Find Academic Supervisors

Alexandre JacquillatView profile

Associate Professor

• Data-driven decision-making
• Stochastic optimization
• Integer optimization
• +6 more

Alexandre Jacquillat is the Maurice F. Strong Career Development Associate Professor and Associate Professor of Operations Research and Statistics at MIT Sloan School of Management. His research focuses on data-driven decision-making with applications in air traffic management, urban mobility, and decarbonization. He holds a PhD in Engineering and MS degrees from MIT and École Polytechnique. Education PhD in Engineering, MIT MS in Technology and Policy, MIT MS in Applied Mathematics, École Polytechnique Research Interests His work develops scalable optimization models for efficient, equitable, and sustainable operations. Key areas include stochastic optimization, large-scale systems design, and machine learning applications in transportation and public policy. Recent projects explore vertiport planning for urban aerial mobility and prescriptive analytics for pandemic response. Awards Harold W. Kuhn Award (2024) INFORMS Harvey Greenberg Research Award (2023) MIT Jamieson Prize for Excellence in Teaching (2023) Multiple INFORMS Best Paper Awards (2015-2023) Named Leading Academic Data Leader by Chief Data Officer Magazine (2021-2022) Teaching & Grants Teaches courses in optimization (15.093, 15.083) and analytics (15.072). His grants support work in robotic warehousing, air traffic scheduling, and disaster response logistics. Advises on transportation analytics for industry and government. Labs/Teams Leads MIT Sloan's operations research group, collaborating with industry partners like McKinsey & Co. and Booz Allen Hamilton on transportation analytics and optimization projects.

Allison KoeneckeView profile

Assistant Professor

• Algorithmic Fairness
• Computational Social Science
• Public Health
• +4 more

Allison Koenecke is an Assistant Professor of Information Science at Cornell Tech and a field faculty member in Computer Science at Cornell University. Previously, she was a postdoctoral researcher at Microsoft Research New England and completed her PhD at Stanford University’s Institute for Computational & Mathematical Engineering. Her research focuses on algorithmic fairness, computational social science, and causal inference in public health, addressing disparities in automated systems like speech recognition and policy decision-making. Education : PhD, Stanford Institute for Computational & Mathematical Engineering MA/MS, Stanford University BA/BS, Massachusetts Institute of Technology Research Interests : Dr. Koenecke’s work bridges economics and computer science, emphasizing equity in AI systems. Key areas include: Algorithmic bias in speech recognition (e.g., racial disparities in voice assistants) Fairness in policy tools like environmental justice data systems Causal analysis in public health interventions Ethical implications of large language models in education Media & Impact : Her research has been featured in outlets like New York Times , Science , and Scientific American . Notable studies include exposing racial gaps in speech-to-text systems and advocating for inclusive dataset development. She also explores societal impacts of AI in education and governance. Awards : Sloan Research Fellow in Computer Science Forbes 30 Under 30 in Science NSF Awards Cornell CIS Teaching Excellence Award (2024) Teaching & Outreach : She teaches courses like Designing Fair Algorithms and Data Science for Global Development , emphasizing interdisciplinary collaboration. Her PhD Professionalization course addresses hidden curricula in academia. She advises on AI ethics for nonprofits, tech companies, and government agencies.

