business owner. Education: Ph.D., Computer Science, University of Wyoming M.S., Computer Science, University of Wyoming B.S., Computer Science, University of Wyoming Research interests include machine learning, AI applications in natural language processing (LLMs), generative AI, computer vision, ecological/environmental AI, AI in games, and gamification in education. Recent publications focus on cybersecurity challenges, AI ethics, and insider threat detection. His work has been recognized with awards such as the AAAI’s Innovative Applications of Artificial Intelligence (IAAI) Award and an International IPM Award for Excellence related to the CARMA AI tool. Teaching emphasizes active learning and practical skills, including courses on programming, data structures, AI, and cybersecurity. He advocates for gamification in education to enhance student engagement and success.

Francesca GrisoniView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Drug Discovery
• +8 more

Francesca Grisoni serves as an Assistant Professor in the Department of Biomedical Engineering at Eindhoven University of Technology (TU/e), where she currently leads the Molecular Machine Learning team. She additionally holds appointments as an ICMS Core member and Associate Professor at EAISI (Eindhoven Artificial Intelligence Systems Institute), reflecting her cross-disciplinary role at the intersection of computational science and biomedical applications. Academic Background : Grisoni completed her Environmental Sciences degree and earned a Ph.D. in 2016 from the University of Milano-Bicocca, where her dissertation focused on interpretable machine learning for molecular property prediction. During doctoral studies, she conducted research at ETH Zurich's Department of Chemistry and Applied Biosciences and the U.S. EPA's National Center for Computational Toxicology. Ph.D., University of Milano-Bicocca, 2016 (Dissertation: Interpretable machine learning for molecular property prediction) Environmental Sciences, University of Milano-Bicocca Her research integrates artificial intelligence, chemistry, and biology to develop computational methods for drug discovery, emphasizing wet-lab experimental validation alongside algorithmic innovation. Key focus areas include overcoming activity cliffs in molecular machine learning, generative modeling for scaffold hopping, and AI-augmented decision-making in therapeutic development, with the ultimate goal of achieving 'better decisions faster' in drug discovery pipelines. Analysis of her recent 2025 publications reveals a concentrated trend toward chemical language models and generative deep learning frameworks, specifically addressing low-data drug discovery challenges through active learning and neural network architectures. These works bridge computer science with pharmacology, targeting bioactivity prediction, molecular representation, and enzyme design while maintaining strong ties to experimental validation. Scientific Awards : Lush Young Researcher Prize Early Career Award 2022 from the Dutch Royal Netherlands Academy of Arts and Sciences (KNAW) ERC Starting Grant (2022) Grants and Supervision : Dr. Grisoni secured the prestigious ERC Starting Grant in 2022 to advance her molecular machine learning research. Institutional records indicate she has supervised 7 students (as shown in TU/e's 'Supervised Work (7)' repository section), though specific names aren't provided in the source material. Her group maintains active industry collaborations, including past engagement with Bracco Pharmaceuticals. Laboratory and Team : The Molecular Machine Learning team operates under the ICMS and EAISI frameworks, merging computational AI development with experimental wet-lab validation. This collaborative unit focuses on fragment-based molecular design, chirality representation (evidenced by fragSMILES work), and high-throughput nanoparticle identification using machine learning, as highlighted in recent press coverage and datasets.

• System Infrastructure for Big Data Processing
• High-Performance Computing (HPC)
• Storage Systems
• +5 more

Dr. Song Jiang is a Professor in the Department of Computer Science and Engineering at The University of Texas at Arlington (UTA). He holds a PhD from the College of William and Mary (2004) and has held academic positions at institutions such as Wayne State University and Los Alamos National Laboratory. His research focuses on system infrastructure for large language models (LLMs) and big data processing, including GPU/CPU memory systems, file and storage systems, and high-performance computing (HPC) I/O systems. He has received significant funding from the National Science Foundation (NSF) and industry partners like VMware and Tencent. Education: B.S. and M.S. from University of Science and Technology of China (1993, 1996), Ph.D. in Computer Science from College of William and Mary (2004). Postdoctoral research at Los Alamos National Laboratory (2004–2006). Research interests include file and storage systems, data management, big data analytics, and optimizing computing architectures for AI/ML. Key contributions include the LIRS replacement algorithm (adopted in MySQL and NetBSD), CLOCK-Pro page replacement (used in Linux), and swap token algorithms (Linux kernel). Awards include the 2022 ACM SIGMETRICS Test of Time Award and 2009 NSF CAREER Award. His work has led to 15+ patents and impactful industry collaborations with Facebook, Baidu, and others. Advising: Supervised 14+ PhD/Master’s students, including current advisees Chen Zhong and Sujit Maharjan. Active roles in doctoral committees and thesis supervision. Grants: Over $2.5M in NSF funding for projects like 'Software Defined Cache for Index Search' and 'Taming Small Data Writes'. Industry grants include VMware’s $240K project on distributed key-value storage. Labs/Teams: Leads research on persistent memory systems, key-value stores, and LLM infrastructure through UTA’s CSE department and collaborations with industry partners.

