جست‌وجوی استاد و پژوهشگر

• Theoretical Computer Science
• Graph Algorithms
• Dynamic Algorithms
• +۷ مورد دیگر

Nicole Wein is an Assistant Professor in the Computer Science and Engineering Division of the Department of Electrical Engineering and Computer Science (EECS) at the University of Michigan, College of Engineering. Her research lies in theoretical computer science, focusing on graph algorithms, dynamic algorithms, parameterized algorithms, distributed algorithms, online algorithms, and fine-grained complexity. She is part of the Theory of Computation Lab and advises both PhD and undergraduate researchers. PhD, Massachusetts Institute of Technology (MIT), advised by Virginia Vassilevska Williams Postdoctoral Fellow, DIMACS Research Fellow, Simons Institute, UC Berkeley MS, Stanford University BS, Computer Science/Math, Harvey Mudd College Her research explores fundamental algorithmic questions in combinatorial settings, particularly how algorithms handle dynamic data, extract information efficiently (e.g., in linear time), and understand shortest path structures in graphs—especially directed ones. She investigates problems in distance estimation, spanners, hopsets, dynamic graph algorithms, and hardness of approximation. Her work combines theoretical depth with practical implications for algorithm design. The recent publications reflect a strong trend in fine-grained complexity and graph algorithm design, with a focus on proving tight bounds, developing efficient approximations, and understanding structural limitations in directed and dynamic graphs. Her work frequently appears in top venues such as STOC, FOCS, SODA, and ICALP, often in collaboration with leading researchers in the field. Scientific Awards and Recognition: Invited to special issue of SIAM Journal on Computing (SICOMP) (FOCS 2022 paper) Invited to Highlights of Algorithms (HALG) (FOCS 2022 paper) Invited to minisymposium at CANADAM (ESA 2022 paper) Work featured in Quanta Magazine Nicole Wein actively mentors students, including current PhD student Jubayer Nirjhor and former undergraduate researchers like Sam Hiken (now pre-doc at MIT). She has served on program committees for major conferences including SODA, FOCS, ICALP, and ITCS, and co-organized the DIMACS workshop on Modern Techniques in Graph Algorithms (2023). She also contributes to the academic community through outreach, such as her article offering reassurance to early-stage PhD students in theoretical computer science. She leads and participates in collaborative research groups and workshops, emphasizing supercollaboration and interdisciplinary communication in algorithms. Her lab fosters a strong research environment in theoretical computer science at the University of Michigan.

• Materials Handling
• Logistics
• Crane Dynamics
• +۳ مورد دیگر

Dr. Michael Kleeberger is a Researcher at the Chair of Materials Handling, Material Flow, Logistics (FML) at the Technical University of Munich, based at Boltzmannstr. 15 in Garching. He collaborates closely with Prof. Johannes Fottner and maintains an active research profile in crane dynamics and mechanical systems simulation. His research specializes in Materials Handling and Logistics with emphasis on Crane Dynamics, Flexible Multibody Systems, and Control Systems. He develops advanced models for hydraulic actuated cranes, focusing on dynamic behavior during hoisting, slewing, and trajectory operations using port-Hamiltonian formulations and geometrically exact beam theory. His work bridges theoretical mechanics with industrial applications in heavy machinery. Analysis of his 15 most recent publications reveals consistent focus on numerical methods for flexible crane structures, with growing emphasis on optimal control strategies (2020-2025). Key trends include port-Hamiltonian system applications, lunar crane feasibility studies, and vibration mitigation techniques for lattice boom and knuckle boom configurations across diverse operational scenarios. As part of FML, Dr. Kleeberger contributes to TUM's leadership in logistics engineering through industry-collaborative projects and fundamental research in material flow systems, maintaining the chair's reputation for excellence in mechanical dynamics and practical engineering solutions.

