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Prineha NarangView profile

Professor

• Quantum Materials
• Quantum Information Science
• Non-Equilibrium Dynamics
• +7 more

Dr. Prineha Narang is a Professor of Physical Sciences and Electrical and Computer Engineering at the University of California, Los Angeles (UCLA). Previously, she held positions as an Assistant Professor at Harvard University and a Research Scholar at MIT. Her research focuses on quantum materials, quantum information science, and non-equilibrium dynamics, with interdisciplinary contributions to photonics, topological materials, and cavity quantum electrodynamics (QED). She leads the Narang Lab, which develops theoretical and computational methods to design quantum systems and explores applications in quantum networks and energy conversion. Dr. Narang has held leadership roles in major initiatives such as the DOE Quantum Science Center and the NSF Center for Quantum Networks. She is also the founder and CTO of Aliro Quantum, a company advancing quantum networking technologies. Education: M.S. and Ph.D. in Applied Physics from the California Institute of Technology (Caltech). Her work has been recognized with prestigious awards, including the Mildred Dresselhaus Prize, NSF CAREER Award, and being named a Moore Inventor Fellow. She serves on editorial boards for journals like ACS Nano and Applied Physics Letters , and chairs international conferences. Outside academia, she advises organizations like arXiv and actively engages in promoting quantum technologies through industry collaborations. Research Interests: Quantum materials engineering, quantum networks, non-equilibrium phenomena, topological quantum states, and quantum defect physics. Current projects include designing scalable quantum repeaters, developing error-corrected quantum systems, and studying light-matter interactions in novel materials. Her lab’s SpaRTaNS code enables spatially-resolved transport simulations, advancing understanding of electron and phonon dynamics. Awards and Grants: Over 20 major awards, including the Guggenheim Fellowship (2023), ONR Young Investigator Award (2022), and leadership roles in DOE and NSF-funded centers. Her work bridges academia and industry, with partnerships at companies like Applied Materials and Northrop Grumman.

Cam Ha TranView profile

Assistant Professor

• Neuroscience
• Cardiovascular Physiology
• Neurovascular Coupling
• +4 more

Cam Ha Tran is an Assistant Professor in the Department of Physiology and Cell Biology at the University of Nevada, Reno, affiliated with the Institute of Neuroscience. Her research focuses on neurovascular unit interactions, particularly how blood flow regulation impacts brain function under health and disease conditions such as stroke and dementia. She employs advanced techniques like two-photon imaging, optogenetics, and electrophysiology to study astrocyte-endothelial communication and vascular reactivity. Education: PhD in Cardiovascular and Respiratory Sciences from the Cumming School of Medicine, University of Calgary (Canada); Master of Biomedical Technology and Bachelor of Science from the University of Alberta (Canada). Research emphasizes understanding how astrocytes and endothelial cells coordinate to maintain cerebral blood flow, with implications for neurological disorders. Her recent work explores TRPA1 channels in neurovascular coupling, astrocyte dysfunction in Alzheimer’s, and seizure-induced vascular changes. Techniques include in vivo imaging and chemogenetic approaches to dissect cellular mechanisms. Key contributions include uncovering astrocyte roles in functional hyperemia and identifying therapeutic targets for cerebrovascular diseases. Her lab’s findings bridge basic science and clinical applications, aiming to improve diagnostics and treatments for stroke and neurodegenerative conditions.

Jeff LundeenView profile

Associate Professor

• Quantum Optics
• Photonics
• Quantum Computing
• +3 more

Dr. Jeff Lundeen is an Associate Professor in the Department of Physics at the University of Ottawa's Faculty of Science. His research focuses on experimental and theoretical quantum physics, particularly in photonics and quantum computing. He leads the Lundeen Lab, developing methods to manipulate single photons and entangled photon pairs for quantum logic, communication, and metrology applications. Research interests include experimental photonics, quantum-enhanced sensors, quantum metrology, and quantum optics. His work addresses challenges in quantum device development, such as ultra-thin imaging systems and quantum state tomography. Key contributions include direct measurements of quantum wave functions and density matrices, weak value amplification techniques, and space-compressing optics. His recent publications (2023–2025) explore neural adaptive quantum tomography, quantum metrology in noisy environments, and reconfigurable optical systems. Dr. Lundeen collaborates internationally on projects like quantum state estimation and photon pair generation in fibers. His lab emphasizes practical applications of quantum principles in sensors, communication, and imaging technologies.

