Sahar Sharifzadeh is an Associate Professor in the Department of Electrical & Computer Engineering at Boston University's College of Engineering. She holds an affiliation with the Boston University Institute for Global Sustainability (IGS). Her research focuses on predicting and understanding functional material properties using first-principles electronic structure methods, aiming to design novel materials for energy and technology applications. She earned her PhD in Electrical Engineering from Princeton University, an MA from Princeton, and a BS in Electrical Engineering from UC Berkeley. Her research group develops computational frameworks to model quantum mechanical phenomena in materials, including nanotubes, semiconductors, and biological systems. Recent work emphasizes machine learning integration and defect engineering in materials. She has contributed to software tools like Nexmd v2.0 for molecular dynamics simulations. Her advising and grants focus on training researchers in interdisciplinary computational methods. She collaborates with the IGS to advance sustainable energy technologies through material innovation.
Dr. Alexander Eichler is a Senior Lecturer (Privatdozent) and Senior Scientist at ETH Zürich's Department of Physics. His research focuses on nanomechanical sensing, spin-mechanics coupling, and parametric phase logic devices. He holds a permanent position at ETH since 2019 and became a Privatdozent in 2022. Education: Doctoral studies at University of Basel (2006–2009) Teaching: Teaches Classical and Quantum Parametric Phenomena (Autumn 2025). His work explores cutting-edge topics like nuclear spin detection, parametric instability landscapes, and topological classification of nonlinear systems. Research highlights include developing membrane-based scanning force microscopy and creating Boltzmann machines using coupled parametric oscillators. Awards: KITE award for teaching innovation (2022) Swiss Physical Society ABB Award (2012) Marie-Curie IEF Fellowship (2010) Current projects involve nanoscale MRI, stochastic dynamics in coupled oscillators, and parametric phenomena in graphene resonators. His lab develops advanced microscopy techniques and quantum-classical hybrid systems.
Sankar Das Sarma is a Distinguished University Professor and Director of the Condensed Matter Theory Center (CMTC) at the University of Maryland. He holds the Richard E. Prange Chair and is a leading researcher in condensed matter theory and quantum science. His work focuses on topological materials, quantum computing, superconductivity, and many-body phenomena. Das Sarma’s research explores theoretical frameworks for quantum technologies, including Majorana nanowires, topological superconductors, and quantum dot qubits. He has pioneered studies on disorder effects in topological systems and machine learning applications for quantum device optimization. His contributions to the fractional quantum Hall effect, moiré materials, and exciton condensation have been widely recognized. Notably, his group has advanced understanding of Majorana zero modes, Kondo lattice models in twisted bilayer graphene, and prethermal discrete time crystals. He has collaborated extensively on experimental platforms like germanium-based and graphene-based quantum systems. Das Sarma has received multiple recognitions, including being named a Highly Cited Researcher by Clarivate in 2018, 2019, and 2020. He leads the CMTC, fostering interdisciplinary research at the intersection of theory and experiment in quantum materials and technologies.
Ronald L Walsworth is a Professor of Physics and Electrical and Computer Engineering at the University of Maryland (UMD), holding the Minta Martin endowed professorship. He is the Founding Director of UMD's Quantum Technology Center (QTC), which focuses on advancing quantum science for translational applications and workforce education. His research develops precision measurement tools and quantum sensors applied to physical and life sciences, including quantum diamond magnetometry, NMR/MRI, and bioimaging. Education details are not explicitly stated in the provided texts. His work combines experimental and theoretical approaches, leveraging quantum defects in diamond and boron nitride for ultra-sensitive measurements. Notable contributions include quantum diamond microscopes, all-optical magnetometers, and applications in astrophysics, biomedical imaging, and dark matter detection. Recent research themes emphasize solid-state spin ensembles for high-resolution magnetic spectroscopy, machine learning for data analysis, and interdisciplinary collaborations. He advises graduate students like Andrew Beling (2025 Boron Nitride Workshop presenter) and has pioneered sensor systems with industrial and academic partners. Grants and collaborations include NASA-funded quantum sensing assessments and DOE initiatives. Labs/Teams: Director of Quantum Technology Center (QTC), leading teams in quantum microscopy, sensor development, and quantum workforce training programs at UMD.