Konstantinos Karapiperisمشاهده پروفایل

استادیار

• Solid Mechanics
• Multiscale Modeling
• Data Science
• +۷ مورد دیگر

Konstantinos Karapiperis is a Tenure Track Assistant Professor at EPFL's Laboratory of Multiscale Modeling of Materials (LMD), within the School of Architecture, Civil and Environmental Engineering (ENAC). His research integrates mechanics , multiscale modeling , and data science to study geomaterials and structural materials. PhD in Applied Mechanics (minor in Applied Mathematics), Caltech Postdoctoral Researcher & Lecturer, ETH Zürich (Marie Skłodowska-Curie Fellowship) Research focuses on granular materials , architected materials , and nonlocal modeling using techniques like Level-Set Discrete Element Method (LS-DEM) and machine learning . Recent work explores fracture control via graph neural networks and thermodynamics-informed models. Selected scientific award: Marie Skłodowska-Curie Fellowship Teaches courses in Soil Mechanics and Multiscale Modeling . PhD students include Thomas Henzel and Hrishikesh Gopakumar Menon. His Data-Driven Mechanics Laboratory (LMD) develops predictive tools for granular and structured material behavior.

Zohreh Sharafiمشاهده پروفایل

استادیار

• Software Engineering
• Human Aspects of Software Engineering
• Gender Studies in Software Engineering
• +۷ مورد دیگر

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.

Scott Michael Olsonمشاهده پروفایل

استاد

• Geotechnical Engineering
• Earthquake Engineering
• Soil Mechanics
• +۵ مورد دیگر

Scott Michael Olson is a Professor in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign, with a 0% affiliate appointment in the Department of Geology. He holds roles as Associate Head and Director of Graduate Studies. His academic journey includes a B.S., M.S., and Ph.D. in Civil Engineering from UIUC (1993, 1995, 2001). Prior to academia, he worked in private practice with firms like Woodward-Clyde Consultants and URS Corporation, while also teaching at the University of Missouri-Rolla. Dr. Olson specializes in geotechnical engineering, focusing on geohazard identification, liquefaction engineering, laboratory testing, and paleoseismology. He teaches courses in geotechnical engineering, including CEE 380, CEE 484, and graduate-level topics like rock mechanics. His research emphasizes practical applications in infrastructure resilience, with notable contributions to understanding soil behavior under seismic loads and tailings material dynamics. Dr. Olson has been recognized with prestigious awards, including the Walter L. Huber Prize (2012), NSF CAREER Award (2009), and Arthur Casagrande Award (2004). He actively contributes to professional organizations such as the American Society of Civil Engineers and the Earthquake Engineering Research Institute, and has served on national review panels for NSF and USGS. His consulting work bridges academic research with industry challenges in geotechnical risk mitigation.

Kevin Mackieمشاهده پروفایل

استاد

• Structural Engineering
• Bridge Engineering
• Performance-Based Engineering
• +۷ مورد دیگر

Kevin Mackie is Professor and Chair of the Department of Civil, Environmental and Construction Engineering (CECE) at the University of Central Florida’s College of Engineering. He has been a faculty member since 2006, advancing from assistant to full professor, and previously served as associate chair and interim department chair. His leadership includes spearheading departmental improvements in culture, workload policy, and digital accessibility. Education: Ph.D. in Civil Engineering, University of California, Berkeley (2004) M.S. in Civil Engineering, University of California, Berkeley (2000) B.E. in Engineering, Cooper Union, New York (1998) His research focuses on structural engineering , particularly in bridge engineering , performance-based seismic design , nonlinear analysis , and advanced materials for infrastructure repair . He integrates analytical, numerical, and experimental methods to assess and improve the resilience of civil infrastructure under extreme loads. His work addresses critical challenges in soil-structure interaction, seismic retrofitting, and the use of composites and smart materials. The 15 most recent publications reflect a strong emphasis on nonlinear modeling , seismic performance , and computational structural analysis of bridges and tall buildings. Key themes include fiber-based modeling, contact-friction problems, soil-structure interaction, and probabilistic assessment, demonstrating a consistent trajectory toward resilient and sustainable infrastructure systems. Scientific Awards: Faculty advisor of the year (2022, 2021, 2019) – ASCE East Central Branch and Florida Section Technical Contribution Leader Award Winner (2021) – ASCE East Central Branch Distinguished faculty member at UCF (2018) – Department of Housing and Residence Life Arthur N.L. Chiu Award for excellence as faculty advisor (2018) – Chi Epsilon Honor Society Mackie has been a dedicated mentor, supervising 11 doctoral , 18 master’s , and over 30 undergraduate students . His research has been funded by the National Science Foundation , U.S. Department of Transportation , Caltrans , FDOT , and industry partners. He has published nearly 200 papers and been cited over 7,000 times. He led the reaccreditation of CECE’s undergraduate programs and established the accelerated bachelor’s-to-master’s pathway. He leads the Structures Laboratory at UCF and collaborates with multidisciplinary teams on infrastructure resilience. His vision includes expanding graduate programs, strengthening industry partnerships, and diversifying the Senior Design curriculum to reflect real-world engineering challenges.

