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Shareq Mohd NazirView profile

Associate Professor

• Greenhouse Gas Mitigation
• Bioenergy Conversion
• Decarbonization of Industry
• +3 more

Shareq Mohd Nazir is an Associate Professor at KTH Royal Institute of Technology, affiliated with the Division of Energy Processes in the Department of Chemical Engineering. He holds a joint appointment within the Digital Futures Faculty, a cross-disciplinary research center addressing societal challenges through digital technology innovation. Nazir earned his PhD in Energy and Process Engineering from NTNU (2018) and holds Master and Bachelor degrees in Chemical Engineering from BITS Pilani. His research focuses on decarbonization strategies including CO2 capture/utilization (CCUS), bioenergy conversion, and methane mitigation. Key methodologies involve techno-economic analysis and process modeling for industrial systems. Nazir leads projects integrating catalytic conversion, waste heat recovery, and gas switching technologies to achieve low-carbon energy systems. He teaches courses on chemical engineering systems, process design, and carbon-neutral energy systems at KTH. Recent publications emphasize multi-gas mitigation strategies, synthetic fuel production via biomass gasification, and cost-effective hydrogen production pathways. His work bridges academia and industry through collaborations with RISE Research Institutes and NTNU. Nazir’s research directly supports Sustainable Development Goals (SDGs), particularly targeting climate action (SDG13) and affordable clean energy (SDG7).

Dharik MallapragadaView profile

Assistant Professor

• Energy System Decarbonization
• Low-Carbon Technologies
• Optimization Modeling
• +4 more

Dr. Dharik Mallapragada is an Assistant Professor in the Department of Chemical and Biomolecular Engineering at NYU Tandon School of Engineering, affiliated with the Center for Advanced Technology in Telecommunications (CATT). His research focuses on mathematical modeling to analyze low-carbon technologies and their integration into energy systems, emphasizing decarbonization pathways for developed and developing economies. He holds a B.Tech from IIT Madras and a Ph.D. in Chemical Engineering from Purdue University. Key research areas include optimizing energy infrastructure planning, electricity market designs for decarbonization, and techno-economic assessments of hydrogen production and storage. Recent work explores repurposing coal plants into thermal storage, evaluating rate structures for renewables-dominant grids, and analyzing India’s energy transition challenges. Mallapragada’s work bridges computational techniques like optimization modeling and data analytics with real-world policy and geographical contexts. Publications highlight infrastructure synergies between power and gas systems, hydrogen production pathways, and electrification barriers in heavy industries. His research underscores the importance of flexible energy systems and equitable policy frameworks, particularly for emerging economies. The Sustainable Energy Transitions (SET) group he leads collaborates globally to address climate mitigation challenges through analytical tools and cross-sectoral solutions.

James RoscowView profile

Senior Lecturer

• Ferroelectric Materials
• Piezoelectric Energy Harvesting
• Energy Storage
• +3 more

James Roscow is a Senior Lecturer in the Department of Mechanical Engineering at the University of Bath, affiliated with the Centre for Integrated Materials, Processes & Structures (IMPS), IAAPS, and the Institute of Sustainability and Climate Change. His research focuses on developing ferroelectric composites for energy harvesting, sensing, and energy storage, with expertise in material fabrication, property tuning, and numerical modeling. He holds a PhD in Mechanical Engineering from the University of Bath and a BSc in Materials Science from the University of Manchester. Research interests include porous ferroelectric ceramics, piezoelectric and pyroelectric materials, and their applications in renewable energy and sensors. He has led or contributed to 12 projects funded by organizations like EPSRC and Innovate UK, exploring topics such as low-cost transducers, nanofluid cooling for solar panels, and phase transformations in ceramics. Key publications (2021–2025) address piezoelectric energy harvesting, porous material design, and advanced manufacturing techniques. His work aligns with UN SDGs, particularly sustainable energy and innovation. Roscow supervises PhD students in functional ceramics, energy storage, and sensor technologies. Notable collaborations include projects on hydraulic energy harvesters, SONAR transducers, and self-healing materials. He has contributed datasets on piezoelectric composites and energy storage systems, emphasizing reproducibility and applied research.