Prof. Daniel P. Lathrop is a Professor of Geology at the University of Maryland, College Park. His research focuses on turbulence, geophysical/astrophysical magnetic fields, and nonlinear dynamics. He leads the Nonlinear Dynamics Laboratory, conducting experiments in liquid sodium models of planetary cores and magnetic dynamo action. Key projects include the Three-Meter Liquid Sodium Spherical Couette Experiment to simulate Earth's outer core dynamics. His work integrates geophysics, fluid dynamics, and advanced instrumentation with applications in environmental monitoring (e.g., methane flux measurement) and UXO detection via UAV-based geophysical systems. Recent collaborations explore quantum computing hardware, stochastic systems, and machine learning for predictive modeling of complex phenomena. Education: Ph.D. in Physics from University of Texas at Austin (1991) Research interests span experimental fluid dynamics, magnetic field amplification, granular material behavior under magnetic fields, and interdisciplinary applications of nonlinear physics. His lab innovates in geophysical sensing technologies, including magnetic gradiometry and multi-modal UAV platforms. Publications highlight advancements in dynamo experiments, magnetic anomaly detection, and novel approaches to computational hardware leveraging stochastic magnetic systems. Awards and recognitions are not explicitly listed in provided materials.
Wilfred G. van der Wiel is a Full Professor in the Nano Electronics department at the MESA+ Institute for Nanotechnology, University of Twente. His work bridges nanotechnology, quantum physics, and unconventional computing, focusing on novel hardware for machine learning and brain-inspired systems. Full Professor, Nano Electronics, MESA+ Institute, University of Twente Research Interests: His research lies at the intersection of nanoelectronics and cognitive computing. He investigates disordered dopant-atom networks in silicon , gold nanoparticle assemblies , and in-materio computing to develop energy-efficient, adaptive hardware. His work explores how physical systems can inherently perform computation, bypassing traditional von Neumann architectures. Publication Trends: Recent articles (2023–2025) highlight a shift toward practical implementations of neuromorphic computing, including speech recognition in physical systems and systematic reviews of brain-inspired architectures. Earlier works focus on fundamental transport mechanisms in nanostructures. Collectively, his publications reveal a trajectory from basic physics of nanodevices to applied neuromorphic engineering and software frameworks like Brains-PY. Scientific Contributions: While specific awards are not listed, his high-impact publications in journals like Nature and Physical Review Applied , along with continuous funding and supervision of research, indicate significant recognition in the field. Advising and Grants: He has supervised at least 29 research projects, including PhD and postdoctoral work, as indicated by 'Supervised Work (29)'. He leads or participates in externally funded projects related to nanotechnology and neuromorphic computing, evidenced by collaborative publications and datasets. Labs and Teams: He is a key member of the MESA+ Institute for Nanotechnology at the University of Twente, working within the Nano Electronics group. He collaborates extensively with researchers in physics, materials science, and computer science, particularly on projects involving unconventional computing and nanofabrication.
Michael L. Rivera is an Assistant Professor at the ATLAS Institute and the Department of Computer Science at the University of Colorado Boulder. He leads the Utility Research Lab, a highly interdisciplinary group that invents and investigates digital fabrication technology, tools, and techniques with the goal of advancing science and engineering while positively impacting people, society, and the environment. Dr. Rivera completed his Ph.D. and M.S. in Human-Computer Interaction at the Human-Computer Interaction Institute of Carnegie Mellon University, where he was advised by Scott Hudson as part of the DevLab. Before Carnegie Mellon, he earned a M.S.E in Computer Graphics and Game Technology and a B.S.E in Digital Media Design from the University of Pennsylvania. He also previously worked as a software engineer at Facebook. His research spans the intersection of digital fabrication, human-computer interaction, and material science. Dr. Rivera's work focuses on developing novel fabrication techniques such as desktop biofibers spinning, electrospinning, and sustainable material processing with everyday waste products like coffee grounds. His research has significant implications for sustainable manufacturing, tangible interfaces, and accessible technology design. Analysis of his recent publications reveals a consistent focus on making digital fabrication more accessible, sustainable, and interdisciplinary. His work bridges computer science, material engineering, and design, with particular emphasis on open-source hardware development, computational design tools, and applications for social good. The research demonstrates a progression from fundamental fabrication techniques toward more applied, socially conscious applications. CRA/CCC Computing Innovation Fellowship Google - CMD-IT Dissertation Fellowship Carnegie Mellon University Sansom Endowed Presidential Fellowship Adobe Research Fellowship Honorable Mention Xerox Technical Minority Scholarship Dr. Rivera is currently recruiting PhD students to join the Utility Research Lab. His research has been supported by various fellowships and grants throughout his career, including industry partnerships with Google and Adobe. His work demonstrates strong potential for future funding in sustainable manufacturing and accessible technology. The Utility Research Lab, directed by Dr. Rivera, is a highly interdisciplinary research group focused on inventing and investigating digital fabrication technology. The lab has developed several notable projects including the Desktop Biofibers Spinning Machine (presented at CHI 2024), desktop electrospinning technology (CHI 2019), and systems for 3D printing with spent coffee grounds. The lab maintains an active GitHub presence with numerous open-source repositories related to their research.