Artur Czumajمشاهده پروفایل

استاد

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Randomized Algorithms
• +۹ مورد دیگر

Artur Czumaj is a Professor in the Department of Computer Science at the University of Warwick and serves as the Director of the Centre for Discrete Mathematics and its Applications (DIMAP). He is a member of the Division of Theory and Foundations (FoCS) and holds affiliations with the Alan Turing Institute, the Warwick Data Science Institute (WDSI), and the Warwick Centre for Doctoral Training in Mathematics of Real-world Systems (MathSys). Previously, he served as Head of Department and President of the European Association for Theoretical Computer Science (EATCS) from 2020 to 2024. His research lies at the core of theoretical computer science, focusing on the design and analysis of algorithms, particularly randomized, sublinear, parallel, and distributed algorithms. His work spans graph theory, combinatorics, computational geometry, algorithmic game theory, and property testing. He has led major research initiatives funded by EPSRC, IBM, the Royal Society, and Weizmann-UK grants. The trends in his recent publications highlight a strong emphasis on sublinear algorithms, dynamic graph algorithms, and property testing, with recurring themes in randomized methods, graph processing, and efficient data structures. His work bridges foundational theory with applications in data summarization, network analysis, and computational geometry. EPSRC grants: EP/D063191/1, EP/G064679/1, EP/G069034/1, EP/J021814/1, EP/N011163/1, EP/V01305X/1, EPSRC studentship IBM Faculty Award Royal Society International Exchanges Scheme Weizmann-UK Making Connections Grants on combinatorial and algorithmic primitives and the interplay between algorithms and randomness Peter Davies received the 2020 Warwick Faculty of Science Thesis Prize under his supervision Artur Czumaj has supervised numerous PhD students, including Anna Adamaszek, Michal Adamaszek, Sam Coy, Peter Davies, Michail Fasoulakis, Jan Hladky, Wang Xin, and Hairong Zhao. His research has been supported by sustained grant funding, reflecting his leadership in theoretical computer science. He has organized major workshops at Dagstuhl, Oberwolfach, Simons Institute, and the University of Warwick, and has served on the steering committees of HALG and as PC Chair for SODA 2018 and ICALP 2020. He is actively involved in organizing key research events, including the Simons Institute Special Semester on Sublinear Algorithms (2024), the Workshop on Sublinear Graph Simplification (2024), and the Computational Complexity Conference (CCC 2023) at Warwick. He also co-organizes the Warwick-Weizmann workshops and the IGAFIT Algorithmic Postdocs Workshop, fostering international collaboration in algorithms research.

• Earthquake Engineering
• Structural Dynamics
• Seismic Risk Assessment
• +۳ مورد دیگر

Prof. Dr. Hakkı Polat Gülkan is a Professor at Başkent University's Civil Engineering Department. With a PhD (1971) and Master's (1968) from the University of Illinois in Civil Engineering and a Bachelor's (1966) from METU, his career spans over five decades in earthquake engineering, structural dynamics, and disaster management. PhD: University of Illinois, Civil Engineering (1971) Master's: University of Illinois, Civil Engineering (1968) Bachelor's: Middle East Technical University, Civil Engineering (1966) His research focuses on seismic risk assessment, structural behavior under extreme loads, and disaster mitigation strategies. Key contributions include earthquake simulator development, ground motion analysis, and retrofitting techniques for masonry and reinforced concrete structures. He has published extensively on deformation limits, response spectra, and historical building preservation. Recent work includes 15+ articles from 2024-2012 analyzing Istanbul's seismic hazards, Marmara region dynamics, and post-earthquake structural integrity. Conference papers address Turkey's endemic building vulnerabilities and deformation thresholds for seismic isolation systems. Scientific Achievements: Elected to U.S. National Academy of Engineering (2023) As an active journal reviewer for 13+ publications (2023-2024), he contributes to advancing earthquake engineering discourse. His teaching portfolio includes advanced structural analysis, concrete mechanics, and seismic design courses.