Sean ReardonView profile

Professor

• Social Inequality
• Educational Inequality
• School Segregation
• +6 more

Sean Reardon is the endowed Professor of Poverty and Inequality in Education at Stanford University's Graduate School of Education and Professor (by courtesy) of Sociology. He serves as Director of the Stanford Interdisciplinary Doctoral Training Program in Quantitative Education Policy Analysis and is a Senior Fellow at the Stanford Institute for Economic Policy Research. Reardon is also a member of the National Academy of Education and the American Academy of Arts and Sciences. His educational background includes an Ed.D. in Educational Administration, Planning, and Social Policy from Harvard Graduate School of Education (1997), M.Ed. from Harvard Graduate School of Education (1992), M.A. in International Peace Studies from University of Notre Dame (1991), and B.A. in Program of Liberal Studies with a minor in Honors Mathematics from University of Notre Dame (1986). Reardon's research investigates the causes, patterns, trends, and consequences of social and educational inequality, with particular focus on residential and school segregation and racial/ethnic and socioeconomic disparities in academic achievement. He develops methods for measuring social and educational inequality, including segregation and achievement gaps, and advances causal inference methods in educational research. His work has significantly shaped understanding of how poverty and school segregation impact educational outcomes across America. Analysis of Reardon's 15 most recent publications reveals a consistent focus on educational inequality, with particular emphasis on measuring achievement gaps, school segregation patterns, and the relationship between socioeconomic status and educational outcomes. His research increasingly utilizes large-scale administrative datasets, most notably the Stanford Education Data Archive (SEDA), which he developed based on 300 million standardized test scores to provide measures of educational opportunity across all U.S. public school districts. William T. Grant Foundation Scholar Award National Academy of Education Postdoctoral Fellowship Andrew Carnegie Fellow Member of the National Academy of Education Member of the American Academy of Arts and Sciences Reardon directs the Stanford Interdisciplinary Doctoral Training Program in Quantitative Education Policy Analysis, mentoring the next generation of education researchers. His work has been supported by major research grants that have enabled the development of the Stanford Education Data Archive, a groundbreaking resource that provides detailed metrics on educational opportunity across all U.S. public school districts. This archive has become a critical tool for policymakers and researchers seeking to understand and address educational inequality. As developer of the Stanford Education Data Archive, Reardon leads a significant research initiative that has transformed how educational opportunity is measured and understood across the United States. His work has established new methodologies for analyzing large-scale educational data and has provided policymakers with concrete evidence about the relationship between poverty, school segregation, and academic achievement.

• Hydrogeology
• Groundwater hydraulics
• Seepage flow
• +3 more

Dr. FARKAS Dávid is an Assistant Professor in the Department of Hydraulic and Water Resources Engineering, Faculty of Civil Engineering, Budapest University of Technology and Economics (BME). His office is located in Building K, basement level, room 12/7, and he holds weekly consultation hours on Mondays from 1–3 pm. Educational contributions include teaching core courses in hydrogeology and groundwater engineering: Groundwater (BMEEOVVMV63) Hydrogeology (BMEEOGMMG62) Infrastructural Design Project (BMEEODHAI41) Research activities concentrate on quantitative hydrogeology, with a special emphasis on karstic groundwater systems, seepage hydraulics, and the safety of flood-protection levees. He couples field investigations in iconic Hungarian cave systems (Buda Castle Cave, Molnár János Cave) with laboratory sandbox experiments and numerical modelling to advance understanding of flow and transport processes in fractured carbonates. Over the past decade his work has evolved from fundamental hydrogeological mapping toward the design and deployment of automated monitoring networks that integrate classical hydrological instruments with modern sensor technologies. This progression is evident in his most recent publications (2024-2025) that document the establishment of high-resolution cave monitoring systems capable of capturing rapid responses to precipitation events. Scientific awards currently listed: none. Advising and grants: no specific student names, grant numbers, or funded project titles are provided in the supplied text. Laboratories and teams: while no dedicated laboratory name is stated, his affiliation with the Department of Hydraulic and Water Resources Engineering implies access to the faculty’s hydraulics and hydro-environmental laboratories, including sandbox and seepage modelling facilities.

