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Domitilla Del VecchioView profile

Professor

• Synthetic Biology
• Control Theory
• Systems Biology
• +9 more

Professor Domitilla Del Vecchio is the Grover M. Hermann Professor in Health Sciences and Technology at the Massachusetts Institute of Technology (MIT), affiliated with the Department of Mechanical Engineering and the Synthetic Biology Center. She conducts pioneering research at the intersection of engineering, mathematics, and biology, focusing on designing robust synthetic genetic circuits for cellular control and regenerative medicine. Ph.D. in Control and Dynamical Systems, California Institute of Technology (2005) Laurea in Electrical Engineering, University of Rome Tor Vergata (1999) Her work addresses the unpredictability of biological circuits by developing context-aware design frameworks and feedback control mechanisms to ensure modular and scalable synthetic biology applications. Current projects include bio-sensing in bacteria, chromatin state control, and analog memory engineering in mammalian cells. She has received numerous accolades, including: IEEE and IFAC Fellowships NSF CAREER and Understanding the Rules of Life Awards Bose Research Award Donald P. Eckman Award Del Vecchio teaches courses such as 2.004 (Dynamics and Control), 2.151 (Advanced Dynamical System Analysis), and 2.18/6.057 (Design of Synthetic Biological Systems). Her collaborations span multiple disciplines, including aerospace, electrical engineering, and industry partnerships.

Joshua MarshallView profile

Professor

• Field Robotics
• Autonomous Vehicles
• Control Systems Engineering
• +7 more

Joshua Marshall is a Professor of Electrical & Computer Engineering at Queen’s University, Canada, and Director of the Offroad Robotics research group. He holds a PhD from the University of Toronto and has cross-appointments in Mechanical & Materials Engineering and the Robert M. Buchan Department of Mining. His expertise spans field robotics, autonomous systems, control engineering, and harsh-environment applications in mining, space, and marine domains. He led the Ingenuity Labs Research Institute (2018–2024) and served as a Visiting Professor at Örebro University (2016–17). Dr. Marshall’s work focuses on autonomous vehicle navigation, robotic excavation, and spatiotemporal mapping. He has received the 2025 OPEA Engineering Medal and has commercialized technologies through partnerships with companies like Epiroc and RockMass Technologies. Education: PhD, Electrical & Computer Engineering, University of Toronto (2005) MSc(Eng), Mechanical Engineering, Queen’s University (2001) BSc (Hons), Engineering, (details not specified) Research Interests: Autonomous robotics in mining, space, and marine environments Data-driven control systems and model predictive control Proprioceptive sensing and terrain classification Multi-robot coordination and task planning Underground navigation and SLAM Professional Activities: Senior Member, IEEE Editorial roles: International Journal of Robotics Research , IEEE Transactions on Mechatronics Co-founded the NSERC Canadian Robotics Network (NCRN) Contributions to the IEEE Medal for Environmental & Safety Technologies Committee Labs/Teams: Offroad Robotics Group (Queen’s University) Ingenuity Labs Research Institute (founding Director) Advisor to Queen’s AutoDrive Challenge II Team and aQuatonomous ASV Design Club

Luis C. HerreraView profile

Assistant Professor

• Power Electronics Control
• DC Microgrids
• Power System Optimization
• +5 more

Luis C. Herrera is an Assistant Professor in the Department of Electrical Engineering at the School of Engineering and Applied Sciences, University at Buffalo. Previously, he served as Assistant Professor at Rochester Institute of Technology (2016-2018) and as Research Engineer at University of Dayton Research Institute (2015-2016). PhD in Electrical Engineering (2015) from The Ohio State University BS in Engineering (2010) from University of Tennessee at Martin His research focuses on power electronics control , DC microgrids , fault detection via parameter estimation , and optimal energy utilization . Key projects include improving DC microgrid resiliency , time-scale separation control , and voltage balancer design for aerospace applications . Recent publications emphasize data-driven fault detection , unknown input observers , and quickest change detection in DC systems. He has received: NSF CAREER Award (2023) for DC microgrid control Two AFRL Summer Faculty Fellowships (2019, 2020) Current advisees include PhD students Richard Tarbell , Sarbajit Basu , and Patrick Johnson . Past advisees include Kaushik Gajula (now at Sonnen Inc.) and Lalit Marepalli (L&T Technologies).

