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Haobin NiView profile

Research Fellow

• Programming Languages
• Software Engineering
• Formal Verification
• +5 more

Haobin Ni is a Postdoctoral Scholar at the University of Washington in the Programming Language and Software Engineering (PLSE) group, advised by Professor Zachary Tatlock. His research bridges theoretical formal methods with practical systems development in programming languages and security. Education: Ph.D. in Computer Science, Cornell University (2024). Dissertation: "Formal Modeling Languages for High-assurance Domain-specific Systems." Advisors: Greg Morrisett and Robbert van Renesse. Ni's research focuses on language design, program analysis, and compiler optimization with emphasis on formal verification of distributed systems, concurrent programs, and parsers. He pioneers secure smart contract languages using information flow control type systems and develops novel protocols for distributed systems. His work consistently targets high-assurance systems where correctness and security are critical, spanning blockchain, binary parsing, and state machine replication. Analysis of his 11 publications (2019-2024) reveals three dominant research thrusts: compositional security frameworks for smart contracts (especially against reentrancy attacks), provably correct implementations of critical infrastructure like ASN.1 parsers, and modular abstractions for distributed ledger technologies. His methodology combines deep theoretical formalization with practical implementation, resulting in tools and protocols adopted in real-world systems. Scientific awards: Best Paper Award, IEEE Symposium on Security and Privacy (2021) ICPC World Finals Gold Medal (2016) ICPC World Finals Silver Medal (2014) Ni actively mentors through competitive programming: he coached Cornell's ICPC team (2018-2024), leading them to World Finals qualifications in 2019 and 2023, and volunteered for high school programming contests. Currently, he leads the PLSE Programming Languages Reading Group (PLRG) at the University of Washington, fostering community engagement in PL research. His work shows strong industry collaboration, particularly with Microsoft Research on blockchain and security projects. As a core member of UW's PLSE group, Ni contributes to one of academia's leading programming languages research teams. His current leadership of the PLRG demonstrates active community building, while his technical work on Charlotte and ASN1★ positions him at the forefront of secure distributed systems research.

Selcuk PakerView profile

Professor

• Electromagnetic Fields
• Microwave Systems
• Telecommunication Systems
• +8 more

Prof. Dr. Selcuk Paker is a faculty member at the Department of Electronics and Communication Engineering , Faculty of Electrical and Electronics Engineering , Istanbul Technical University. His research spans electromagnetic field theory, microwave systems, and telecommunications, with a focus on antenna design, radar imaging algorithms, and bioelectromagnetics. Research Interests : Electromagnetic scattering, inverse scattering, radar systems, SAR imaging, GNSS algorithms, microwave heating, and wireless communication. Recent publications highlight his work in 5G antenna design , radar-based earthquake detection , and biological effects of RF exposure . He contributes to microwave and radar technologies, including applications in structural diagnostics and sensor networks.

• Materials Science
• Computational Method Development
• Catalytic Mechanism Study
• +3 more

Dr. Li Lei is an Associate Professor and doctoral supervisor in the Department of Materials Science and Engineering at the Southern University of Science and Technology (SUSTech). He holds a BS from the University of Science and Technology of China and a PhD in Chemistry (2016) from the University of Nebraska-Lincoln. From 2016-2020, he conducted postdoctoral research with Prof. Graeme Henkelman at the University of Texas at Austin, where he developed the machine-learning software package PyAMFF. Education : BS (Materials Science, USTC), PhD (Chemistry, UNL) Affiliation : Southern University of Science and Technology, Shenzhen Peacock Plan Category B Talent Research Focus : His work bridges computational method development and catalytic mechanism discovery through: Machine learning algorithms for force field training Long-timescale dynamics simulations of nanomaterials Saddle-point searching methods for reaction pathways Monte Carlo-based catalyst optimization Development of catalytic reaction databases His recent publications in JACS , Nat. Commun. , and ACS Catalysis demonstrate expertise in: Machine learning-enhanced molecular dynamics Electrochemical catalyst design (ORR/OER) in situ reaction mechanism analysis Atomic-scale electrostatic modeling Scientific Contributions : - Led development of PyAMFF machine learning potential framework - Published 27+ SCI papers in top-tier journals - Collaborated with leading computational chemists (Henkelman, Zeng, Francisco) Awards : Shenzhen Peacock Plan Category B Talent Contact : Office: 5th Floor, North Building, College of Engineering, SUSTech Phone: 0755-88015040 Email: lil33@sustech.edu.cn | lei.li@sustech.edu.cn