Lauren A. DelisioView profile

Associate Professor

• Special Education
• Inclusive Education
• Autism Spectrum Disorders
• +5 more

Lauren A. Delisio is an Associate Professor of Special Education at Rider University's Department of Teacher Education. She has taught graduate and undergraduate courses in special education, inclusive practices, and assistive technology since 2015. Ph.D. in Exceptional Student Education (2015, University of Central Florida) Graduate Certificate in Autism Spectrum Disorders (2012, University of Central Florida) M.S. in Teaching (2005, Pace University) B.A. in Communications (2000, Rider University) Her research focuses on universal design for learning (UDL) , assistive technology , and inclusive education practices for students with autism spectrum disorders (ASD), attention deficit hyperactivity disorder (ADHD), and intellectual disabilities. She has explored trauma-informed instruction, STEM accessibility, and evidence-based practices in inclusive classrooms. Her recent publications analyze UDL implementation, video prompting for independence, and pandemic impacts on inclusive education. She has received grants through the Department of Education's Office of Special Education Programs (OSEP) for Project LEAD and served as a doctoral intern with OSEP. Delisio has contributed to STEM research via video game integration for students with disabilities and supported alumni engagement through data collection. She collaborates with service providers, universities, and policymakers to improve educational outcomes for neurodiverse learners.

Marcia BarnesView profile

Professor

• Cognitive Processes in Learning
• Learning Disabilities
• Reading Comprehension
• +7 more

Marcia Barnes is the Dunn Family Chair in Psychoeducational Assessment and a Professor of Special Education at Vanderbilt University's Peabody College, Department of Special Education. Her research focuses on understanding and addressing learning difficulties in reading comprehension and mathematics among children with neurodevelopmental disorders and those at risk for learning disabilities. Her research interests include: Cognitive and linguistic processes in reading and math disabilities Development of assessment tools for inferential comprehension Design and evaluation of interventions for early mathematics and reading comprehension Co-occurring reading and math disabilities Technology-assisted and combined cognitive-academic interventions Her work employs longitudinal studies, randomized controlled trials, and meta-analyses, and has been supported by federal funding from the Institute of Education Sciences (IES) and the National Institutes of Health (NIH). Her publications appear in top journals such as Scientific Studies of Reading , Journal of Educational Psychology , and Neuropsychology . Marcia Barnes is the author of numerous peer-reviewed papers, book chapters, and a widely used book on learning disability identification and intervention. She leads the Barnes Lab at Vanderbilt, which is dedicated to improving outcomes for children with or at risk for learning disabilities through rigorous research. Ph.D. in Psychology, McMaster University, 1988 Postdoctoral Fellowship, Research Institute, The Toronto Hospital for Sick Children, 1988–1991 She advises students and leads research teams in the Barnes Lab, focusing on innovation in assessment and intervention for learning disabilities. While specific advisees are not listed, her federally funded projects suggest active mentorship and collaboration. Her lab explores future directions in technology-enhanced learning and integrated cognitive-academic supports. The Barnes Lab conducts cutting-edge research on: Risk factors for co-occurring math and reading disabilities Intervention efficacy through randomized trials Development of novel assessment instruments Technology-assisted learning tools Longitudinal trajectories of learning difficulties

Ricardo SabatesView profile

Professor

• Educational Inequalities
• Quantitative Methods in Education
• Economics of Education
• +2 more

Ricardo Sabates is a Professor of Education and International Development at the University of Cambridge, affiliated with the Faculty of Education and the Research for Equitable Access and Learning (REAL) Centre . He is a Fellow at Hughes Hall and serves as Deputy Director of Research at the Faculty of Education. His career spans institutions including the University of Sussex, Institute of Education London, and Hughes Hall, Cambridge. PhD in Development (University of Wisconsin-Madison, USA) MSc in Economics (University of Wisconsin-Madison, USA) BA Honours (ITAM, Mexico) Ricardo is a development economist with expertise in educational inequalities , particularly in low-income countries. His work focuses on quantitative methods , maternal education impacts , and equity in educational access and learning . He collaborates with international agencies such as the OECD , UNICEF , UNESCO UIS , DFID , and the World Bank . His recent research trends include large-scale educational reform in Ethiopia , community-school participation in India , disability and learning outcomes , and teacher effectiveness in Africa . Projects often involve experimental/quasi-experimental designs and policy evaluation in Ethiopia, Ghana, India, Pakistan, Rwanda, and Tanzania. Ricardo also supervises postgraduate doctoral and masters students and contributes to core research training courses at Cambridge. He is actively involved in multiproject collaborations funded by the DFID-ESRC , MasterCard Foundation , and CAMFED , addressing topics like girls' secondary education , teacher effectiveness , and equity in educational interventions .