Hina TabassumView profile

Associate Professor

• 5G/B5G wireless communications
• Massive MIMO
• Mm-wave communication
• +9 more

Hina Tabassum is an Associate Professor at the Lassonde School of Engineering , York University, Canada, specializing in 5G/6G wireless communications and sensing applications. She was awarded the York Research Chair in 2023 for her work in 5G/6G-enabled mobility and sensing. Areas of Expertise: THz communications, WiFi sensing, and multi-band wireless systems Editorial Roles: Area Editor for IEEE OJCOMS and Associate Editor for multiple IEEE journals Research Focus : Ultra-reliable low-latency communication Reconfigurable intelligent surfaces (STAR-RIS) Machine-type communications Energy-efficient network design Scientific Recognition : Stanford's Top 2% World Researchers (2021-2024) Lassonde Innovation Early-Career Researcher Award (2023) N2Women Rising Stars (2022) Multiple IEEE Exemplary Editor/Reviewer Awards

Ahmed S. IbrahimView profile

Associate Professor

• Wireless communications
• Drone-assisted aerial communications
• Vehicular communications
• +3 more

Dr. Ahmed S. Ibrahim is an Associate Professor in the Department of Electrical & Computer Engineering at Florida International University (FIU), leading the Wireless Innovation Lab (WIL). He holds a Ph.D. from the University of Maryland and M.S./B.S. degrees from Cairo University. His research focuses on wireless communications, vehicular networks, millimeter wave systems, and geometric machine learning applications in network optimization. Education: Ph.D., Electrical Engineering, University of Maryland, College Park (2009) M.S., Electronics and Electrical Communications, Cairo University (2004) B.S., Electronics and Electrical Communications, Cairo University (2002) Research Interests: Dr. Ibrahim specializes in advanced wireless communication systems, including drone-assisted aerial networks, vehicular communications, and millimeter wave technologies. His work integrates Riemannian geometry and machine learning to address challenges in network optimization, security, and resource allocation. Recent projects include applying geometric frameworks to link scheduling, beamforming, and interference management. Key Contributions: His NSF CAREER-funded research ( CNS-2144297 ) explores Riemannian-geometric tools for low-latency wireless networks. Notable outputs include frameworks for RIS-assisted ISAC systems, massive MIMO resource allocation, and satellite network scheduling. Awards: NSF CAREER Award (2022-2027) Rising Star Award, Florida Academy of Science (2022) Advising & Grants: He mentors Ph.D. students in geometric machine learning and wireless systems. Current projects include Riemannian-geometry-based scheduling and NSF-funded studies on mmWave vehicular communications. His lab collaborates with industry and academic institutions on 5G/6G network solutions. Labs & Teams: Director of the Wireless Innovation Lab (WIL), focusing on 6G research, network testbeds, and interdisciplinary projects combining signal processing, AI, and communications.

Fei LiuView profile

Assistant Professor

• Robotics
• Surgical Robotics
• Medical Robotics
• +3 more

Fei Liu is an Assistant Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. His research focuses on surgical robotics, medical robotics, and control systems. He holds a PhD in Robotics from the University of Lyon (INSA de Lyon), France, an MSc in Control Systems and Automation Engineering from INSA de Lyon, and a BSc in Control Systems and Automation Engineering from Northwestern Polytechnical University, China. Fei's research interests include autonomous robotic systems, deformable object manipulation, and perception frameworks for surgical applications. His work emphasizes bridging real-world and simulation environments through advanced modeling and control techniques. Recent projects involve optimizing robotic actions using multi-modal demonstrations, improving tool-tissue interaction tracking, and developing frameworks for boundary parameter estimation in surgical settings. His articles highlight contributions to surgical robotics, including real-to-sim matching of deformable tissues, autonomous suturing, and trajectory optimization for wound care. He has also explored applications in haptic training systems and medical telerobotics. Fei's work often combines machine learning, physics-based simulation, and real-time control to address challenges in robotic surgery. Fei is affiliated with the Tickle College of Engineering and maintains an active research profile with collaborations in robotics and medical engineering domains. His lab focuses on advancing robotic autonomy in healthcare environments through interdisciplinary approaches.