• Sustainable Materials Engineering
• Green Materials Processing
• Wood Science and Technology
• +7 more

Thomas Schnabel is a Research Group Leader and Senior Researcher in Design and Green Engineering at Salzburg University of Applied Sciences, where he heads the Green Materials and Processing research group and leads the Salzburg Center for Smart Materials 2.0 initiative. His work bridges academic research with practical industrial applications in sustainable materials science. His research focuses on: Valorization of wood byproducts, particularly tree bark extracts for multiple applications Development of natural fiber insulation materials from recycled wood residues Life cycle assessment of sustainable material production processes Application of bioactive compounds from bark for biomedical uses Green chemistry approaches to material processing and purification Dr. Schnabel's publication record shows a cohesive research trajectory focused on extracting maximum value from wood processing byproducts. His recent articles demonstrate increasing sophistication in characterizing bark extracts and developing practical applications across construction, biomedical fields, and sustainable manufacturing. The research directly contributes to UN Sustainable Development Goals related to responsible consumption, climate action, and industry innovation. He leads multiple significant research initiatives including: NETTLE: Cross-border cooperation for alpine plant bioactive compounds (2024-2026) DRWO4.0: Danube Region Wood Industry Transformation toward Industry 4.0 (2024-2025) SCSM 2.0: Salzburg Center for Smart Materials 2.0 (2023-2026) User-centered teaching materials development in forestry and bioeconomy (2023-2026) His collaborative network spans the Danube region and beyond, reflecting the international significance of his work in advancing sustainable materials science and engineering practices.

• Fluid Power Engineering
• Hydraulic Systems
• Tribology
• +4 more

Prof. Dr.-Ing. Katharina Schmitz serves as Institute Director and Vice Dean at the Institute for Fluid Power Drives and Systems, RWTH Aachen University. Her leadership within the Production Technology Cluster and extensive contributions to fluid power engineering establish her as a leading authority in mechanical engineering research and education. Her research spans fluid power systems, hydraulic component design, tribology, and physics-informed machine learning applications. She pioneers sustainable propulsion solutions through bio-hybrid fuels research while addressing fundamental challenges in polymer material behavior under hydraulic stresses. Current work focuses on carbon-neutral heavy-duty transportation, physics-based neural networks for lubrication modeling, and advanced control systems for electro-hydraulic actuators. Analysis of her 15 most recent publications reveals a dominant trend toward integrating physics-based modeling with deep learning to solve complex engineering problems. Her team consistently develops novel frameworks for cavitation prediction, flow rate determination, and material compatibility assessment - significantly advancing fluid power system reliability, efficiency, and digitalization. Scientific recognition includes: GfT Förderpreis 2023 for experimental and simulative investigation of partially hydrostatic relieved contacts in variable speed axial piston machines As head of the Institute for Fluid Power Drives and Systems, she leads cutting-edge research in sustainable fluid power technologies. The institute maintains strong industry partnerships while driving innovation in hydraulic component design, digital twins for condition monitoring, and next-generation propulsion systems through its position within RWTH Aachen's Production Technology Cluster.