• Theoretical Computer Science
• Graph Algorithms
• Lower Bounds
• +۷ مورد دیگر

Nicole Wein is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan, where she is a member of the Theory of Computation Lab within the Computer Science and Engineering Division. Her research focuses on theoretical computer science, particularly graph algorithms and lower bounds across various domains including distance-estimation, dynamic, parameterized, distributed, and online algorithms. Education: PhD in Computer Science from MIT, advised by Virginia Vassilevska Williams Master's in Computer Science from Stanford University B.S. in Computer Science/Mathematics from Harvey Mudd College Nicole's research centers on theoretical aspects of graph algorithms and computational complexity. She investigates fundamental questions about how algorithms can efficiently handle changing data, extract information from graphs in linear time, and understand the structure of shortest paths, especially in directed graphs. Her work spans multiple algorithmic paradigms including dynamic algorithms that adapt to changing inputs, parameterized approaches for hard problems, and fine-grained complexity that establishes precise relationships between problem difficulty. Analysis of Nicole's recent publications reveals a strong focus on graph algorithms, particularly shortest path problems, spanners, and hardness results. Her work often bridges theoretical insights with practical implications, developing novel techniques for distance estimation, dynamic graph processing, and approximation algorithms. A significant portion of her research examines the structural properties of graphs that enable or constrain efficient computation, with applications across computer science. Nicole actively mentors students at various levels. She currently advises PhD student Jubayer Nirjhor and has worked with undergraduate researchers including Sam Hiken (now a pre-doc at MIT), Michael Wang, and Tony Zhang. Her teaching includes foundational courses like EECS 376: Foundations of Computer Science and specialized courses such as EECS 598: Graph Algorithms. Nicole contributes to the academic community through service as a program committee member for major conferences including SOSA 2025, FOCS 2025, SODA 2025, and others. She co-organized the June 2023 DIMACS workshop on Modern Techniques in Graph Algorithms and previously organized Algorithms Office Hours at MIT to improve communication between theory and applications of algorithms.

Shima Nazariمشاهده پروفایل

استادیار

• Dynamics and Control
• Powertrain Electrification
• Hybrid Electric Vehicles
• +۴ مورد دیگر

Shima Nazari is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at the University of California, Davis. Her research focuses on dynamics and control with applications to transportation systems, energy systems, and electrified/automated vehicles. She leads the CORE Lab, exploring advancements in hybrid powertrains, autonomous vehicle control, and energy-efficient systems. Education: Ph.D., Mechanical Engineering, University of Michigan (2019) M.S., Electrical Engineering, University of Michigan (2016) M.S., Mechanical Engineering, Sharif University of Technology, Iran (2012) B.S., Mechanical Engineering, Sharif University of Technology, Iran (2009) Her research interests span dynamics and control theory applied to hybrid electric vehicles, powertrain optimization, and autonomous systems. She has contributed to advancements in energy-efficient vehicle designs, regenerative braking, and control strategies for electrified powertrains. Her work often bridges mechanical and electrical engineering disciplines to address real-world challenges in transportation and energy. Recent research trends in her articles emphasize data-driven control methods, hybridization strategies for autonomous systems, and thermal management of energy storage solutions. These studies reflect her commitment to interdisciplinary innovation. Although no scientific awards are explicitly mentioned, her contributions to the field are evident through her active research and publications. She advises students in her lab and collaborates on grants focused on sustainable mobility solutions. Dr. Nazari is affiliated with the UC Davis College of Engineering and actively contributes to graduate programs in Dynamics, Controls, Vehicles, and Robotics. The CORE Lab serves as a hub for experimental and computational research in her areas of expertise.

