Ioan Raicu is a Professor in the Department of Computer Science at Illinois Institute of Technology (IIT) and a guest research faculty at Argonne National Laboratory's Math and Computer Science Division. He leads the Data-Intensive Distributed Systems Laboratory (DataSys) at IIT, focusing on distributed systems, cloud computing, and high-performance computing. His work is primarily funded by the NSF and DOE. Research interests include distributed systems, many-task computing, and data-intensive applications. Over 140 peer-reviewed publications have yielded a H-index of 46, with top papers addressing cloud vs. grid computing comparisons, Globus GridFTP, Swift workflow systems, and Falkon frameworks. Recent projects explore fine-grained parallelism, scalable indexing, and energy-efficient blockchain algorithms. Awards include NSF grants and recognition for lab innovations. Advised PhD students include Alexandru Orhean and Poornima Nookala. The DataSys lab has won the Grainger Computing Innovation Prize and leads initiatives like the BigDataX REU program. Active in conferences such as SC and IEEE IPDPS, Raicu's work bridges theory and practice in extreme-scale computing systems.
Dr. Jing Li is a Senior Research Fellow at the University of Hull's Energy and Environment Institute. He holds a BSc (2006) and PhD (2011) from the University of Science and Technology of China (USTC), followed by a postdoctoral position there and an EU Marie Skłodowska-Curie Fellowship at the University of Nottingham (2017–2019). His research focuses on renewable energy, energy storage, and sustainable heating technologies, with expertise in heat pumps, organic Rankine cycles, and solar PV/T systems. Dr. Li has led/co-led 12 research projects funded by organizations such as the EU, BEIS, and the Royal Society. He is a Fellow of the Higher Education Academy (FHEA) and has co-authored over 100 peer-reviewed papers, 3 books, and holds 10 patents. His innovations include vapor-injection heat pumps, novel thermal storage techniques, and advanced photovoltaic/thermal systems. Key research themes include low-carbon energy systems, thermodynamic cycle optimization, and sustainable building technologies. His recent work demonstrates low-carbon heating systems in public buildings and advanced solar-assisted heat pump designs. Education: BSc (USTC, 2006), PhD (USTC, 2011) Awards: FHEA, EU Marie Curie Fellowship Grants: £12k (Royal Society, 2022), EU/BEIS/EPSRC-funded projects His lab investigates cutting-edge energy solutions, including heat batteries, solar-driven ORC systems, and hydrogen-based CHP systems. He actively contributes to international conferences, delivering keynote speeches on sustainable energy advancements.
Ben Goddard is a Professor in the School of Mathematics at the University of Edinburgh. His work bridges applied mathematics with real-world scientific challenges, emphasizing interdisciplinary collaboration across engineering, biology, chemistry, and physics. He earned his PhD at the University of Warwick, later completing his final year at TU Munich following his advisor. His research focuses on mathematical modeling, numerical methods, and asymptotic analysis applied to problems such as quantum chemistry, fluid dynamics, and biological systems. Education: Bachelor’s degree in Mathematics (undergraduate details unspecified) PhD in Mathematical Quantum Chemistry (University of Warwick/TU Munich) Research interests include: Dynamic density functional theory (DFT) for complex fluids and nanoparticles Interfacial phenomena and contact line dynamics Numerical optimization and pseudospectral methods Biological systems modeling (e.g., RNA transcription mechanics) Recent work explores applications like ouzo phase behavior, aerosol droplet stability, and opinion dynamics in social networks. His collaborations span diverse fields, including experimental biology at the Welcome Centre for Cell Biology. He advocates for mathematicians’ role in interdisciplinary problem-solving, emphasizing clear communication and adaptability. Advising and grants: While specific grant details are not listed, his projects reflect significant funding and team-based research. He actively promotes STEM engagement through activities like designing math-themed escape rooms with his spouse, a statistician. Labs/Teams: Collaborates extensively with Edinburgh’s Schools of Engineering, Biology, and Informatics, though no specific lab names are mentioned.