Alina LandowskaView profile

Assistant Professor

• Cultural Studies
• Discourse Analysis
• Cultural Evolution
• +3 more

Alina Landowska serves as Assistant Professor in the Department of Cultural Studies at the Faculty of Humanities, SWPS University of Social Sciences and Humanities in Warsaw. Her academic profile integrates cultural studies, computational linguistics, and ethics, with significant contributions to understanding moral foundations in digital discourse and technological futures. Her educational background includes degrees in Management and Economics from Gdańsk University of Technology and European Integration from the Pontifical University of John Paul II in Krakow, complemented by international scholarship experiences: SDG Academy (United Nations) Tantur Ecumenical Institute, Jerusalem (University of Notre Dame) Baltic University Program, Uppsala Swedish Institute of Environmental Research, Kalmar Royal Danish Student Fund, Copenhagen Landowska's research investigates cultural evolution through computational discourse analysis, focusing on morality-technology intersections. She pioneers text-mining methodologies to examine moral foundations in social media, anticipatory rhetoric in digital communication, and value-based management frameworks. Her work bridges humanities with data science, analyzing polarization mechanisms and proleptic cues in online environments while exploring cooperation ethics in business contexts. Recent publications demonstrate methodological innovation in mapping technological futures through sentiment/emotion analysis and moral-value detection systems. Her article corpus reveals consistent thematic threads: digital rhetoric analysis (particularly prolepsis functions), moral psychology applications in AI/social media, and cultural evolution studies linking cooperation theory with business ethics. This interdisciplinary approach positions her at the nexus of computational social science and humanistic inquiry. No scientific awards or prizes are documented in her current professional profile. As an educator, Landowska mentors students in discourse analysis methodologies and socio-economic media studies while serving as executive coach with EMCC Poland. Her research leadership extends to co-founding the Institute for Development think tank and representing Employers of Poland at the OECD's Business and Industry Advisory Committee (2016-2018). She previously held vice-presidential roles in the Polish Association of Businesswomen. Landowska maintains active research affiliations with the Humanistic Management Center (University of Lucerne), International Council for Small Business (George Washington University), and ArgDiaP association. Her 2022-2024 tenure with New Ethos Lab advanced dialogue studies in persuasion frameworks, complementing her current work on digital rhetoric's ethical dimensions.

• Epigraphy
• Classical Philology
• Neo-Latin Studies
• +2 more

Dr. Grzegorz Kotłowski serves as an Assistant Professor at the University of Gdańsk's Faculty of Languages within the Institute of Classical and Slavonic Studies, Division of Classical Philology. He concurrently holds the significant administrative position of Deputy Dean for Students Affairs at the Faculty of Languages, demonstrating dual expertise in academic scholarship and institutional leadership. His research centers on Classical Philology with intense specialization in Latin epigraphy, particularly the documentation and analysis of Neo-Latin inscriptions in historical churches of Gdańsk (notably St. Mary's Church) and Warmia (Frombork Cathedral). Dr. Kotłowski's work bridges philological rigor with historical contextualization, examining epitaphs, sepulchral plates, and commemorative texts from the early modern period to reconstruct social hierarchies, religious practices, and cultural identities within Gdańsk's multicultural urban landscape. His methodological contributions extend to digital approaches in Neo-Latin studies, addressing data acquisition and dataset creation challenges. Recent publications (2020-2022) reveal a highly focused epigraphic output, with over twenty articles detailing specific monuments while collectively forming a comprehensive corpus of Gdańsk's Latin funerary heritage. His collaborative multi-volume series with Elżbieta Starek— Łacińskie inskrypcje w kościołach Gdańska (covering Mariacka Basilica, Śródmieście, and Oliwa) and Łacińskie inskrypcje w kościołach Warmii (Frombork)—establishes foundational references for regional epigraphic studies. No scientific awards are documented in available sources. Administrative responsibilities as Deputy Dean for Students Affairs indicate active engagement in academic governance, though specific advising roles or grant funding remain unreported in current materials. The absence of laboratory or team descriptions suggests individual or small-collaboration research models centered on archival and field-based epigraphy.