Dirk Englund is a Professor in the Department of Electrical Engineering and Computer Science (EECS) at MIT, leading the QP-Group focused on quantum technologies, nanophotonics, and optical systems. His research spans quantum computing, quantum sensing, and photonic integration, with emphasis on silicon photonics and 2D materials. Englund joined MIT in 2013 after roles at Columbia University and Harvard. He has pioneered advancements in quantum networks, photonic neural networks, and optical AI accelerators. Education: BS in Physics from Caltech (2002), MS in Electrical Engineering and PhD in Applied Physics from Stanford (2008). Postdoctoral research at Harvard (2008–2010). Research Interests: Quantum-enhanced sensing, solid-state quantum memories, spin-photon interfaces, and photonic integrated circuits. Key areas include silicon photonics for quantum information processing, 2D material-based optoelectronics, and optical quantum networks. Awards: 2011 PECASE, 2017 Adolph Lomb Medal, 2018 Bose Fellowship, 2020 Humboldt Fellowship. Active in developing MIT’s quantum engineering curriculum, including the 6-5 Electrical Engineering with Computing track. Labs/Teams: QP-Group collaborates with researchers like Dr. Ryan Hamerly and Dr. Matt Trusheim. Current projects include high-definition quantum-limited optical bolometry and photonic AI processors. Grants/Positions: Recipient of DARPA Young Faculty Award (2012), NSF grants, and industry partnerships with companies like Q Tools. Oversees research positions in quantum networks, photonics for machine learning, and 2D quantum devices.
Dr. Nooshin Mohammadi Estakhri is an Assistant Professor at Chapman University in the Fowler School of Engineering (Electrical Engineering and Computer Science) and Schmid College of Science & Technology (Physics). She holds a Ph.D. from the University of Michigan and prior degrees from the University of Tehran. Her research focuses on quantum computing, photonics, and metamaterials. Education B.S. and M.S. in Electrical Engineering, University of Tehran Ph.D. in Applied Physics, University of Michigan Research Interests Quantum dot spin qubit systems Resonator-mediated quantum interactions Metasurface engineering for radiative cooling Machine learning applications in optical trapping Coherent wave scattering in disordered media Spin-orbit coupling and quantum interference Key Article Trends Quantum information processing in modular architectures Machine learning for nanoparticle design Phase-change materials in photonic control Decoherence mechanisms in spin qubit systems Wave dynamics in metamaterials Entanglement protocols with virtual photons Grants National Science Foundation Grant No. 2137776 U.S. Army Research Office Grant No. W911NF-23-1-0115
Dr. Kenneth M. Hopkinson is a Professor of Computer Science and Head of the Department of Electrical and Computer Engineering at the Air Force Institute of Technology (AFIT) in Dayton, Ohio. He holds a Ph.D. and M.S. from Cornell University and a B.S. from Rensselaer Polytechnic Institute, all in Computer Science. He is a Senior Member of IEEE and ACM, reflecting his active engagement in the academic and professional communities. Ph.D., Computer Science, Cornell University, 2004 M.S., Computer Science, Cornell University, 2002 B.S., Computer Science, Rensselaer Polytechnic Institute, 1997 Dr. Hopkinson's research focuses on cybersecurity, networking, smart grid protection, critical infrastructure, and sensor fusion. His work integrates formal methods, machine learning, and distributed systems to enhance the reliability and security of cyber-physical systems. He has pioneered research in trust management, agent-based protection systems, and formal verification of safety-critical software. His recent publications highlight a strong trend in applying machine learning to hardware security, formal verification of algorithms, and resilience in critical infrastructure using social sensing. These works span domains from FPGA Trojan detection to SPARK-based verification of sorting algorithms, indicating a multidisciplinary approach that bridges theory and practical defense applications. Best Student Paper Award Winner, 15th International Command and Control Research and Technology Symposium (ICCRTS), 2010 Dr. Hopkinson has secured significant research funding and leads projects involving simulation, wargaming, and critical infrastructure protection. He has mentored numerous students through collaborative research, though formal advisee lists are not provided. He is actively involved in major research initiatives, including the EPOCHS simulation platform for power and communication systems. He has also contributed to book chapters and edited volumes on avionics cybersecurity and cyber-physical systems. He leads or contributes to research teams focused on cognitive radio networks, secure SCADA systems, and space applications. His work often involves interdisciplinary collaboration with electrical engineers, computer scientists, and defense analysts. Labs under his oversight likely include those in cybersecurity, network simulation, and hardware security, supporting both academic and military applications.