Amritanshu PandeyView profile

Assistant Professor

• Grid Simulation and Optimization
• Grid Cybersecurity
• Modeling of Future Energy Systems
• +3 more

Amritanshu Pandey is an Assistant Professor in Electrical Engineering at the University of Vermont, with a part-time adjunct appointment in Electrical and Computer Engineering at Carnegie Mellon University. His research focuses on enhancing the efficiency, reliability, and security of electric grids through methods in circuit theory, optimization, and machine learning. He pioneered the SUGAR simulation engine for power systems and collaborates globally on grid challenges. Research Interests: Pandey's work spans renewable integration, grid cybersecurity, digital twins, and decarbonization. Key projects include developing algorithms for large-scale grid optimization, anomaly detection, electric vehicle infrastructure modeling, and cyber-resilient energy systems. His research addresses real-world challenges in rapidly evolving grids across Asia and Africa. Awards: Best Paper Award, IEEE PES General Meeting (2017, 2021) Best-of-the-Best Paper Award, IEEE PES General Meeting (2021) Best Student Paper Runner-up, ECML-PKDD (2018) Students & Labs: He advises 7 PhD students and has graduated 11 advisees (PhD/MS/BS). His lab focuses on power systems innovation, including the SUGAR simulation framework and projects on grid cybersecurity and sustainable electrification.

• Wireless Networks
• Signal Processing
• 5G/6G Communications
• +3 more

Dr. Wibowo Hardjawana is a Senior Lecturer in Telecommunications Engineering at the School of Electrical & Computer Engineering , University of Sydney. He holds a PhD from the University of Sydney and serves as an ARC DECRA Research Fellow. His research focuses on wireless network softwarisation, enabling programmable radio interfaces to address traffic elasticity in 5G/6G systems. Education : PhD (University of Sydney) Grants : ARC DP210100744 (2021), ARC DECRA DE140101114 (2014) His work spans 5G/6G network architectures , machine learning for wireless systems , and open radio interfaces . Key contributions include graph representation learning for interference management, Bayesian neural network detectors for OTFS modulation, and NOMA decoding techniques . Recent publications analyze ultra-reliable low-latency communications , UAV-enabled networks , and stochastic geometry in wireless systems . He has collaborated with institutions in China, Indonesia, and UAE, and engaged with industry partners like Telstra and Ausgrid.

Tobias BrandtView profile

Professor

• Digital Innovation
• Public Sector Management
• Information Systems
• +5 more

Prof. Dr. Tobias Brandt serves as a Full Professor and Chair of Digital Innovation and the Public Sector at the University of Münster's School of Business and Economics. His academic journey includes roles as Assistant Professor at Rotterdam School of Management (2016-2021) and Research Assistant at the University of Freiburg (2011-2015). He co-founded Geospin GmbH in 2016 and holds memberships in VHB, INFORMS, and AIS. Research Interests: Brandt focuses on digital innovation in public sectors, sustainable urban systems, e-government, and platform ecosystems. His work bridges information systems and operational research to address challenges in mobility, energy, and public service delivery. Recent projects include developing tools for sustainable urban planning, digital platforms for elderly care, and leveraging AI for crisis management. Notable Projects: Current initiatives include the PIONEER II Master's program on public innovation, SMARD-Gov (LLMs for government decision-making), and comuneo (digital sustainability management platform). Completed projects include INNO4S (integrating sustainability in business education) and studies on pandemic-driven digitalization in public administration. Awards: RSM Teaching Award (2020), Daniel H. Wagner Prize (2020), IBM Faculty Award (2016). Grants: €5M+ secured from EU Erasmus+, DFG, and German Federal Ministry of Research. Labs/Teams: Leads the Chair of Digital Innovation & Public Sector, collaborating with ERCIS (European Research Center for Information Systems). Active in GovTech and digital sustainability initiatives.