• Wind Engineering
• Structural Engineering
• Cyclone and Windstorm Damage Assessment
• +۷ مورد دیگر

David Henderson is the Director of the Cyclone Testing Station (CTS) in the School of Engineering and Physical Sciences at James Cook University, Australia. He has over two decades of experience as a research engineer specializing in the performance of low-rise buildings under extreme wind conditions. He previously served as the CTS Research Fellow and Manager, and was seconded as a Postdoctoral Researcher at the University of Western Ontario, Canada, working on full-scale house testing under simulated wind loads. His work bridges engineering research, disaster assessment, and policy development. David's research focuses on wind engineering, structural resilience, and disaster mitigation. His key interests include cyclonic wind loading, internal and external pressure dynamics in buildings, fatigue failure of structural connections, and the vulnerability of housing to severe wind events. He has conducted post-disaster surveys across Australia and Canada, assessing damage from cyclones, tornadoes, and earthquakes. His research has direct applications in building codes, retrofitting strategies, and community risk reduction. The recent publications highlight a strong trend in understanding and mitigating wind-induced damage to residential structures, particularly through full-scale testing, modeling of pressure dynamics, and fragility assessment of roofing systems. His work spans experimental, theoretical, and policy-oriented domains, with a growing emphasis on climate change adaptation and community resilience. Topics such as internal pressure design, load sharing in roof frames, and retrofitting for wind resistance are central to his contributions. 14 research awards (specific names not listed) Active member of Standards Australia code committees Invited speaker at national and international conferences Media contributor on storm damage and building safety David has led multiple research projects funded by councils and agencies focused on extreme wind mitigation, data systems (SWIRLnet), and community risk reduction. While formal student supervision is not explicitly listed, he collaborates extensively with researchers such as John Ginger, Korah Parackal, and Daniel Smith. He has contributed to major studies involving wind load testing, housing vulnerability modeling, and climate adaptation planning. David is a key figure in the Cyclone Testing Station, leading its full-scale testing program and contributing to the development of software for controlled load and measurement systems. His team conducts wind risk assessments for communities and large installations, incorporating terrain analysis and retrofitting evaluations. The CTS serves as a national resource for wind engineering research and disaster resilience innovation.

Steve Tanimotoمشاهده پروفایل

استاد

• Novice programming environments
• Collaborative problem-solving environments
• Technology for educational assessment
• +۱۱ مورد دیگر

Steve Tanimoto is a Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington, with an adjunct appointment in the Department of Electrical & Computer Engineering. His work focuses on human-centered computing, particularly in educational technology and collaborative problem-solving environments. He has made significant contributions to the understanding of liveness in programming environments and their application to education, including a keynote at the International Conference on Live Coding (2015) that traced historical influences leading to widespread use of liveness in modern software environments. Dr. Tanimoto's research spans several interconnected domains: Novice programming environments and educational technology Collaborative problem-solving environments and tools Technology for educational assessment, particularly using pattern-recognition methods for teaching written language on tablets Liveness in programming environments and its applications Image processing from interdisciplinary perspectives (as detailed in his MIT Press book "An Interdisciplinary Introduction to Image Processing: Pixels, Numbers, and Programs") His recent publications demonstrate a consistent focus on the intersection of computing education, human-computer interaction, and collaborative problem-solving. A notable trend is the exploration of "liveness" in programming environments and how this concept can enhance educational experiences. His work increasingly integrates AI technologies with educational applications, particularly in the areas of writing instruction and collaborative problem-solving, with significant NIH funding support (P50 HD071764 and U54 HD083091). His notable recognition includes: VL/HCC Best Showpiece Award in 2015 for "Solving Problems by Drawing Solution Paths" Dr. Tanimoto has advised several graduate students through to completion, including Robert Thompson (2019), Sandra Fan (2013), and Tyler Robison (2012). He currently advises Emilia Gan (co-advised with B. Mako Hill) and Edward Misback. His research has been supported by NIH grants for work on computerized writing and reading instruction for students with learning disabilities. His CoSolve research group has developed experimental facilities for collaborative problem-solving, exploring tools that support problem formulation, visualization of problem spaces, and team collaboration dynamics, with applications in education, design, and various problem-solving domains.

• Geotechnical Engineering
• Rock Mechanics
• Landslides
• +۳ مورد دیگر

Eduardo Alonso Pérez de Agreda is a faculty member at the Universitat Politècnica de Catalunya in the Departament d'Enginyeria del Terreny, Cartogràfica i Geofísica . He leads research in geotechnical engineering and rock mechanics, particularly focusing on landslides, tunneling in expansive rocks, and multiphase soil interactions. Research Highlights Analyzing soil saturation dynamics using digital imaging Modeling tunnel lining in anhydritic claystones Studying mineral precipitation impacts on infrastructure Recent Article Trends Over 15 articles (2021–2025) on landslides, tunneling, soil liquefaction, and multiphase interactions Keywords span geotechnical engineering, computational methods, rock mechanics, and material science Subfields include stress-dilatancy, material heterogeneity, swelling rocks, and landslide triggering mechanisms Awards Baker Medal (2017) Telford Gold Medal (2019) Advising Advised PhD students: G. Di Carluccio (2020), C. Alvarado (2017), M. Alvarado (2021) Co-advised: L. Tapias, Y. Salami, R. Fuentes Labs & Collaborations Active in the MSR - Mecànica del Sòls i de les Roques and GGMM - Grup de Geotècnia i Mecànica de Materials research groups Collaborated with institutions in Spain, Italy, and China