Ben ClarkeView profile

Professor

• Mathematics Education
• Educational Psychology
• Special Education
• +3 more

Dr. Ben Clarke is an Associate Professor and Department Head of Special Education and Clinical Sciences at the University of Oregon’s College of Education. His research focuses on mathematical development, assessment systems, and school-based interventions to support student achievement. He has led over 20 federally funded grants totaling ~$55 million, emphasizing early numeracy interventions and multi-tiered instructional models. Clarke’s work bridges theory and practice, with publications on mathematics instruction, assessment, and RTI frameworks. Education: PhD (2002), MA (2001) in School Psychology/Special Education from University of Oregon; BS (1997) in Psychology from Wabash College (Phi Beta Kappa). Research Interests: Mathematics intervention design and efficacy Early numeracy assessment Multi-tiered systems of support (MTSS) Technology in education Equity in mathematics education Publications highlight his focus on intervention fidelity, tiered models, and outcomes for students with learning difficulties. Awards include the AERA Special Education SIG Research Award and recognition for academic excellence. Grants and Advising: Principal Investigator on ~$55M in federal grants; advises graduate students in School Psychology and Special Education. His lab develops evidence-based tools like the KinderTEK iPad program and contributes to national practice guides (e.g., IES RTI for Mathematics). Labs/Teams: Leads research teams focused on early mathematics intervention and MTSS implementation, collaborating with schools and policymakers to scale effective practices.

Paul TaeleView profile

Academic

• Sketch Recognition
• Human-Computer Interaction (HCI)
• Artificial Intelligence
• +5 more

Paul Taele is an Instructional Assistant Professor and Deputy Lab Director in the Sketch Recognition Lab at Texas A&M University's Department of Computer Science & Engineering. He holds a Ph.D. (2019), M.S. (2010), and dual B.S. degrees in Computer Science and Mathematics from the University of Texas at Austin (2006). His research focuses on sketch recognition, haptics, and intelligent interfaces for education and accessibility, with notable work in mid-air gesture recognition, educational sketching tools, and assistive technologies for disabilities. He has contributed to projects like Kanji Workbook , Hashigo , and HaptiMoto , and has published over 50 peer-reviewed articles across venues like CHI, IUI, and AAAI. Taele has received awards including the NSF Student Travel Grant (2014) and Ford Foundation Honorable Mention (2015). He teaches courses in capstone design, programming, and sketch recognition, and mentors students across all academic levels through strict eligibility criteria for research collaborations. Education : Ph.D. Computer Science, Texas A&M University (2019) M.S. Computer Science, Texas A&M University (2010) B.S. Computer Science & Mathematics, University of Texas at Austin (2006) Concentration in Mandarin Chinese, National Chengchi University (2007) Research Interests : Taele's work bridges HCI and AI to create accessible educational interfaces. His projects emphasize: Sketch Recognition : Developing algorithms for mid-air gestures, children's developmental assessments, and language learning Accessibility : Haptic systems for visually impaired learners and algebra education Educational Tech : Intelligent tutoring systems for music, math, and East Asian languages Awards & Grants : EAAI-20 Travel Grant (2020) Ford Foundation Dissertation Honorable Mention (2015) NSF East Asia-Pacific Summer Institutes (2013, 2012) Royce E. Wisenbaker Fellowship (2009) Lab & Teams : Director of the Sketch Recognition Lab (SRL) and collaborator with global institutions like Singapore Management University and National Taiwan University. Active in organizing workshops like SketchRec at IUI conferences.