Dr. Jose Escribano is a Lecturer in Aviation & Logistics at the Department of Civil and Environmental Engineering within the Faculty of Engineering at Imperial College London. His research focuses on humanitarian logistics optimization, AI-driven airspace management, and urban resilience strategies. He holds a First Class Honours bachelor’s degree (2015) and a PhD (2021) from Imperial College London. Dr. Escribano is affiliated with the Centre for Transport Engineering and Modelling and the Transport Systems and Logistics Project D-Risk SHIFT. His academic qualifications include a BEng in Engineering and a PhD in Civil Engineering, both from Imperial College London. His professional affiliations include the Institution of Civil Engineers, Chartered Institute of Logistics and Transport, and the American Institute of Aeronautics and Astronautics. He has received the 2023 Transportation Research Board Best Paper Award and a JSPS Fellowship for urban evacuation modelling. Dr. Escribano’s research integrates stochastic modelling, machine learning, and simulation to address challenges in humanitarian response, UAV coordination for disaster relief, and airspace safety. His work emphasizes endogenous value-of-information analysis and the application of cutting-edge technologies to enhance societal resilience. He has collaborated with the United Nations World Food Programme on UAV deployment models for humanitarian contexts. His recent publications span topics like air traffic network resilience, autonomous vehicle optimization, and last-mile delivery mechanisms. He advises doctoral candidates in transportation systems, logistics, and air traffic management, offering opportunities for PhD research in these domains.
Bill Howe is an Associate Professor at the University of Washington's Information School, with adjunct appointments in Computer Science & Engineering and Electrical Engineering. He serves as Founding Program Director and Faculty Chair of the UW Data Science Masters Degree, Founding Associate Director and Senior Data Science Fellow at the UW eScience Institute, Director of the Urbanalytics Lab, and Co-Founding Director of the Center for Responsible AI Systems and Experiences. He also co-founded Urban@UW and created the first Data Science MOOC through Coursera. His research focuses on making data science accessible in public sector applications with emphasis on equity, privacy, and compliance. Current interests include: Algorithmic fairness in urban and social contexts Privacy-preserving synthetic data generation Machine learning for heterogeneous data Database systems and high-performance computing Human-computer interaction for data systems Responsible AI development and deployment Publication analysis reveals strong focus on responsible data science, with recent work emphasizing differential privacy, COVID-19 data equity, urban mobility fairness, and relational data systems. Earlier foundational work established contributions to scientific workflow systems and data pricing models. Awards and Honors: Runner-up Best Paper Award (VLDB 2023) Best Paper Award (SIGMOD 2019) Best Paper Award (VIs 2019) Best Paper Award (InfoVis 2018) He leads the Urbanalytics Lab and advises multiple students including An Yan (fairness in urban mobility), Sean Yang (machine learning embeddings), and Dominik Moritz (visualization systems). His projects span EZLearn for automatic claim validation, privacy-preserving synthetic data, and Myria middleware for polystores.
Waltraud M. Kriven is a Full Professor at the University of Illinois at Urbana-Champaign, holding joint faculty positions in the Materials Research Laboratory and Department of Materials Science and Engineering. She is also an Affiliate Professor in Mechanical Science and Engineering. Her expertise spans phase transformations in inorganic compounds, geopolymers, and ceramic composites. Kriven has pioneered research in low-temperature synthesis of ceramics and developed advanced geopolymer composites with applications in energy, infrastructure, and environmental sustainability. Education: PhD in Solid State Chemistry (University of Adelaide, 1976); B.Sc. (Hons) and Baccalaureate in Physical and Inorganic Chemistry and Biochemistry (University of Adelaide). Research Interests: Geopolymer-derived ceramics, carbothermal reduction processes, amorphous self-healing materials, and sustainable construction materials. Her work emphasizes nanoporous microstructure analysis and tailoring thermal expansion coefficients for advanced applications. Recent studies include neutron shielding geopolymers and environmental durability assessments. Conferences & Leadership: Organizer of over 22 international conferences on geopolymers, including the 2025 International Symposium on Geopolymers and Alkali Activated Materials. Served as Past-Chair of the Engineering Ceramics Division of the American Ceramic Society. Awards: Member of European Union Academy of Sciences (2020), Academician in World Academy of Ceramics (2005), Fellow of American Ceramic Society (1995), and recipient of the Mueller Award (2017) and Brunauer Award (1988, 1991). Industry Impact: Founded Keanetech LLC (2004), a technology transfer company specializing in ceramics and geopolymers. Collaborates with the US Army Corps of Engineers on infrastructure projects. Labs & Teams: Director of the Center for Geopolymer Research and Applications (CeGRA). Her research group develops in situ synchrotron furnaces for high-temperature ceramic studies.