Roles and Affiliations: Danna Freedman is the Frederick George Keyes Professor of Chemistry at the Massachusetts Institute of Technology (MIT). She leads the Freedman Group, which focuses on quantum information science and high-pressure materials synthesis. Her work bridges synthetic chemistry with fundamental physics, creating molecular-based qubits and discovering novel intermetallic compounds at extreme pressures. Research Interests: Her research spans quantum technologies, materials science, and inorganic chemistry. Key areas include designing optically addressable molecular qubits, exploring spin dynamics under magnetic fields, and synthesizing emergent materials via high-pressure methods. The Freedman Group’s approach combines synthetic chemistry, spectroscopy, and computational modeling to engineer quantum systems with tailored properties. Key Contributions: Notable achievements include the discovery of FeBi₂ and Cu₃Pb through high-pressure synthesis, as well as advancements in spin-phonon coupling control for qubit stability. Recent work emphasizes ligand field design to enhance quantum coherence and modular integration of solid-state quantum systems. Labs and Teams: The Freedman Lab at MIT integrates synthetic chemistry, physics, and engineering to address grand challenges in quantum information and materials discovery. Collaborations span academia and industry, focusing on translating molecular qubit research into scalable quantum technologies.
Hyeongrak Choi is an Assistant Professor in the Department of Electrical and Computer Engineering at Stony Brook University. His research focuses on quantum information science, quantum computing, quantum photonics, and quantum networks. He is affiliated with the Light Engineering research group and specializes in developing scalable quantum systems through innovations in spin-photon interfaces, photonic integrated circuits, and entanglement protocols. His work emphasizes practical applications of quantum technologies, including congestion-free quantum networks, heterogeneous integration with CMOS platforms, and reinforcement learning-driven gate synthesis. Key contributions include designs for optical interconnects using 2D atomic emitters, cavity-based light-matter interactions, and entanglement distribution protocols leveraging percolation-based architectures. His research also intersects with nanofabrication techniques and superconducting materials for enhanced magnetic field control. Research Highlights Developed scalable quantum computing architectures using optical interconnects Pioneered congestion-free hierarchical entanglement routing protocols Advanced photonic integrated circuits for spin-photon coupling in CMOS platforms Designed ultrastrong magnetic light-matter interaction systems via cavity engineering Grants & Advising No specific grants or advisees are currently listed in the provided information. Labs & Teams His work is conducted in collaboration with the Light Engineering research group at Stony Brook, focusing on experimental and theoretical advancements in quantum photonics and integrated quantum systems.
Georgios Pappas is an Associate Professor at the School of Physics , Aristotle University of Thessaloniki since July 2025. Previously, he held positions as Assistant Professor there (2018–present), Researcher at Sapienza University of Rome (2018), and multiple Research Fellow/Postdoc roles at institutions including the University of Nottingham (2017–2018), Instituto Superior Técnico (2016–2017), University of Mississippi (2015–2016), and earlier postdoc/research roles since 2012. PhD in Physics (2005–2012), MSc (2001–2005), and Bachelor's (1996–2001) from the National and Kapodistrian University of Athens His research focuses on gravitational physics , particularly black holes and neutron stars in the context of general relativity , alternative gravity theories , and gravitational wave astronomy . Recent work includes applying machine learning to neutron star universal relations analyzing black hole shadows as tests of the no-hair theorem developing surrogate models for gravitational waveforms He has contributed to international collaborations like the Laser Interferometer Space Antenna (LISA) mission planning and has expertise in spacetime metrics , QPO analysis , and neutron star structure . Peer review activities centered on general relativity and celestial mechanics.
Farshad Moradi is a Professor at the Institute of Mechanical and Electrical Engineering, University of Southern Denmark, specializing in Microelectronics. His research spans spintronics, neuromorphic computing, and analog-to-digital conversion technologies. Current Role: Professor at SDU Microelectronics Research Focus: Spin-Orbit Torque, Magnetic Tunnel Junctions, CMOS Integration Collaborations: Active in international research networks with recent partnerships in Europe His work emphasizes the intersection of electronics, materials science, and computational innovation, particularly in spin-based hardware for AI applications. Recent publications highlight trends in hybrid spin-CMOS circuits and vortex dynamics for wearable sensors, demonstrating interdisciplinary impact.
Adrien F. Vincent is an Associate Professor at IMS Bordeaux (Laboratory of Integration, Material to System) under Université de Bordeaux, Institut Polytechnique de Bordeaux, and CNRS. He leads research in neuromorphic computing with a focus on spiking neural networks and memristive devices. His team, 2HC Production Engineering, develops energy-efficient hardware for real-time event-based data processing. Key research areas: Neuromorphic systems, Low-power electronics, Memristor technology Recent publications explore spintronic neural networks, STDP plasticity, and energy optimization His work addresses hardware-friendly learning algorithms and co-integration of analog silicon neurons with memristive arrays. Projects include ULPEC (Ultra-Low Power Event-Based Camera) and MIRA2015 (Memristive Architectures).