• Robust Statistics
• Dimension Reduction
• Meta-Analysis
• +3 more

Professor Luke Prendergast is the Deputy Dean of the School of Computing, Engineering & Mathematical Sciences (SCEMS) at La Trobe University (LTU) and holds a Professorship in the Department of Mathematics and Statistics. He previously served as Head of Department (2014–2020) and led LTU's Statistics Consulting Platform. His research focuses on robust statistics, meta-analysis, dimension reduction, and applied statistics, leading the DRAMA research group. Collaborations span fields like endocrinology, disability studies, and respiratory health. He actively contributes to research grants, including projects on Prader-Willi syndrome and exercise for disability populations. Professor Prendergast's recent work emphasizes statistical software development (e.g., the rquest package) and applications in biostatistics, such as metabolomics analysis and health intervention fidelity. His articles address topics like quantile-based hypothesis testing, geospatial accessibility for disability care, and motivational interviewing efficacy. Professional roles include NHMRC grant review panels, editorial boards for Nutrients and Respirology , and leadership in the Statistical Society of Australia (SSA Vic). His teaching includes courses in meta-analysis, linear models, and data-based critical thinking. Grants funded projects on exercise programs for cerebral palsy populations and community-university partnerships for disability inclusion. Luke's work bridges statistical theory with real-world health challenges, emphasizing robust methodologies and interdisciplinary collaboration.

Nenad RadakovicView profile

Associate Professor

• STEM Education
• Transdisciplinary Learning
• Mathematics Education
• +5 more

Nenad Radakovic is an Associate Professor of STEM Education at Queen's University's Faculty of Education. His research focuses on transdisciplinary approaches in mathematics and STEM education, emphasizing how interdisciplinary integration can enhance learning across PK-12 and post-secondary contexts. He holds a PhD in Curriculum Studies and Teacher Development from the Ontario Institute for Studies in Education (OISE), University of Toronto, and has taught secondary mathematics in Croatia and Canada. Prior roles include Associate Professor at the College of Charleston and Sessional Lecturer at the University of Toronto, where he instructed courses on holistic mathematics pedagogy and curriculum design. Dr. Radakovic’s research interests span transdisciplinary curricula, risk education, mathematics teacher training, and the role of technology in education. He is a STaR Fellow with the Association of Mathematics Teacher Educators and contributes to professional organizations like NCTM and PMENA. His work explores how mathematics education can address societal challenges through critical pedagogy and inclusive practices. Key publications include edited volumes on transdisciplinarity in mathematics education and borders in teacher training. His recent articles address STEM curriculum innovation, inclusive pedagogical frameworks, and the application of feminist theory to educational research. Collaborations include transdisciplinary projects blending arts and mathematics, such as using 3D printing to explore cultural heritage through art.

Maithilee KundaView profile

Associate Professor

• Artificial Intelligence
• Computational Cognitive Systems
• Visual Reasoning
• +3 more

Maithilee Kunda is an Associate Professor in the Department of Computer Science and Computer Engineering at Vanderbilt University's School of Engineering. She leads the Laboratory for Artificial Intelligence and Visual Analogical Systems and co-leads the Vanderbilt Initiative for Autism, Innovation, and the Workforce. Her research focuses on AI-driven cognitive systems, particularly visual reasoning and technology applications for neurodiverse populations, including autism spectrum disorder. Dr. Kunda holds a B.S. in Mathematics with Computer Science from MIT (2007) and a Ph.D. in Computer Science from Georgia Tech (2013). She was honored as an MIT Technology Review Innovator Under 35 in 2016 for her groundbreaking work. Her research bridges computational models of visual thinking and real-world impact, emphasizing neurodiverse cognition. Notable projects include developing AI systems for autism-related social skills interventions, designing visual analogy problem-solving frameworks, and advancing nonverbal communication understanding in AI. Her work addresses challenges in abstract reasoning tasks (e.g., Raven's Matrices), visual imagery-based learning, and ethical AI integration. She advocates for inclusive technology design, leveraging both generative AI and cognitive principles to create human-centered solutions. Key awards: MIT Technology Review Innovator Under 35 (2016) Her labs focus on practical AI applications for education, healthcare, and workforce development, emphasizing interdisciplinary collaboration between engineering, psychology, and neuroscience.