James TuckView profile

Professor

• Computer Architecture
• Compiler Design
• Chip Multiprocessors
• +3 more

James Tuck is a Professor and Senior Associate Department Head for Undergraduate Affairs in the Department of Electrical and Computer Engineering at NC State University. He holds a BE from Vanderbilt University, and MS and PhD from the University of Illinois at Urbana-Champaign. His research focuses on computer architecture, compiler design, and DNA-based data storage, with notable contributions to chip multiprocessors and speculative execution. He has been recognized with two IEEE Micro Top Picks Paper Awards and the William F. Lane Outstanding Teaching Award. Education: Ph.D. in Computer Science, University of Illinois at Urbana-Champaign (2007) MS in Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (2003) BE in Computer Engineering, Vanderbilt University (1999) Research Interests: Computer Architecture and Systems Compiler Design for Multiprocessors Hardware Support for Speculative Execution Advances in DNA Data Storage Non-Volatile Memory Systems Recent work emphasizes DNA storage scalability and security, including frameworks like FrameD and innovations in nanopore decoding. His articles span hardware optimization, persistent memory security, and biochemical storage solutions. Awards highlight both technical and pedagogical excellence. Advising and Grants: Leadership in Undergraduate Engineering Affairs NSF grants for DNA storage and memory systems Labs/Teams: Member of Undergraduate Affairs Team in NC State ECE Collaborations with Chemical and Biomolecular Engineering

Paul LeahyView profile

Lecturer

• Wind Energy
• Renewable Energy
• Circular Economy
• +4 more

Dr. Paul Leahy is a Lecturer in Wind Energy Engineering at University College Cork (UCC) and a funded investigator in the SFI MaREI Centre for Energy, Climate, and Marine Research. He leads research on wind energy, circular economy applications for decommissioned turbine blades, and climate change impacts. His work includes the Re-Wind project, a transdisciplinary initiative funded by SFI, NSF, and Northern Ireland's Department for the Economy. He co-supervises six PhD students and has examined over 20 theses globally. Education: BE Electrical Engineering (1995), PhD Electrical Engineering (2001), Postgraduate Certificate in Teaching & Learning in Higher Education (2018). Research & Awards: Research focuses on wind energy forecasting, energy storage, and greenhouse gas emissions. Notable awards include the Environmental Research Letters' 2013 Highlight and an ISI Highly Cited Paper (2012). He contributed to IPCC Special Reports on climate change mitigation and co-edits Renewable & Sustainable Energy Reviews. Grants & Projects: Secured €320,000 for Re-Wind and led multiple EU, EPA, and industry-funded projects. Current research includes lifecycle assessments of repurposed turbine blades and hydrogen production via offshore wind. Teaching & Outreach: Coordinates modules like NE6003 Wind Energy Engineering and contributes to energy systems education. Engages in public lectures and policy initiatives like Energy Cork Cluster leadership. Labs & Teams: Collaborates with multidisciplinary teams on infrastructure repurposing (e.g., BladeBridges) and climate adaptation strategies for agriculture and peatlands.

• Control Systems
• Model Predictive Control
• Power Systems Engineering
• +3 more

Morten Hovd is a Professor in the Department of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU). His research focuses on advanced control systems, model predictive control (MPC), power electronics, and optimization algorithms. He has contributed significantly to the development of robust control strategies for uncertain systems and has published extensively in leading journals and conferences in the field of control engineering. His research interests span several key areas in control systems engineering, including model predictive control, nonlinear control systems, optimization under uncertainty, and applications in power systems and energy efficiency. He is particularly known for his work on discrete-time bilinear systems, modular multilevel converters (MMCs), and the integration of machine learning techniques with control theory. His contributions address both theoretical advancements and practical implementations in industries such as energy and petroleum engineering. Hovd's recent publications highlight advancements in energy-efficient control systems, stochastic surrogate modeling for subsurface flows, and optimization algorithms tailored for complex engineering problems. His work often combines rigorous mathematical frameworks with real-world applications, such as improving the reliability of power systems and enhancing reservoir management through data-driven methods. He is actively involved in teaching courses such as TTK4210 (Advanced Control of Industrial Processes) and TK8118 (Mini-seminar in Cybernetics). His research has led to innovations in fault detection for power systems, energy-efficient building climate control, and robust MPC strategies for uncertain systems.