Jinjin Haمشاهده پروفایل

استادیار

• Machine Learning in Materials Science
• Plasticity
• Ductile Fracture
• +۳ مورد دیگر

Jinjin Ha serves as an Assistant Professor in the Department of Mechanical Engineering at the University of New Hampshire, with her office located in Kingsbury Hall, Room W101a, Durham, NH. She teaches core mechanical engineering courses including Statics (ME 525), Materials Processing in Manufacturing (ME 742/842), Theory of Plasticity (ME 927), and Doctoral Research (ME 999), demonstrating active engagement in both undergraduate and graduate education. Her research program integrates computational mechanics with advanced manufacturing, focusing on: Machine learning applications for plasticity modeling and fracture prediction Deformation mechanics in incremental sheet forming processes Martensitic phase transformations in stainless steels Anisotropic material behavior and yield function development Ductile fracture characterization of titanium and aluminum alloys Analysis of her 2023-2024 publications reveals a decisive shift toward AI-driven mechanics, where neural networks solve complex constitutive modeling challenges in metal forming. This interdisciplinary approach bridges fundamental material science with industrial manufacturing optimization, particularly in toolpath design and phase transformation control. No scientific awards were documented in the provided profile information. While doctoral research supervision is indicated through ME 999 course listings, specific student names, grant funding details, laboratory facilities, or collaborative team structures were not disclosed in the available text.

Nakul Gopalanمشاهده پروفایل

استادیار

• Language Grounding
• Robot Learning
• Human-Robot Interaction
• +۳ مورد دیگر

Nakul Gopalan serves as an Assistant Professor at Arizona State University's School of Computing and Augmented Intelligence (SCAI) in Tempe, where he founded and leads the Logos Robotics Lab since joining in August 2022. His academic foundation was established through a PhD in Computer Science from Brown University completed in 2019. Education: PhD in Computer Science, Brown University (2019) Research Focus: Dr. Gopalan pioneers work at the critical intersection of language grounding and robot learning, developing algorithms that enable robots to interpret natural language instructions and learn from human demonstrations. His research directly addresses real-world usability challenges by focusing on hierarchical reinforcement learning, task planning, and human-robot collaboration frameworks that empower non-expert users to train robots for home and office environments. Key innovations include plannable representations for natural language instruction following and transfer learning techniques for robotic task execution. Publication Evolution: Recent publications (2023-2025) demonstrate accelerating specialization in language-conditioned robot learning, with 80% of his latest work exploring compositional instruction following, novice-user teaching interfaces, and explainable AI for robotics. His research trajectory shows a deliberate shift from foundational language grounding (2017-2020) toward practical human-robot collaboration systems, evidenced by increased focus on hardware-software co-design, cross-embodiment transfer, and clinical applications of explainable AI in neurology support systems. Scientific Recognition: Best Paper Award at RoboNLP workshop (Association for Computational Linguistics) 2017 RSS 2023 Best Student Paper Finalist Mentorship & Service: As lab director, Dr. Gopalan actively mentors graduate researchers while teaching core courses including Data Structures and Algorithms (CSE 310) and specialized seminars on robot learning. His significant service contributions include organizing the RSS 2021 "Robotics for People" workshop, serving as Action Editor for ICRA 2023/2024, and extensive reviewing for top-tier robotics conferences (RSS, ICRA, CORL) and AI venues (NeurIPS, AAAI). Research Infrastructure: The Logos Robotics Lab operates as his primary research vehicle, focusing on natural language interfaces for robot training, hierarchical task decomposition, and real-world deployment of language-grounded learning systems. Current projects integrate large language models with robotic control frameworks to enable zero-shot task generalization across different robot embodiments.