Christopher Ernest OumaView profile

Associate Professor

• African Literature
• Postcolonial Studies
• Diaspora Studies
• +3 more

Christopher Ernest Ouma is an Associate Professor of English at Duke University's Trinity College of Arts & Sciences. He specializes in African literature, postcolonial studies, and diaspora studies with a focus on literary analysis of Cold War dynamics and Pan-Africanism. Ouma holds a Ph.D. (2011) and M.A. (2007) from the University of Witwatersrand, South Africa. Research Interests : His work examines intersections of diasporic identity, transnational literary networks, and historical memory in African fiction. Key themes include postcolonial spatiality, anti-apartheid intellectual movements, and the role of small literary magazines in shaping cultural discourse. Publications Trends : Recent work explores contemporary Nigerian author Yewande Omotoso's diasporic narratives and reinterprets Chimamanda Ngozi Adichie's portrayals of Biafran history. Earlier scholarship analyzed Cold War-era African literary networks and the evolution of African novel form. Professional Network : Maintains academic ties with North Carolina State University and University of Cape Town through institutional collaborations. Teaches courses on literature, African studies, and critical reading methodologies. Grants & Labs : No specific grants or research labs mentioned in provided materials. Active in editorial roles for journals like Social Dynamics and Black Scholar .

Rathna RamanathanView profile

Professor

• Communication Design
• Typography
• Intercultural Communication
• +5 more

Dr. Rathna Ramanathan is a leading academic and practitioner in intercultural communication and alternative publishing. Currently serving as Provost of Central Saint Martins and UAL Executive Dean for Global Affairs , she has previously held deanships at Central Saint Martins and the Royal College of Art. Based in London but originally from Chennai, India, her work bridges South Asian and global design practices. University of Reading - PhD in Typography and Graphic Communication Central Saint Martins - MA in Communication Design University of Madras - BA Fine Art Her research focuses on intercultural communication and alternative publishing in the Global South, examining how marginalized voices can be amplified through design. She explores the tension between tangible/intangible heritages and contemporary design, and investigates how form, media, and content interact in addressing social/political issues. Recent publications highlight her design research trends in decolonial publishing, critical typography, and intercultural book design. As a design educator , she emphasizes listening, cross-cultural learning, and sustainable practices. Her supervision includes postgraduate research students working on topics like female printers in India, exhibition design, and architectural lettering. Key scientific collaborations include major projects with Tara Books (international design awards), British Council-funded initiatives (Crafting Futures, Going Global Partnership), and the Murty Classical Library of India (Harvard University Press partnership). She consults on Indic typeface design with Adobe and Monotype. Her design lab at Central Saint Martins (M9Design) works with international networks of editors, translators, and type designers. Current team projects focus on digital/print transitions, bilingual typography, and preserving endangered typographic practices through innovative publishing formats.

Michel LarocheView profile

Professor

• Consumer Behavior
• Culture
• Social Media
• +7 more

Michel Laroche serves as Professor of Marketing and holds the Royal Bank Distinguished Professorship at Concordia University's John Molson School of Business. He maintains active research leadership through editorship of the Canadian Journal of Administrative Sciences and extensive scholarly contributions across global marketing domains. His educational background includes a Diplôme d'ingénieur from École Centrale de Paris, M.S.E. from Johns Hopkins, and M.Ph./Ph.D. from Columbia University, complemented by an honorary Doctor of Science from the University of Guelph. This multidisciplinary foundation underpins his research approach. Consumer behavior modeling Social media/digital marketing analytics Cross-cultural retailing dynamics Advertising effectiveness in global contexts Internet of Things consumer adoption Artificial intelligence in marketing systems His publication portfolio demonstrates consistent innovation in digital consumer behavior, with recent work examining social commerce cultural dynamics, TikTok authenticity metrics, and pandemic-driven media consumption patterns. Articles consistently integrate technological advancement with deep cultural analysis. Fellow of the Royal Society of Canada Recipient of the Jacques-Rousseau Medal for multidisciplinary research Living Legend of Marketing Award (HEC-Montreal) Hans B. Thorelli Award for international marketing research JBR Outstanding Associate Editor Award (namesake) Laroche has supervised 64 M.Sc. and 27 Ph.D. theses while securing major funding from SSHRC and FQRSC. His editorial leadership spans 16 years as Managing Editor of the Journal of Business Research and current Editor-in-Chief role at CJAS , establishing significant infrastructure for marketing scholarship. Professional service includes presidential roles in ASAC and AMS, plus extensive journal editorial board participation.