Adem AtmacaView profile

Professor

• Energy Systems
• Thermodynamics
• Heat Transfer
• +9 more

Professor Adem Atmaca is a prominent academic at Gaziantep University's Faculty of Engineering, Department of Mechanical Engineering, where he currently serves as a Professor since 2023. His academic journey includes progressive appointments from Instructor (2009-2014) to Assistant Professor (2016-2018), Associate Professor (2018-2020), and finally Professor (2023-present). He has also held significant administrative roles including Department Head (2018-2021) and Director of Research and Application Center. Professor Atmaca holds a PhD in Mechanical Engineering from Gaziantep University (2009-2014) and completed his undergraduate studies in Mechanical Engineering at the same institution (2000-2005). His research interests span energy systems, thermodynamics, heat transfer, renewable energy (particularly solar), carbon footprint analysis, cement industry energy efficiency, and life cycle assessment of buildings. His work demonstrates a consistent focus on sustainability and energy optimization across multiple industrial and construction sectors. His publication portfolio shows a clear evolution from early work on cement industry thermodynamics and energy consumption to more recent research on solar energy systems, carbon footprint analysis, and sustainable building materials. The most recent articles (2022-2025) reveal a strong emphasis on machine learning applications in solar energy, advanced carbon footprint assessment methodologies, and innovative sustainable construction materials using recycled waste products. His research consistently bridges theoretical thermodynamics with practical industrial applications. 2024 Stanford University Annual Impact Success Award 2024 TÜBİTAK HORIZON EU Threshold Award 2023 Carbon Footprint Publication Incentive Award 2022 HORIZON 2022 - Threshold Award 2017 Best Presentation Award at UEMK2017 Professor Atmaca has supervised numerous graduate students across various research topics including photovoltaic systems, concrete properties, sustainable building design, and energy optimization. His extensive grant portfolio includes international projects such as the REBUILD project focused on historical building restoration after disasters, the NEURONES project on positive energy districts, and multiple national research projects on renewable energy and sustainable construction. He has also been involved in significant industry collaborations with Limak Cement Group and other industrial partners. His research activities are closely connected to practical applications through various international projects including the REBUILD project (Digital Twin-Driven Multidimensional Decision Platform for Sustainable Post-Disaster Restoration of Historical Buildings), which addresses the aftermath of the 2023 Turkey earthquakes, and collaborations with international institutions through Horizon Europe and other EU-funded programs. His work bridges academic research with real-world engineering challenges in energy efficiency and sustainability.

Laura PowerView profile

Associate Clinical Professor

• Public Health Practice
• Infectious Diseases
• Public Health Workforce Development
• +3 more

Laura Power serves as Clinical Associate Professor in Epidemiology at the University of Michigan School of Public Health and Infectious Diseases (Internal Medicine), directing the Office of Public Health Practice. Her work bridges medical practice and public health through experiential learning, workforce development, and infectious disease epidemiology initiatives. Her educational background includes: BA from Albion College (1998) MD from Wayne State University School of Medicine (2002) MPH from University of Michigan School of Public Health (2015) Her research centers on public health practice systems, workforce capacity building, and infectious disease prevention. Recent projects include HRSA-funded Region V Public Health Training Center and Preventive Medicine Residency Program, focusing on applied epidemiology and outbreak response training. Her scholarly work demonstrates consistent emphasis on antimicrobial resistance, diagnostic accuracy, and translational public health practice. Her 15 most recent publications reveal strong focus on infectious disease epidemiology (73%), public health practice systems (60%), and antimicrobial resistance (47%), with growing emphasis on workforce development and outbreak response since 2016. Key trends include methodological innovation in surveillance systems and practical interventions for healthcare-associated infections. Dr. Power actively mentors students through the Public Health Action Support Team (PHAST) and Public Health in Action courses, connecting academic training with community practice. Her HRSA-funded programs support over 200 public health practitioners annually through the Region V Leadership Institute and residency training. She leads the Office of Public Health Practice, Region V Public Health Training Center, and Public Health Prepared program—fostering partnerships between academic, governmental, and community health organizations to enhance outbreak response capacity.