George Vouros is a Professor in the Department of Digital Systems at the University of Piraeus, Greece. He is the head of the AI Lab (http://ai-group.ds.unipi.gr/ai-group/) and director of the MSc in Artificial Intelligence program in collaboration with the Institute of Informatics and Telecommunications at NCSR Demokritos. He completed his BSc in Mathematics (1986) and PhD in Artificial Intelligence (1992) at the University of Athens. His research focuses on Expert Systems, Knowledge Management, Multi-Agent Systems, Reinforcement Learning, and Mobility Analytics. He has served as program chair and committee member for major conferences (AAMAS, AAAI, IJCAI) and editorial roles in journals like Discover Artificial Intelligence (Springer Nature) and Information (MDPI). He has supervised 13 PhD students and currently oversees 4. His work spans EU-funded projects and national initiatives, emphasizing scalable mobility analytics, air traffic management automation, and ontology engineering. He is also President of the Hellenic A.I. Society and actively promotes interdisciplinary applications of AI in healthcare, transportation, and environmental monitoring. Recent research highlights include deep reinforcement learning for tactical air traffic conflict resolution, LLM-integrated ontology engineering, and multimodal generative adversarial imitation learning for flight trajectory modeling. His work bridges theoretical advancements with real-world applications in critical infrastructure systems.
Prof. Katarzyna Piwowar-Sulej is a Professor of Economics in Management and Quality Sciences at Wrocław University of Economics, holding a position in the Department of Labor, Capital and Innovation. She actively contributes to academic governance as a member of the Doctoral School Council and various strategic committees. Her research focuses on sustainable human resource management, leadership, and project management, with a strong emphasis on integrating sustainability into organizational practices. Expertise: Sustainable HR Development, Green HRM, Organizational Innovation Leadership Roles: Director of 'Psychology in Management' postgraduate studies Her academic contributions span over 200 publications in top journals such as Human Resource Management and Journal of Business Ethics . She has secured EU grants and led projects addressing HR challenges in Industry 5.0 and digitalization. Notable achievements include recognition in the World's TOP 2% Scientists 2023 and second place in the 2025 Science Personality of the Year award. Awards: Medal of the National Education Commission, Emerald's Outstanding Paper Award Research trends in her work highlight the intersection of leadership, sustainability, and innovation. Recent studies explore sustainability-focused leadership, green behaviors in SMEs, and neurodiversity management. She bridges academic and business worlds through HR consulting and project management expertise in sectors like finance and manufacturing. Key Projects: Digital HR process optimization, compensation system design, post-merger integration Her teaching legacy includes pioneering postgraduate programs for business trainers and integrating design thinking into academic curricula. She advocates for sustainable HR practices, emphasizing employee development and environmental responsibility.
Haitham Al-Deek is a Professor in the Department of Civil, Environmental, and Construction Engineering at the University of Central Florida's College of Engineering and Computer Science. He leads the Intelligent Transportation Systems and Data Analytics Lab and has over 32 years of experience in transportation engineering, planning, and operations. His work is nationally recognized, particularly in freeway operations and intelligent transportation systems (ITS). Ph.D., Civil Engineering-Transportation Engineering, University of California, Berkeley (1991) M.S., Civil Engineering-Transportation Engineering, University of California, Berkeley (1987) B.S., Civil Engineering (with Honors), University of California, Berkeley (1985) Dr. Al-Deek's research focuses on wrong-way driving countermeasures, connected and automated vehicles, traffic safety, and data analytics. He pioneered innovative ITS solutions for detecting and preventing wrong-way driving, including the development of a high-success-rate detection system in partnership with the Central Florida Expressway Authority (CFX). His work extends to freight transportation, electronic toll collection, and sustainable transportation systems. He has also contributed to safety performance functions and driver behavior modeling. His recent publications highlight advanced methodologies in network screening for crash modeling, the use of crowdsourced data (e.g., Waze) for incident detection, optimization of wrong-way driving countermeasures, and benefit-cost analyses of safety technologies. These works reflect a strong trend toward data-driven, real-time, and cost-effective solutions in transportation safety and operations. Scientific awards and recognitions include: TRB Chairman Award (2018, 2012) Multiple TRB Best Paper Awards (Freeway Operations and Regional TSM&O, 2023–2003) TRB Best Student Paper Awards (2022, 2019, 2018, 2017) UCF Excellence in Research Award (2018) UCF Researcher of the Year (1999) Distinguished Researcher, UCF College of Engineering (2003) Dr. Al-Deek has supervised 15 Ph.D. students and 29 M.S. theses and has secured over $10.3 million in research funding from agencies including FDOT, TRB, USDOT, and CFX. He serves as a technical editor for TRR and associate editor for the Journal of Intelligent Transportation Systems. He also chaired key TRB paper review subcommittees and is an active professional engineer in Florida. He leads the Intelligent Transportation Systems and Data Analytics Lab, which focuses on real-world applications of ITS, data warehousing, and advanced analytics for transportation safety and efficiency.