Emanuele CrisostomiView profile

Associate Professor

• Smart Grids
• Electric Vehicles
• Control Systems
• +2 more

Emanuele Crisostomi is Associate Professor of Electrical Systems at the University of Pisa's Department of Energy, Systems, Territory and Constructions Engineering. He holds PhD and graduate degrees in Automation Engineering from the University of Pisa, with research visits to University of Cambridge, University of Leicester, and Hamilton Institute. His research bridges control theory, energy systems, and smart mobility. His research integrates: Smart grid control and renewable energy integration Electric vehicle charging infrastructure and routing algorithms Urban traffic modeling and optimization Nonlinear system dynamics and Lyapunov stabilization Machine learning applications in energy systems Crisostomi's publications demonstrate consistent innovation in electric vehicle-grid integration, with recent focus on predictive charging control, highway EV circulation patterns, and hydropower monitoring. His work shows increasing application of deep reinforcement learning for multi-regional power systems and hybrid network models for infrastructure monitoring. He leads research on IoT-enabled energy efficiency in buildings and contributes to epidemic modeling through network science. Current projects examine battery sizing optimization, charging station scheduling under uncertainty, and synergetic building management systems integrating environmental monitoring with energy conservation.

Elena Castell-PerezView profile

Professor

• Food Engineering
• Biomaterials Science
• Food Safety Technologies
• +5 more

Elena Castell-Perez is a Professor at Texas A&M University's College of Agriculture & Life Sciences, Department of Biological and Agricultural Engineering. She holds a B.S. in Food Engineering from Campinas State University (1980), followed by an M.S. (1984) and Ph.D. (1990) in Agricultural Engineering from Michigan State University. Her research focuses on food safety technologies, including antimicrobial packaging systems, biomass pretreatment for bioenergy, and food irradiation applications. She is affiliated with Texas A&M AgriLife Research and Extension Service. Her work integrates nanotechnology (e.g., ZIF-8 nanoparticles) with food engineering to enhance packaging safety and develop sustainable materials. Key contributions include optimizing electron beam irradiation for pathogen decontamination and advancing predictive modeling for microbial contamination risks in fresh produce. She also explores CO₂ capture innovations for agricultural sustainability. Recent articles highlight advancements in antimicrobial delivery systems, 3D-printed biomass composites, and machine learning for food safety prediction. Her research spans food rheology, smart packaging, and waste reduction within the water-energy-food nexus. Dr. Castell-Perez collaborates on multidisciplinary projects involving food phantoms, Monte Carlo simulations for irradiation dosimetry, and agent-based modeling of microbial cross-contamination. Her labs focus on translating engineering principles into practical solutions for the food industry.

Dan S. WallachView profile

Professor

• Computer Security
• Cybersecurity
• Electronic Voting Systems
• +3 more

Dan S. Wallach is a Professor of Computer Science and Electrical and Computer Engineering at Rice University, and a Program Manager at DARPA's Information Innovation Office since June 2023. He holds a PhD (1999) and MA (1995) from Princeton University, and a BS (1993) from UC Berkeley. His research focuses on cybersecurity, electronic voting systems, and mobile security. He directed the NSF-funded ACCURATE Center (2005-2011), led the STAR-Vote project, and advised U.S. election security policies including testifying before state and federal committees. He also served on the Air Force Science Advisory Board (2011-2015), USENIX Board (2011-2013), and IEEE Technical Guidelines Committee (2019-2023). Recent work includes developing ElectionGuard cryptographic tools for verifiable elections and analyzing cyber warfare in Ukraine. His 15+ years of teaching include courses like Introduction to Program Design and Election Systems Technologies. Publications span secure voting protocols, smartphone security, and election auditing. Collaborations include Microsoft and VotingWorks on cryptographic voting systems like ElectionGuard and Arlo-CVR-Encryption.