Hossein AminiView profile

Lecturer

• Data Science
• Machine Learning
• Big Data Analytics
• +6 more

Hossein Amini is a Lecturer in Data Analytics at Olin Business School, Washington University in St. Louis. He holds a Ph.D. in Data Science from Kansas State University (2019), an MS (2015), and a BS in Computer Engineering from Khaje Nasir Toosi University of Technology (2007). His research focuses on applying machine learning to healthcare and manufacturing, including predictive analytics for diseases like breast cancer and adverse drug reactions, as well as process monitoring in additive and semiconductor manufacturing. Education: Ph.D. in Data Science, Kansas State University, 2019 MS in Data Science, Kansas State University, 2015 BS in Computer Engineering, Khaje Nasir Toosi University of Technology, 2007 Research Interests: Hossein’s work spans machine learning applications in multistage industrial processes (e.g., 3D metal printing), medical decision support systems, and predictive modeling for healthcare and manufacturing. He emphasizes data-driven solutions for resource optimization, sustainability, and crisis management. Teaching: He instructs graduate courses in SQL (DAT560G) and Big Data Analytics (DAT560M) at Olin Business School. Publications Trends: His publications address emergency response systems, sustainable architecture design, industrial process monitoring frameworks (e.g., MLCPM), medical decision-making under uncertainty, and knowledge management failure analysis using fuzzy logic. Recent work emphasizes real-world applications of machine learning in critical sectors. Professional Activities: No grants or awards explicitly listed. He actively reviews electronic gadgets and engages in academic reviewing.

Valerie B. ShapiroView profile

Associate Professor

• Prevention Science
• Social and Emotional Learning (SEL)
• Implementation Science
• +11 more

Dr. Valerie B. Shapiro is an Associate Professor jointly appointed in Social Welfare and Public Health at the University of California, Berkeley . She co-directs the Center for Prevention Research in Social Welfare and leads continuous improvement efforts for the FEMA/SAMHSA-funded CalHope Student Support Initiative . As a William T. Grant Foundation Scholar , her work bridges prevention science, community coalitions, and systemic social and emotional learning (SEL). Research Interests : Dr. Shapiro’s research focuses on the adoption, implementation, and sustainability of evidence-based prevention practices to promote mental, emotional, and behavioral health in children and youth. Key areas include strength-based screening (e.g., DESSA tools), SEL implementation at scale , and equity-driven educational reform . Her work emphasizes data-driven decision-making , coalition-based models , and addressing racial, socioeconomic, and gender disparities in SEL outcomes. Scientific Awards : William T. Grant Foundation Scholar Phi Beta Kappa Inductee (2002) NIMH Child Intervention, Prevention, & Services Fellow (2013) Prytanean Faculty Prize (2014) Fellow of the Society of Social Work & Research (2017) Advising & Grants : Dr. Shapiro mentors students and collaborates on projects funded by the Berkeley Faculty Research Fund , Kaiser Permanente Northern California Community Benefit Program , Stuart Foundation , and National Institute of Mental Health . Her research has inspired practice tools like the DESSA and influenced National Academy of Medicine policy discussions. Labs & Teams : As co-director of the Center for Prevention Research in Social Welfare , she leads teams in developing scalable SEL frameworks and serves on the National Prevention Science Coalition and California Department of Education CASEL Collaborating States Initiative .

Mostafa MilaniView profile

Assistant Professor

• Data Management
• Databases
• Data Cleaning
• +7 more

Mostafa Milani is an Assistant Professor in the Department of Computer Science at Western University. His research focuses on data management, databases, and their applications in data cleaning, privacy, provenance, and fairness. Before joining Western, he held postdoctoral positions at the University of British Columbia and McMaster University, and earned his Ph.D. from Carleton University under Dr. Leopoldo Bertossi. Education: Ph.D. in Computer Science from Carleton University (supervised by Leopoldo Bertossi), Postdoctoral Fellowships at University of British Columbia and McMaster University. Research Interests: Data Quality, Privacy, Provenance, Fairness, Entity Matching, Query Optimization, and Database Systems. His work emphasizes ethical data practices and integrates machine learning for improved database interactions. He has contributed to projects like Building Trust in Data (privacy/fairness integration) and Unified Data Exploration (provenance and query recommendations). Courses taught include Databases I/II, Applied Logic, and Web Systems. Current advisees include 7 MSc and 1 PhD student. Former students have graduated across MSc and undergraduate programs. His research is supported by grants and collaborations, and he actively participates in program committees for top conferences like SIGMOD and VLDB.