Tushar Sharma is an Assistant Professor in the Faculty of Computer Science at Dalhousie University, Canada. His research focuses on software engineering, particularly software quality, refactoring, technical debt, and the application of machine learning in software engineering (ML4SE). He leads the SMART Lab and is actively involved in projects related to Green AI and sustainable software development. PhD : Software Engineering, Athens University of Economics and Business, Greece (2019) MS : Computer Science, Indian Institute of Technology-Madras, India His research interests span software design and architecture, code and design quality, refactoring, technical debt, mining software repositories, and applied machine learning for software engineering. He is particularly interested in sustainable AI, green software engineering, and the use of large language models for code. His work bridges empirical studies with practical tool development to improve software maintainability and quality. His recent publications highlight a strong trend in code smell detection, refactoring automation, energy-aware AI, and the reliability of large language models in software engineering. He has developed tools like Designite and DPy and contributed datasets such as MaRV and DACOS, emphasizing empirical validation and reproducibility in software engineering research. Dean's Research Excellence Award Best Artifact Award, SCAM 2023 IEEE Senior Member Tushar Sharma has secured significant research funding, including an NSERC Discovery Grant for DevQOps, Mitacs Accelerate grants with industry partners, and contributions to the $154M Canada First Research Excellence Fund project. He actively mentors students and collaborates with industry. He leads the SMART Lab at Dalhousie and has organized workshops such as SATToSE 2018. He is also a founding developer of Designite, a widely used software design quality assessment tool.
Dr. Mark D. Soucek is a Professor and Interim Director at the University of Akron 's School of Polymer Science and Polymer Engineering . With over 140 publications, his work focuses on developing environmentally benign coatings, including UV-curable systems, nanotechnology-enabled smart coatings, and inorganic/organic hybrid materials. He previously served as President of the Cleveland Coating Society (2009) and has held academic positions at NASA-Langley (1990-1993), North Dakota State University (1993-2001), and currently at the University of Akron since 2001. Education : Ph.D. in Inorganic Chemistry (University of Texas, Austin, 1990) M.S. in Organic Chemistry (Illinois State University, 1986) B.S. in Chemistry (Eastern Illinois University, 1983) His research emphasizes crosslinked coating systems such as autoxidatively crosslinked , high solids , crosslinkable latexes , and UV-curable thermosets . Using Photo-DSC , Real-time IR , and DMTA , his group analyzes in situ crosslinking reactions to correlate molecular structure with coating properties like fracture toughness , abrasion resistance , and corrosion protection . Recent projects include creating a UV-Curable Powder Coatings Research Center to bridge industrial and academic collaborations. Dr. Soucek's publications span topics like smart ceramer coatings , seed oil-based reactive diluents , and hydrolytic stability of polyesters . His work has received multiple citations in areas such as environmental degradation and tire wear particle analysis . He has secured grants from the National Institute of Food and Agriculture and the Industry/University Cooperative Research Center in Coatings .