Jihong WangView profile

Professor

• Power System Modelling and Control
• Energy Storage and Grid Integration
• Energy Efficient Actuators
• +3 more

Professor Jihong Wang is a faculty member at the University of Warwick's School of Engineering, where she has held the position since January 2011. She previously served as a Professor of Control and Electrical Power at the University of Birmingham and held academic roles at the University of Liverpool from 1998 to 2007. As the Head of the Power and Control Systems Research Laboratory, her research focuses on power system modeling and control, energy storage integration, and energy-efficient actuators. Her work has led to over 100 journal publications and several industry collaborations, including a smart voltage controller and a clean pneumatic UPS. She led the EPSRC-funded IMAGES project, developing an open-source software tool for energy storage systems. Professor Wang actively contributes to energy storage initiatives, including co-leading the Supergen Energy Storage Hub and the Joint UK-India Clean Energy Centre (JUICE). Her funded projects span compressed air energy storage (CAES), grid-tied photovoltaic inverters, and net-zero engineering innovation. She advises on energy policy and has pioneered innovations in thermal storage, grid decarbonization, and renewable energy integration. Her research bridges academic rigor and practical applications, addressing critical challenges in sustainable energy systems. Her professional engagement includes roles like Deputy Director of the Supergen Energy Storage Network+ and collaborations with global institutions. Her work emphasizes interdisciplinary approaches to energy challenges, combining control systems, thermal engineering, and policy analysis. Professor Wang’s contributions have been recognized through best paper awards and leadership in major energy storage consortia.

Thia KirubarajanView profile

Professor

• Estimation Theory
• Multisensor-Multitarget Tracking
• Information Fusion
• +7 more

Dr. Thia Kirubarajan is a Professor and Distinguished Engineering Professor in the Electrical and Computer Engineering Department at McMaster University. He holds the NSERC/General Dynamics Mission Systems-Canada Industrial Research Chair in Target Tracking and Information Fusion. His expertise spans Estimation Theory, Multisensor-Multitarget Tracking, Information Fusion, and Signal Processing. He has led the Estimation, Tracking and Fusion Research Laboratory (ETFLab) with over 50 students and researchers, including PhD candidates and postdoctoral fellows. His academic journey includes degrees from Cambridge University (B.A., M.A.) and the University of Connecticut (M.S., Ph.D.). Education: B.A./M.A. (Cambridge, UK), M.S./Ph.D. (University of Connecticut, USA) Research Interests: Multisensor tracking, sensor fusion, fault diagnosis, and autonomous systems Dr. Kirubarajan has received notable awards including the Barry Carlton Award and Ontario Premier's Research Excellence Award. He teaches advanced courses like Algorithms for Parameter and State Estimation (ECE 771) and has advised numerous students across PhD, M.A.Sc., and undergraduate levels. His research lab collaborates internationally, hosting visiting scholars and fostering innovation in smart systems and transportation.

Shahin SirouspourView profile

Professor

• Robotics
• Autonomous Systems
• Control Systems
• +7 more

Shahin Sirouspour is a Professor in the Department of Electrical and Computer Engineering at McMaster University. His research focuses on robotics, autonomous systems, control systems, and optimization, with applications in aerial robotics, teleoperation, haptics, medical robotics, and smart energy grids. He is affiliated with the Telerobotics, Haptics and Computational Vision Laboratory and teaches courses such as Non-linear Control Systems and Electrical Systems Integration Project. He holds a Ph.D. from the University of British Columbia and has supervised numerous graduate students. His lab includes advanced equipment like multi-axis robotic manipulators, haptic interfaces, and real-time computing systems. Education: B.Sc. and M.Sc. from Sharif University of Technology (Iran), Ph.D. from University of British Columbia (Canada). Current roles include accepting graduate students and leading research clusters in Digital & Smart Systems, Energy, and Transportation. Awards include the McMaster President's Award for Excellence in Graduate Supervision. His work bridges theoretical control systems with practical applications in healthcare, energy, and autonomous systems. Research highlights include developing control strategies for multi-agent robotic systems, smart grid optimization, and medical robotics. Collaborations with institutions like MacAUTO and industry partners (e.g., MDA Space Missions) enhance translational impact. His lab supports projects on asymmetric teleoperation, deformable tissue simulation, and microgrid energy management.