• Additive Manufacturing
• Materials Engineering
• Surface Engineering
• +3 more

Denis Dowling is a Full Professor at University College Dublin (UCD), leading the School of Mechanical and Materials Engineering. He directs the I-Form Advanced Manufacturing Research Centre, a 40M Euro initiative focusing on additive manufacturing and digital integration in manufacturing environments. His research spans surface engineering, plasma treatments, and advanced materials processing, with a focus on composites and additive manufacturing innovations. Dr. Dowling holds a PhD from UCD and has supervised 20 PhD and 5 MSc students. He is actively involved in the European Institute of Innovation and Technology (EIT) in manufacturing and previously led UCD's participation in the SFI Precision Cluster. His awards include the UCD Innovation Award (2012) and the Institute of Materials Finishing Gold Medal (2013). His work bridges academia and industry, with collaborations in solar energy, medical devices, and manufacturing SME sustainability. Key research themes include functional coatings for biomedical applications, microwave-assisted synthesis of nanostructures, and in-situ process monitoring for additive manufacturing quality control. Teaching includes modules on nanomaterials and manufacturing, reflecting his research-led approach. Professional roles include chairing the Irish branch of the Institute of Metal Finishing.

Amneet BhallaView profile

Associate Professor

• Fluid-Structure Interaction
• Multiphase Flows
• Aquatic Locomotion
• +7 more

Dr. Amneet Bhalla serves as an Associate Professor in the Department of Mechanical Engineering within the College of Engineering at San Diego State University (SDSU). His primary contact email is asbhalla@sdsu.edu, with office located in Engineering Building Room 323-G, and phone number (619) 594-2043. Education: Ph.D., Mechanical Engineering, Northwestern University (2013) M.S., Mechanical Engineering, Indian Institute of Technology Kharagpur (2009) B.S., Mechanical Engineering, Indian Institute of Technology Kharagpur (2004-2008) Postdoctoral Training: University of North Carolina at Chapel Hill (Mathematics Department) and Lawrence Berkeley National Laboratory (Computational Research Division) Research Interests: Dr. Bhalla develops advanced numerical methods and high-performance computing techniques for computational fluid dynamics (CFD) and fluid-structure interaction (FSI) problems. His work spans aquatic locomotion, renewable energy device modeling, multiphase flows, vehicular aerodynamics, and bioengineering applications. He creates mathematical models to interrogate underlying flow physics for engineering design optimization, with emphasis on open-source software development through the IBAMR library. Publication Trends: Recent publications (2023-2025) focus on robust numerical frameworks for multiphase flows with phase change, acoustic streaming, and fluid-structure interaction. Key themes include mass conservation in level set methods, adaptive mesh refinement, and solvers for non-isothermal gas-liquid-solid systems. Applications range from aquatic locomotion and renewable energy devices to microfluidics and biomedical flows, demonstrating commitment to both theoretical advances and practical engineering solutions. Scientific Awards: No awards mentioned in the provided text Advising and Grants: Dr. Bhalla secured an NSF CAREER award (2023) for "Consistent Continuum Formulation and Robust Numerical Modeling of Non-Isothermal Phase Changing Multiphase Flows". As PI of the CFD Lab, he mentors graduate students in computational mechanics, leveraging prior industrial experience at ExxonMobil Upstream Research Company. His research integrates industrial practicality with academic rigor through collaborations with national laboratories. Laboratory and Team: The Computational Fluid Dynamics and Flow Physics Laboratory (CFD Lab) develops the open-source IBAMR software—a distributed-memory parallel implementation of the immersed boundary method with adaptive mesh refinement. The lab emphasizes transparency, community engagement, and reproducibility, establishing cross-institutional collaborations while advancing computational methods for complex flow phenomena in engineering and biological systems.

Aysegul DemirView profile

Assistant Professor

• Sustainable Design
• Energy Efficient Buildings
• Urban Building Energy Modeling
• +3 more

Aysegul Demir is an Assistant Professor at the University of Wyoming's Department of Civil & Architectural Engineering , part of the College of Engineering and Physical Sciences . Her work focuses on sustainable design, energy efficiency in buildings, and climate change mitigation strategies. She holds a Ph.D. in Building Energy & Environments from The University of Texas at Austin, an M.S. in Structural Engineering from Istanbul Technical University, and dual B.S. degrees in Civil and Environmental Engineering from Dokuz Eylul University, Turkey. Research Interests: Dr. Demir's research emphasizes urban building energy modeling and the integration of renewable energy systems into building design. She explores methods to optimize building energy performance while addressing climate change impacts. Her work often intersects engineering, environmental science, and urban planning. Professional Details: Office: EN 3101 | Email: aysha.demir@uwyo.edu