Janick EdingerView profile

Professor

• Distributed Operating Systems
• Edge Computing
• Computation Offloading
• +7 more

Prof. Dr. Janick Edinger is a Professor of Distributed Operating Systems at the Department of Informatics, Faculty of Mathematics, Informatics and Natural Sciences, University of Hamburg, Germany. He leads a research group focused on distributed, context-aware, and adaptive computing systems, with a strong emphasis on edge computing, computation offloading, and assistive technologies. Education: PhD in Computer Science, University of Mannheim Studies at National Taiwan University Studies at University of Alberta, Canada Research stays at University of British Columbia, Hong Kong Polytechnic University, and Georgia State University, USA His research explores how edge computing and computation offloading can enable efficient, privacy-preserving processing of sensor and video data close to their sources, particularly in dynamic environments. He investigates the integration of autonomous and heterogeneous systems—such as drone fleets and mobile devices—into scalable middleware platforms for real-time monitoring and decision-making in logistics and industrial operations. His work also emphasizes societal impact, contributing to accessible routing, adaptive interfaces, and crowd-sourced mapping. The recent publications reflect a strong trend in edge computing, federated learning, privacy-preserving analytics, and assistive technologies. Topics include WebAssembly-based offloading, emotion prediction via eye tracking, real-time traffic detection, and predictive maintenance in Industry 4.0, showcasing a blend of foundational systems research and applied human-centered computing. Scientific Awards: PerCom 2021 Mark Weiser Best Paper Award Best Paper Award at IEEE PerCom 2021 for 'Voltaire: Precise Energy-Aware Code Offloading Decisions with Machine Learning' Prof. Edinger actively advises students and leads research projects involving grants and collaborations. His team includes PhD candidates and researchers working on middleware, edge systems, and context-aware applications. He has served on conference program committees, such as shadow PC member for EuroSys 2021, and publishes in top venues including IPDPS, PerCom, CHIIR, and COMPSAC. Labs and Teams: He leads the Distributed Operating Systems research group at the University of Hamburg, where he mentors students and collaborates on projects involving edge computing, IoT, and adaptive systems.

R. Luke DuBoisView profile

Associate Professor

• Digital Media
• Human Computer Interaction
• Cyber Physical Systems
• +3 more

R. Luke DuBois is an Associate Professor and Co-Chair of the Technology, Culture and Society Department at the NYU Tandon School of Engineering, where he also directs the Integrated Design & Media program and the Brooklyn Experimental Media Center. He holds a DMA in music composition from Columbia University and is a renowned artist, composer, and performer whose work explores intersections between technology, sound, and visual media. His research focuses on digital media, human-computer interaction, and emerging technologies applied to artistic expression and accessibility. Key roles include directing the SONYC initiative (addressing urban noise pollution via AI) and leading the NYU Ability Project (advancing disability studies through technology). He has collaborated with institutions like the Smithsonian and artists such as Maya Lin, and his work has been exhibited globally, including at the Sundance Film Festival and the Aspen Institute. DuBois co-developed the Jitter software suite for real-time data manipulation and performs in avant-garde groups like Bioluminescence and Fair Use. His artistic practice combines time-lapse phonography, interactive installations, and interdisciplinary projects that critique cultural ephemera while advancing accessibility in STEM and the arts. Recent contributions include browser-based tools for accessible music notation (SoundCells) and sonification techniques for calculus education. He serves on the Board of the ISSUE Project Room and has been featured in major publications like the New York Times and TED Conference talks.