Nadjib BRAHIMIView profile

Associate Professor

• Supply Chain Management
• Production Planning and Scheduling
• Operations Research
• +4 more

Nadjib Brahimi is an Associate Professor at Rennes School of Business, specializing in Supply Chain Management and Operations Research. He holds a PhD in Production and Logistics Systems from Université de Nantes and has extensive academic experience, including roles as Academic Head of the Supply Chain Management & Information Systems department (2019–2020) and Programme Manager of the MSc in Data and Business Analytics. His expertise spans Production Planning, Supply Chain Optimization, and Reconfigurable Manufacturing Systems. Education: PhD in Production and Logistics Systems, Université de Nantes, 2004 M.Sc. in Automatic Control and Applied Computing, Ecole Centrale de Nantes, 2001 Engineering Degree in Electronics and Electrical Engineering, National Institute of Electronics and Electrical Engineering, Boumerdes, Algeria, 1999 Research Focus: His work emphasizes optimization of production systems, reconfigurable manufacturing, and sustainable supply chains. Key areas include task reassignment in assembly lines, biomass supply chain design, and disruption resilience strategies. Key Contributions: Over 40 peer-reviewed articles in journals like International Journal of Production Economics and European Journal of Operational Research . Developed robust optimization models for supplier selection and production routing. Advocated for circular economy principles in hybrid manufacturing systems. Labs/Teams: He collaborates with research groups on reconfigurable manufacturing systems and bioenergy supply chain design, contributing to projects in France, UAE, and Algeria.

Ramana VinjamuriView profile

Associate Professor

• Brain-Machine Interfaces
• Neuroprosthetics and Exoskeletons
• Machine Learning
• +4 more

Ramana Vinjamuri is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He holds a secondary appointment as Visiting Professor at the Indian Institute of Technology, Hyderabad, India. His academic journey includes a Ph.D. in Electrical Engineering from the University of Pittsburgh (2008), M.S. in Bioinstrumentation from Villanova University (2004), and B.Tech. in Electrical and Electronics Engineering from Kakatiya University (2002). Dr. Vinjamuri's research focuses on Brain-Machine Interfaces (BMIs) for upper-limb prostheses control , neuroprosthetics and exoskeletons , machine learning in motor control , and neurophysiological signal processing . His work extends synergy-based models to control 37-dimensional hand movements, addresses human-robot interaction through emotionally intelligent systems, and develops neurotechnologies for substance use disorder using wearable sensors and AI. NSF CAREER Award (2019) NSF IUCRC BRAIN Center Planning Grant (2020) Harvey N Davis Distinguished Teaching Assistant Professor Award (2018) His publications demonstrate expertise in EEG and EMG signal analysis , deep learning for motor decoding , synergy modeling , and humanoid robot control . The Vinjamuri Lab at UMBC involves graduate, undergraduate, and high school researchers, with international collaborations in India and the US.