• Hardware Security
• Machine Learning
• 3D IC Design
• +4 more

Wafi Danesh is an Assistant Professor in the Department of Engineering Programs at SUNY New Paltz, part of the School of Science & Engineering. He holds a PhD in Electrical and Computer Engineering from the University of Missouri Kansas City (2022). Prior to academia, he served as a Senior Engineer I - Design at Microchip Technology Inc. (2022-2023). His research focuses on hardware security, leveraging machine learning for FPGA Trojan detection and secure 3D IC design. Teaching interests include System-on-Chip Design, Digital Logic Fundamentals, and Computer Architecture. Education: PhD in Electrical and Computer Engineering, University of Missouri Kansas City, 2022 Research Interests: Dr. Danesh explores cutting-edge methods to enhance hardware security, including AI-driven approaches for IoT device protection and thermal management in 3D integrated circuits. His work bridges machine learning and physical hardware vulnerabilities, emphasizing FPGA security and PUF-based solutions for wireless systems. Publications Trends: His articles span FPGA Trojan detection via NLP and unsupervised learning, thermal challenges in 3D ICs, and neuromorphic computing innovations. Recent work highlights automated security tools and multi-valued computing for energy efficiency. Awards: None explicitly listed in the provided materials. Advising & Grants: No formal advisees or grants are mentioned. His professional activities center on research and teaching.

Miguel F. AnjosView profile

Professor

• Mathematical Optimization
• Smart Grids
• Operations Research
• +3 more

Miguel F. Anjos is Professor and Chair of Operational Research at the School of Mathematics, University of Edinburgh , and holds the NSERC-Hydro-Québec-Schneider Electric Industrial Research Chair on Optimization for Smart Grids at Polytechnique Montréal. He received his B.Sc. (1992), M.S. (1994), and Ph.D. (2001) from McGill, Stanford, and Waterloo respectively. Research Theme Head of Data and Decisions at Edinburgh Founding Director of Trottier Institute for Energy Editor-in-Chief of Optimization and Engineering Research Interests: His work bridges mathematical optimization with smart grid applications , focusing on conic optimization, optimal power flow, demand response, and facility layout. He applies these techniques to energy storage, electric transportation, and industrial systems. Scientific Awards: Méritas Teaching Award (2012) Humboldt Research Fellowship (2009) Queen Elizabeth II Diamond Jubilee Medal (2013) Elected Fellow of EUROPT and Canadian Academy of Engineering Academic Service: Served on Mathematical Optimization Society Council, SIAM Activity Group on Optimization, INFORMS Optimization Society Vice-Chair, and Mitacs Research Review Committee. Hosts benchmark datasets: QAPLIB, FLPLIB, Jones Benchmark.

Sindy K.Y. TangView profile

Associate Professor

• Microfluidics
• Biomedical Engineering
• Precision Medicine
• +5 more

Dr. Sindy K.Y. Tang is an Associate Professor in the Department of Mechanical Engineering at Stanford University, with courtesy appointments in Bioengineering and Radiology. She leads the Micro-Nano-Bio Lab, focusing on developing micro/nano-scale devices for precision medicine and environmental sustainability. Her work bridges engineering, biology, and medicine through microfluidic platforms for single-cell analysis, cancer organoid models, and allergy diagnostics. Educational Background: PhD in Engineering Sciences (Harvard University, advised by Prof. George Whitesides) MS in Electrical Engineering (Stanford University) BS in Electrical Engineering (Caltech) Research Focus: Dr. Tang's lab explores innovative tools for understanding cellular wound repair, cancer immunotherapy modeling, and precision diagnostics. Key projects include: Microfluidic 'guillotine' for controlled cell dissection Basophil activation tests for food allergy diagnosis Automated micro-dissection systems for tumor organoids Awards & Recognition: NSF CAREER Award (2020) Kenneth & Barbara Oshman Faculty Scholar Invited Lecture at Nobel Symposium on Microfluidics (2019) Lab & Collaborations: The lab collaborates with institutions like UCSF, PNNL, and the Sean N. Parker Center for Allergy Research. Ongoing efforts include synthetic neuron construction (NSF-funded) and spatial proteomics for cancer biology. Recent publications span wound repair mechanisms, fomite transmission studies, and organoid-based cancer models.