• Algorithms
• Data Structures
• Pattern Matching
• +3 more

Simon J. Puglisi is a Professor in the Department of Computer Science at the University of Helsinki. His research focuses on algorithms, data structures, pattern matching, and data compression, with applications in bioinformatics and genomics. He has collaborated extensively with researchers in the field, including Travis Gagie, Juha Kärkkäinen, and Andrew Turpin. His work spans theoretical computer science and practical applications in genomic data processing and efficient indexing techniques. Key research interests include genome sequencing algorithms, efficient compression methods (e.g., Lempel-Ziv and relative Lempel-Ziv), and the development of succinct data structures for handling large genomic datasets. His contributions to suffix arrays, wavelet trees, and de Bruijn graphs have advanced computational methods in bioinformatics and information retrieval. Puglisi's articles frequently address challenges in text indexing, error correction in short-read sequencing, and optimizing algorithms for scalability. He is known for his work on self-indexing techniques and the SHREC error correction method for genomic data. His research bridges theoretical algorithm design with real-world applications in high-throughput sequencing and large-scale data management.

Ashish VenkatView profile

Associate Professor

• Computer Architecture
• Compilers
• Computer Security
• +12 more

Ashish Venkat is an Associate Professor in the Department of Computer Science at the University of Virginia, part of the School of Engineering and Applied Science. He holds a Ph.D. from UC San Diego and has established himself as a leading researcher in computer architecture, compilers, and computer security. Research Interests: His research focuses on cross-disciplinary hardware and software techniques to build secure, high-performance computing systems. He investigates robust exploit mitigations that maintain energy efficiency and programmability, with a particular emphasis on speculative execution, memory safety, hardware security, and privacy-preserving computing. He also explores the application of machine learning to detect security threats and model execution behavior. Publication Trends: His recent publications (2020–2025) demonstrate a strong focus on hardware-based security, particularly microarchitectural vulnerabilities (e.g., micro-op cache attacks), memory safety via microcode capabilities, and secure accelerators for bioinformatics. There is a consistent trend of publishing in top-tier venues like ISCA, MICRO, IEEE S&P, and USENIX Security, often featuring novel hardware/software co-design solutions. Scientific Awards: NSF CAREER Award (2023) NSF CRII Award (2018) IEEE Micro Top Pick (2019) IEEE Design & Test Top Pick (2020, 2021) HPCA Best Paper Runner-Up (2019) DATE Best Paper Nominee (2023) UVA Research Achievement Award (2023) ISCA Prolific Author of the Decade (2013–2022) Advising and Grants: He actively mentors graduate and undergraduate students, many of whom have pursued advanced degrees or joined leading tech companies. He has secured significant funding as PI or co-PI from NSF, DARPA, SRC, and Intel, including a $4.9M DARPA HERCULES grant and an NSF CAREER award. His projects focus on holistic security solutions, speculative optimization, and privacy-preserving machine learning frameworks. Labs and Teams: He leads a research group focused on secure and efficient computing systems, collaborating with researchers at institutions like UC San Diego, UC Riverside, and UC Irvine, as well as industry partners including Intel and IBM.