Dr. Sumanta Das is an Associate Professor and Graduate Director in the Department of Civil and Environmental Engineering at the University of Rhode Island. His research focuses on sustainable infrastructure materials, with particular expertise in cementitious materials, composite structures, and advanced computational modeling techniques. He directs a vibrant research group that bridges experimental mechanics with computational modeling and machine learning approaches to address challenges in infrastructure durability and performance. Dr. Das received his educational training from prestigious institutions: Ph.D. in Materials and Structures from Arizona State University (2015) M.Tech. in Structural Engineering from Indian Institute of Technology, Kanpur (2012) B.E. in Civil Engineering from Jadavpur University (2010) His research interests center around developing sustainable and durable infrastructure materials through innovative design approaches. Dr. Das investigates microstructure-property relationships in cementitious systems, with special focus on materials containing microencapsulated phase change materials for freeze-thaw durability, fiber-reinforced composites, and smart cementitious materials with self-sensing capabilities. His work integrates advanced experimental techniques like nanoindentation with computational modeling approaches including finite element analysis, molecular dynamics simulations, and machine learning algorithms to predict material behavior and optimize performance. Dr. Das's recent publications demonstrate a clear trajectory toward integrating machine learning with traditional materials science approaches. His research group has made significant contributions to understanding the behavior of cementitious composites under extreme conditions, developing multifunctional composites with embedded sensing capabilities, and creating computational frameworks that bridge multiple scales from molecular to structural levels. The work shows increasing sophistication in combining experimental validation with predictive modeling. Dr. Das has successfully secured numerous research grants as PI or Co-PI from diverse funding sources including the Office of Naval Research, Department of Defense, US Department of Transportation, and industry partners like Goetz Composites. His research portfolio spans infrastructure durability, composite materials for marine applications, and smart sensing technologies for structural health monitoring. As an educator and mentor, Dr. Das has supervised multiple doctoral and master's students who have completed theses on topics including: Multiscale simulation and machine learning-assisted performance prediction for cementitious composites Performance-based multiscale tuning of inclusion-modified and 3D printed composites Enhancing freeze-thaw durability of cementitious composites through innovative materials design Underwater explosion response of composite structures Implosion pulse mitigation using additively manufactured filler profiles
Per-Arne Andersen is an Associate Professor at the Department of Information and Communication Technology within the University of Agder . His research focuses on artificial intelligence , reinforcement learning , Tsetlin machines , and deep learning , with applications in real-time strategy games , industrial environments , and IoT systems . Projects: RESTORE Research Groups: CAIR - Center for Artificial Intelligence Research, CIEM - Center for Integrated Crisis Management, Intelligent Mechatronics (iTron) His work explores safe and sustainable reinforcement learning , interpretable AI , and generative environment modeling . He has developed frameworks like CaiRL and CostNet for high-performance RL environments and goal-directed learning. Recent publications include advancements in Tsetlin automaton analysis , GNSS jamming classification , and road quality detection . Articles from 2025-2016 span machine learning , computer vision , and environmental modeling . He contributes to IEEE , Springer , and LNCS publications, with a focus on interdisciplinary AI applications in crisis management , cybersecurity , and industrial optimization .
Irith Pomeranz is the Cadence Professor of Electrical and Computer Engineering at Purdue University's College of Engineering. Her research focuses on advanced testing methodologies for VLSI circuits, including functional test compaction, fault diagnosis, and built-in self-test (BIST) techniques. She is affiliated with the Department of Electrical and Computer Engineering and has contributed extensively to improving test efficiency and fault coverage in digital circuits. Her work addresses challenges such as aging effects, transition faults, and path delay faults, with a particular emphasis on practical implementations for industrial applications. Key areas of interest include modular test sequences, configuration-based compaction, and dynamic testing strategies for in-field environments. She has developed algorithms for dual-target diagnostic testing and synchronization mechanisms for online fault detection in logic blocks. Research Trends in her publications emphasize innovations like storage-based BIST schemes, adaptive test scheduling, and shared test data architectures. These advancements aim to reduce test data volume, improve fault coverage, and enhance reliability in modern integrated circuits. Her work often bridges theoretical foundations and practical hardware implementations. Grants & Advising : While specific grants or student advisees are not listed, her prolific publication record indicates active involvement in research projects and graduate supervision within Purdue's ECE department. Labs & Teams : Her contributions are likely tied to Purdue's VLSI and testing research groups, though specific lab affiliations are not detailed in the provided text.
Husheng Li is a Professor of Aero and Astro Engineering at Purdue University's School of Aeronautics and Astronautics. He holds a PhD in Electrical Engineering from Princeton University and bachelor's and master's degrees in Electronic Engineering from Tsinghua University. Education: PhD in Electrical Engineering, Princeton University BS and MS in Electronic Engineering, Tsinghua University Research Interests: Dr. Li's work focuses on autonomous and connected systems , UAV sensing and communications , and joint design of control and communication systems . His research integrates cyber-physical systems , statistical signal processing , and wireless communications , with recent emphases on integrated sensing and communications (ISAC) , MIMO systems , and waveform optimization . His innovations span OTFS modulation , secure ISAC networks , and multi-functional waveform design . Publications: His articles explore cutting-edge topics like waveform sensitivity analysis , spectral efficiency in ISAC , and secure communication protocols . His work bridges theoretical information theory with practical system implementations , often validated through experimental demonstrations. Grants & Advising: While specific grants or student advisees are not detailed here, his research aligns with major trends in autonomous systems and 6G communication technologies . His lab likely contributes to Purdue's broader efforts in smart infrastructure and cyber-physical systems .