Garvin BrodView profile

Research Professor

• Educational Psychology
• Cognitive Development
• Memory and Learning
• +9 more

Prof. Dr. Garvin Brod is a Research Professor at the DIPF | Leibniz Institute for Research and Information in Education and Goethe University Frankfurt, specializing in individualized learning and cognitive development. He is affiliated with the Department of Educational Psychology within the College of Psychology & Sports Science. His research focuses on technology-supported educational interventions, memory and learning dynamics, and the development of knowledge acquisition processes. Brod leads projects like ACHILLES (learning success diagnostics), PROMPT (digital prompting techniques), and VokSi (vocabulary learning), addressing self-regulated learning, reading education, and cognitive strategies. The 13 most recent publications highlight trends in educational technology, self-regulated learning mechanisms, and cognitive development. Key themes include mobile learning interventions, memory retention strategies, and the role of executive functions in belief revision. Brod’s work bridges experimental psychology with practical EdTech solutions for children’s learning challenges. As a visiting fellow at St John's College, University of Cambridge, and head of DIPF’s departments for Individualized Support and Education and Development, Brod collaborates on data-sharing initiatives like ShaReD. He holds a doctorate from Humboldt University and a diploma in psychology from Saarland University.

Michael C. RodriguezView profile

Professor

• Educational Measurement
• Test Development
• Measurement Accessibility
• +5 more

Michael C. Rodriguez is the Dean of the College of Education and Human Development (CEHD) at the University of Minnesota and holds the Campbell Leadership Chair in Education and Human Development. He has been a professor of measurement at CEHD since 1999. Education: PhD in Measurement & Quantitative Methods (Michigan State University), MA in Public Affairs (University of Minnesota Twin Cities), BA in Psychology (University of Minnesota Morris) His research focuses on test development , measurement accessibility , social-emotional learning assessment , and psychometric meta-analysis . He pioneered the use of item response models to evaluate equity in testing for students with disabilities and English language learners. Recent publications emphasize fairness in assessment , longitudinal SEL measurement , and foundational competencies in educational measurement . His work bridges psychometrics with socio-cultural youth development contexts. Scientific Awards: All My Relations Equity in Action Award (2022), C. Eugene Allen Award (2019), Robert H. Beck Teaching Award (2008) He chairs the Technical Advisory Group of the National Board of Professional Teaching Standards and contributes to the revision of the Standards for Educational and Psychological Testing . As founding director of the Minnesota Youth Development Research Group, he explores measurement frameworks for educational equity and youth wellbeing.

Brenna D. ArgallView profile

Associate Professor

• Robotics
• Rehabilitation Engineering
• Human-Robot Interaction
• +3 more

Brenna D. Argall is an Associate Professor of Computer Science, Mechanical Engineering, and Physical Medicine & Rehabilitation at Northwestern University, and a Faculty Research Scientist at the Shirley Ryan AbilityLab. Her research focuses on assistive and rehabilitation robotics, with an emphasis on human-robot interaction, shared autonomy, and intelligent control systems. She holds a PhD in Robotics from Carnegie Mellon University and has held postdoctoral fellowships at EPFL (Switzerland) and the NIH. Education: PhD in Robotics, Carnegie Mellon University (2009) Postdoctoral Fellow, EPFL (2009–2011) B.S. in Mathematics, Carnegie Mellon University (2002) Affiliations: Director, Argallab (Assistive & Rehabilitation Robotics Laboratory) Member, Northwestern Center for Robotics and Biosystems Advisor, Northwestern MS in Robotics Program Her research explores dynamic autonomy allocation , shared control systems , and interface-aware robotics , with applications in rehabilitation and assistive devices. Key projects include wheelchair automation, robotic arm control, and body-machine interfaces for users with motor impairments. Research Highlights: NSF CAREER Award (2016) AIMBE Fellow (2020) "40 under 40" Innovator (Crain’s Chicago Business) Publications emphasize human-centered robotics, including over 50 peer-reviewed articles on topics like intent inference, assistive autonomy, and teleoperation assistance. Current lab efforts prioritize interface-aware systems and customizable shared control to enhance accessibility for users with disabilities.