• Control Systems
• Signal Processing
• Neuro-Fuzzy Systems
• +3 more

Dragan S. Antic is a Professor at the Department of Automation, Faculty of Electronics, University of Niš. He earned his PhD in Automation from the same institution in 1994, following a Master's (1991) and Bachelor's (1987) degree in the same field. His research focuses on control systems, signal processing, and neuro-fuzzy systems, with a strong emphasis on sliding mode control, orthogonal function-based modeling, and adaptive neural networks. He has published 51 papers in journals with impact factors and currently participates in 2 national and 8 international research projects. Key research areas include dynamic system modeling, quasi-orthogonal filters, and finite-time stability analysis of time-delay systems. His work often integrates mathematical techniques with engineering applications, such as anti-lock braking systems and PID control optimization. Contact details include his office at Aleksandra Medvedeva 4, Niš, and the email dragan.antic@elfak.ni.ac.rs. Professional contributions include foundational research in endocrine neural networks and low-pass filter design, with notable publications in journals like Electronics Letters and Journal of the Franklin Institute . His efforts bridge theoretical advancements with practical engineering solutions in automation and control.

Manxi WuView profile

Assistant Professor

• Societal Networks
• Game Theory
• Network Optimization
• +4 more

Manxi Wu is an Assistant Professor in Cornell University's School of Operations Research and Information Engineering, specializing in societal networks and game-theoretic approaches to system design. Her research develops computational models for strategic learning and incentive mechanisms in socio-technical systems, with applications to transportation networks and digital platforms. Education: B.S. Applied Mathematics, Peking University (2015) M.S. Transportation, Massachusetts Institute of Technology (2017) Ph.D. Social and Engineering Systems, Massachusetts Institute of Technology (2021) Her research integrates game theory, optimization, and machine learning to address challenges in autonomous services, traffic management, and decentralized decision-making. Current investigations focus on adaptive incentive structures, spatial resource allocation, and equilibrium analysis in complex networked environments. Publication analysis reveals consistent emphasis on game-theoretic frameworks applied to urban mobility systems, with recent work exploring multi-agent reinforcement learning, congestion pricing equity, and electric fleet management. Methodological innovations include novel convergence proofs for decentralized algorithms and computational approaches to fairness constraints. Awards and Honors: Hammer Fellowship UTC Milton Pikarsky Memorial Award Siebel Scholarship EECS Rising Star recognition No information is currently available regarding student advising, research grants, or laboratory affiliations.

• Epidemiological Modeling
• Control Theory
• Network Science
• +3 more

Baike She is a Postdoctoral Fellow at the School of Electrical and Computer Engineering, Georgia Institute of Technology. Their research focuses on interdisciplinary topics at the intersection of control theory, network science, and epidemiological modeling. Key areas include epidemic spread analysis, distributed systems optimization, and privacy-preserving algorithms for networked models. Research interests emphasize mathematical frameworks for analyzing complex systems, including compositional control approaches (e.g., LQR analysis via category theory), robust epidemic control strategies, and leveraging differential privacy in sensitive data computations. Work spans both theoretical developments and applied methodologies for real-world systems such as SIR/SIS epidemic models and infrastructure networks. Recent publications (2022-2025) highlight contributions to distributed reproduction number computation, optimal epidemic mitigation under uncertainty, and the integration of opinion dynamics with vaccination strategies. Methodologies include Gaussian process regression, dissipativity theory, and model predictive control frameworks. No specific awards or grants are explicitly listed in the provided texts. Advising roles and laboratory affiliations remain unspecified based on available information.

Paul StevensonView profile

Assistant Professor

• Biophysics
• Quantum Engineering
• Quantum Sensing
• +3 more

Paul Stevenson is an Assistant Professor of Physics at Northeastern University's College of Science, leading the Stevenson Group. His research focuses on quantum sensing and biophysical dynamics using solid-state spins, particularly nitrogen vacancy centers in diamond. He develops nanoscale sensors for probing molecular motion and quantum communication technologies. Notably, his work bridges physics, chemistry, and biology, addressing challenges such as magnetism in complex systems and single-molecule imaging. He is a 2023 TIER1 Awardee and collaborates with institutions like Brown University and UC Berkeley. Stevenson's lab explores quantum materials and spintronics, leveraging interdisciplinary approaches to advance quantum hardware and biophysical understanding. His group's innovations include ultrasensitive magnetometers and tools for studying antiferromagnetic ordering. Contact: p.stevenson@northeastern.edu .