Iñaki EsnaolaView profile

Senior Lecturer

• Information Theory
• Machine Learning
• Cybersecurity
• +6 more

Dr. Iñaki Esnaola is a Senior Lecturer at the Department of Automatic Control and Systems Engineering, University of Sheffield, and a Visiting Research Collaborator at Princeton University. He holds a MSc from the University of Navarra (2006) and a PhD from the University of Delaware (2011). His research focuses on information theory, machine learning, and cybersecurity, particularly in cyberphysical systems like smart grids. His work addresses data integrity, privacy, robust estimation, and optimal sensor placement. Research interests include: Information theory and data science, machine learning and high-dimensional statistics, cybersecurity (especially data injection attacks), privacy, robust estimation, and sensor placement optimization. Recent projects involve empirical risk minimization with regularization, stealth attacks on control systems, and compressive sensing for environmental monitoring. Key publications include studies on relative entropy in machine learning, sensor placement for sewer networks, and stealth attacks in smart grids. He leads a research group with ongoing projects in resilient cyberphysical systems and received a UKRI grant for advanced manufacturing. His work bridges theoretical foundations with real-world applications in energy systems and environmental monitoring.

Taylor JohnsonView profile

Associate Professor

• Formal Verification
• Cyber-Physical Systems (CPS)
• Artificial Intelligence
• +7 more

Taylor Johnson is an Associate Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. He directs the Verification and Validation for Intelligent and Trustworthy Autonomy Laboratory (VeriVITAL) and serves as a Senior Research Scientist in the Institute for Software Integrated Systems. Previously, he was an Assistant Professor at the University of Texas at Arlington from 2013 to 2016. His research focuses on formal verification techniques for cyber-physical systems (CPS), emphasizing safety, reliability, and security through hybrid systems, formal methods, and control theory. He has published extensively on neural network verification, earning best paper awards and recognition from IEEE, IFIP, and ACM. Education: Ph.D., Electrical and Computer Engineering (University of Illinois at Urbana-Champaign, 2013) M.Sc., Electrical and Computer Engineering (University of Illinois at Urbana-Champaign, 2010) B.S.E.E., Electrical and Computer Engineering (Rice University, 2008) Research Interests: Formal verification of neural networks and CPS, safety-critical systems, autonomous systems, and AI/ML security. His work bridges theoretical foundations (e.g., hybrid systems) with practical applications in aerospace, energy systems, and robotics. Key Contributions: Developed the NNV tool for neural network verification, led the Verification of Neural Networks Competition (VNN-COMP), and pioneered techniques for robust federated learning and malware detection. Awards: AFOSR YIP Award (2016), NSF CRII Award (2015), and multiple best paper honors. His research is funded by AFRL, NSF, Intel, NVIDIA, and industry partners. Labs & Collaborations: VeriVITAL Lab (Vanderbilt), collaborations with United Technologies Research Center, Boeing, and Toyota.

Mark F. BockoView profile

Professor

• Superconducting Digital Electronics
• Quantum Computing
• Digital Signal Processing
• +4 more

Mark F. Bocko is a Professor of Electrical and Computer Engineering and Physics at the University of Rochester, serving as Chair of the Department of Computer and Electrical Engineering since 2004. He holds a BA from Colgate University and advanced degrees (MS/PhD) in Physics from the University of Rochester. His research spans superconducting digital electronics, quantum computing, music signal processing, and smart sensor systems. Notable awards include the Excellence in Undergraduate Teaching Award (1991, 2002) and Professor of the Year (2002). His research groups focus on high-frequency digital signal processing using Josephson junctions, quantum coherence in superconducting circuits, and applications in music technology such as internet-based real-time musical collaboration. Collaborations include work with the Eastman School of Music and local industries on sensor networks and wireless technologies. Key contributions include developing GHz-rate analog-to-digital converters, quantum bit control systems, and music encoding algorithms. His NSF-funded projects explore internet2 applications for musical interaction and physical modeling in music systems.