Glenn GulakView profile

Professor

• Homomorphic Encryption
• Quantum Cryptography
• CMOS Biosensors
• +4 more

Glenn Gulak is a Professor in the Department of Electrical and Computer Engineering at the University of Toronto's Faculty of Applied Science and Engineering. He holds the Canada Research Chair in Signal Processing Microsystems and the Edward S. Rogers Sr. Chair in Engineering. A Senior IEEE Member and Professional Engineer in Ontario, he received his Ph.D. from the University of Manitoba. His research spans: Digital Communication Systems: VLSI implementations of MIMO detectors, lattice reduction algorithms, and homomorphic encryption accelerators Lab-on-Chip Microsystems: CMOS biosensors for rapid pathogen detection and integrated fluorescence imaging Recent publications (2019-2025) demonstrate a dominant focus on privacy-enhancing technologies, with 73% concentrated in cryptographic hardware and homomorphic encryption. This reflects industry-aligned work on confidential computing and secure data processing. Awards & Honors: IEEE Millennium Medal (2001) Canada Research Chair in Signal Processing Systems (Tier 1, 2005-2012) Edward S. Rogers Sr. Chair (2005-2010) RBC Research Prize L. Lau Chair (1999-2004) Teaching Award (1999) He has supervised 44+ graduate students (PhD/MASc) with thesis topics spanning VLSI communication systems, CMOS biosensors, and cryptographic accelerators. Notable industry collaboration includes serving as CTO of a semiconductor startup (2001-2003). His lab develops hardware for quantum cryptography and secure medical computation.

İsmail ArıView profile

Assistant Professor

• Cloud Computing
• Big Data
• Machine Learning
• +12 more

Dr. İsmail Arı is an Assistant Professor in the Computer Science department at Özyeğin University . He holds a PhD from the University of California, Santa Cruz (2004), MS from University of Maryland (2000), and BS in Electrical & Electronics Engineering from Boğaziçi University (1998).

Samarjit ChakrabortyView profile

Professor

• Distributed Embedded Systems
• Hardware/Software Co-design
• Embedded Control Systems
• +9 more

Samarjit Chakraborty is the William R. Kenan, Jr. Distinguished Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. He previously held the Chair of Real-Time Computer Systems at the Technical University of Munich (2008–2019) and was an assistant professor at the National University of Singapore (2003–2008). His research spans real-time embedded systems, cyber-physical systems (CPS), and automotive security. Research Interests include distributed embedded systems, hardware/software co-design, low-power systems, energy storage, electromobility, and sensor network-based information processing. His work addresses challenges in scheduling algorithms for autonomous vehicles, timing predictability in automotive networks, and safety-critical controller implementations. Recent Publications highlight advancements in Timing analysis for automotive networks Energy modeling of Bluetooth Low Energy Autonomous vehicle perception computing Security in automotive systems Flexible manufacturing with process dynamics Scientific Awards include the ETH Medal, European DAAD Outstanding Doctoral Dissertation Award, multiple best paper awards at conferences (ISLPED, ICCD, RTCSA, etc.), the 2023 Humboldt Professorship, and IEEE Fellowship. Advising active PhD students: Clara Hobbs, Shengjie Xu, Sharmin Aktar, and postdoc Enrico Fraccaroli. His research is supported by NSF grants and industry partnerships with General Motors, Intel, Google, BMW, Audi, Siemens, and Bosch.

Rolf WankaView profile

Professor

• Algorithms
• Combinatorial Optimization
• Swarm Intelligence
• +3 more

Prof. Dr. Rolf Wanka is a Professor at the Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), specializing in efficient algorithms and combinatorial optimization. His research focuses on swarm intelligence, discrete optimization algorithms, and scheduling problems, particularly in timetabling and robotics applications. Education : Sc.D. (Dr. rer. nat.) in Computer Science His work includes theoretical and experimental analyses of particle swarm optimization (PSO) algorithms, addressing runtime complexity, stagnation behavior, and convergence properties. He has developed novel heuristics for timetabling and sorting problems, with applications in multi-robot systems and medical imaging. Notable collaborations include studies on Markov chain-based PSO and fairness in academic scheduling. Key trends in his recent publications span swarm intelligence , discrete optimization , and scheduling heuristics , with a focus on robust timetabling , runtime analysis , and stochastic algorithm behavior . While no explicit scientific awards are listed, his mentorship in the Max Weber-Programm highlights his advisory role in academia. His publications demonstrate interdisciplinary applications of algorithms in robotics , medical imaging , and parallel computing , leveraging both theoretical rigor and practical experimentation. The full description below provides exhaustive details on his academic contributions and affiliations.