Kallol SettView profile

Associate Professor

• Risk and Reliability
• Civil Infrastructure
• Extreme Events
• +5 more

Kallol Sett is an Associate Professor in the Department of Civil, Structural and Environmental Engineering at the University at Buffalo (SUNY), within the School of Engineering and Applied Sciences. His research focuses on risk and reliability analysis of civil infrastructure under extreme events, with expertise in uncertainty quantification, multi-hazard resilience, and geomechanics. He leads the Risk and Reliability Research Group, which develops computational tools integrating physics-based and data-driven modeling, stochastic calculus, and high-performance computing. Education includes a PhD from the University of California, Davis (2007), an MS from the University of Houston (2003), and a BE from Jadavpur University (1997). His work is funded by NASA, NSF, USDOT, NIST, and industry partners. Key research themes include probabilistic geotechnical site characterization, stochastic simulation of seismic ground motion, and life-cycle cost-benefit analysis of infrastructure systems. Advising includes mentoring over 10 PhD and MS students, with notable alumni now in academia and industry roles such as Assistant Professors at Embry-Riddle Aeronautical University and Tianjin University. His lab’s recent studies address real-time decision support systems for hurricane-impacted infrastructure, resilience deficit indices, and multi-hazard financial risk assessment of integrated infrastructure systems.

Fan YaoView profile

Associate Professor

• Computer Architecture
• Hardware Security
• AI Security
• +5 more

Fan Yao is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Central Florida's College of Engineering and Computer Science. She received her Ph.D. in Computer Engineering from The George Washington University in 2018 and currently leads the Computer Architecture and Systems Research (CASR) lab. Her research focuses on the intersection of computer architecture, security, and machine learning, with particular emphasis on hardware-based security vulnerabilities and defenses. Dr. Yao's research interests span computer architecture, hardware and system security, AI security, energy-efficient computing, and cloud computing. Her work addresses critical security challenges in modern computing systems, particularly focusing on microarchitecture attacks, hardware-based model tampering in deep learning systems, and information leakage threats in emerging non-volatile memory systems. She has developed innovative defense mechanisms against cache timing channels, branch predictor vulnerabilities, and GPU-based side channels. Her recent publications demonstrate a strong focus on AI security (particularly Deep Neural Network vulnerabilities), hardware security (including cache and branch predictor attacks), and secure memory architectures. The research shows an evolution from traditional computer architecture topics toward the security implications of AI hardware and emerging memory technologies, with increasing emphasis on practical attacks and defenses in real-world systems. NSF GW I-Corps Site Grant Award, 2018 Best Dissertation Award, GWU, 2018 The Norris & Betty Hekimian Engineering Endowment Fellowship, GWU, 2017 Top Picks in Hardware and Embedded Security, 2019 NSF CAREER project award, 2024 Dr. Yao currently leads multiple NSF-funded research projects including 'Understanding and Taming Deterministic Model Bit Flip Attacks in Deep Neural Networks' (NSF SaTC, 2020-2023), 'Towards Secure-By-Design Integration of Emerging Non-Volatile Memory in Future System' (NSF CNS, 2020-2023), and 'Architecting Secure-by-Design Memristor-Based Memories' (NSF CNS, 2019-2022). She has successfully mentored numerous PhD students, many of whom appear as first authors on top-tier conference publications, demonstrating her commitment to graduate education and research mentorship. As the leader of the CASR lab, Dr. Yao oversees a vibrant research group focused on building secure-by-design, efficient, and advanced future systems through novel techniques spanning hardware, computer architecture, and systems. The lab actively publishes at top computer architecture and security conferences including ISCA, MICRO, HPCA, IEEE S&P, and USENIX Security, with multiple papers accepted to these venues annually. The group has developed several influential tools and frameworks for security analysis, including proof-of-concept code for BranchSpec exploits that has been widely cited in the hardware security community.