Zhongbei TianView profile

Assistant Professor

• Transport Energy System Decarbonisation
• Transport Energy System Modelling and Analysis
• Railway Traction Power Supply Systems
• +3 more

Dr Zhongbei Tian is an Assistant Professor in Transport Energy Systems at the University of Birmingham's School of Engineering, within the Department of Electronic, Electrical and Systems Engineering. His research focuses on decarbonising transport energy systems, including railway, road, and ship energy systems, with emphasis on energy-efficient train control and sustainable integration of energy systems. He has led projects funded by EPSRC, Royal Society, Horizon 2020, Network Rail, RSSB, and Innovate UK. His work has been implemented globally, including in the UK (Network Rail, Edinburgh Tram), Spain (Madrid Metro), Singapore (SMRT), and China (Beijing and Guangzhou Metro). Awards: 2016 ERESS Award for Best Energy Efficiency Project for Railways. His research spans energy system optimisation and sustainable integration, with over 60 high-impact publications. He collaborates internationally, addressing challenges in decarbonisation across diverse transport sectors. Advising and grants include leadership on major funded initiatives, reflecting his role in advancing transport energy innovation. He leads research groups focused on decarbonisation strategies and energy-efficient systems.

Hans Jonas Fossum MoenView profile

Associate Professor

• Autonomous Systems
• Sensor Technologies
• Robotics
• +3 more

Hans Jonas Fossum Moen is an Associate Professor with a 20% appointment at the Department of Technology Systems, University of Oslo (UiO), and holds a 100% position as a researcher at the Norwegian Defence Research Establishment (FFI). His primary affiliation is with the Section for Autonomous Systems and Sensor Technologies. He is based at the Kjeller campus, with a visiting address at Gunnar Randers Road 19 and a postal address at Postboks 70. His research focuses on advancing autonomous systems and sensor technologies, particularly in the domains of swarm robotics, multi-agent coordination, and optimization algorithms. Key areas include UAV navigation, distributed localization in IoT networks, radar detection enhancement, and adaptive control systems for multi-functional swarms. He emphasizes the integration of biological principles into robotic systems, as evidenced by his participation in the ICRA 2018 Workshop on Swarms. His publications consistently highlight contributions to swarm intelligence, with a focus on improving data quality and efficiency in robotics applications. He has collaborated extensively with colleagues such as Kyrre Glette, Oleg Yakimenko, and Jan Dyre Bjerknes, exploring topics ranging from task allocation in multi-agent systems to evolutionary algorithms for filter optimization. His work bridges theoretical computer science with practical engineering challenges in autonomous systems. No scientific awards have been explicitly mentioned in the provided texts. Moen’s advising and grants narrative indicates no listed advisees or active grant projects, though his 20% UiO position suggests potential involvement in academic supervision. His primary research activities are embedded within FFI and the Autonomous Systems section at UiO, contributing to interdisciplinary efforts in sensor technologies and robotic systems.

H. Jonathan ChaoView profile

Professor

• Networking
• Data Center Networks
• High-Speed Packet Processing
• +3 more

H. Jonathan Chao is a Professor in the Department of Electrical and Computer Engineering at New York University (NYU Tandon School of Engineering). He is the Director of the High-Speed Networking Lab, leading a team of 6 PhD students and 10 Master’s students. His research focuses on software-defined networking, network function virtualization, datacenter networks, and high-speed packet processing. Chao has held significant roles, including Head of the ECE Department (2004–2014) and former CTO of Coree Networks. He has authored over 200 publications and holds 58 patents. His awards include IEEE Fellow and National Academy of Inventors (NAI) Fellow. Education: B.S. and M.S. from National Chiao Tung University (Taiwan), Ph.D. from Ohio State University. Research Highlights Developing solutions for data center networks, network security, and quality of service control. Pioneering work in programmable packet schedulers, reinforcement learning for traffic engineering, and SDN security frameworks like SDNShield. Contributions to hybrid SDN networks, bufferless switch architectures, and energy-efficient data center designs. Awards Fellow of National Academy of Inventors (NAI) Fellow of IEEE Telcordia Excellence Award (1987) IEEE Best Paper Award (2001) IEEE New Jersey Coast Section Speaker of the Year (2003) Advisees & Labs Supervises 6 PhD and 10 Master’s students in the High-Speed Networking Lab. Collaborates with the Center for Advanced Technology in Telecommunications (CATT) to advance telecom innovations. Labs & Teams Directs the High-Speed Networking Lab, focusing on cutting-edge networking solutions, and contributes to CATT’s mission of technology transfer and entrepreneurship.