Tara Boroushaki is an incoming Assistant Professor in Electrical & Computer Engineering at Yale University. She completed her Ph.D. at MIT (expected May 2025), advised by Prof. Fadel Adib, with a focus on sensing and mobile technologies. Her research spans wireless networking, robotics, and human-computer interaction, emphasizing multi-modal sensing for environmental perception. Key achievements include the Microsoft Research PhD Fellowship (2022–2024) and the IEEE RFID '23 Best Paper Award. Her work on RF-based 'X-ray vision' has been featured in TEDxMIT and media outlets like the BBC and World Economic Forum. She co-founded Cartesian Systems, deploying sensing technologies in retail and supply chain. Research interests include non-line-of-sight perception, RFID localization, and robotic grasping. She has developed systems like FuseBot and RFusion, highlighted as transformative in MIT's '103 Ways to Make the World Better' initiative.
Luca Demetrio is an Assistant Professor at the University of Genoa, Italy, specializing in adversarial machine learning and cybersecurity. Previously, he was a Post-doctoral Researcher at the PRA Lab within the Department of Electrical and Electronic Engineering at the University of Cagliari. He holds bachelor's (2015), master's (2017), and Ph.D. (2021) degrees from the University of Genova, with his doctoral thesis focusing on formalizing evasion attacks against security detectors. His research emphasizes enhancing the robustness of machine learning models against adversarial attacks, particularly targeting malware detectors, SQL injection defenses, and Windows security systems. He leads the development of SecML Malware, a Python library for generating adversarial Windows malware, and contributes to the SecML framework. His work has been published in top-tier journals like ACM TOPS and IEEE TIFS. Key research interests include adversarial example generation, malware analysis, and cybersecurity defense mechanisms. He has explored query-efficient attacks on phishing detectors, certified adversarial robustness via randomized smoothing, and robust synthetic data-driven threat detection. His recent studies (2023–2025) address challenges in hardening machine learning models against evasion attacks, adversarial SQL injection countermeasures, and securing autonomous driving systems from adversarial reinforcement learning attacks.
Liu Lili is a Lecturer (Educator Track) in the Department of Computer Science at the School of Computing, National University of Singapore. She holds a Ph.D. from Nanyang Technological University and a Master's in Computer Science from Shanghai University. Prior to NUS, she served as a Senior Research Scientist at Singapore Polytechnic and a Scientist at A*STAR's Institute of High-Performance Computing. Her research focuses on Machine Learning, Computer Vision, and Multi-modal Learning, with applications in FinTech, Social Media Analysis, and Algorithms & Theory. Notable projects include AI-driven coating inspection systems for marine assets and behavioral competency assessment tools for navigational safety. She has contributed to robotics for construction quality assessment and interactive virtual environments for rehabilitation. Liu's publications span AI applications in finance, robotics, and material science, reflecting her expertise in bridging theoretical computer science with practical industrial solutions. Her work emphasizes automation, anomaly detection, and multi-modal data integration.
Suranga Chandima Nanayakkara is an Associate Professor in the Department of Computer Science at the National University of Singapore (NUS), leading the Centre for Holistic Inquiry into Lifelong Learning (CHILL) and the Smart Systems Institute (SSI). He holds roles such as AI+HCI Theme Lead at NUS+CNRS IPAL Lab and Residential Fellow at NUS College. His research focuses on assistive human-computer interfaces, emphasizing technologies that enhance perceptual and cognitive capabilities for individuals with sensory deficits. He earned his PhD and BEng from NUS, followed by postdoctoral work at MIT Media Lab. Notable projects include the Augmented Human Lab, iTILES for rehabilitation, and the FingerReader device for visually impaired shoppers. His work has garnered awards like the MIT TR35, TOYP, and INK Fellowship. Research interests include Intelligent Systems, Human Augmentation, and Design Science. He explores applications in assistive technologies, healthcare informatics, and educational tools. Over 15 publications highlight innovations in wearables, stress management, and multimodal interaction. Awards: 40+ accolades, including MIT TR35, TOYP, and multiple design awards for projects like Kiwrious and FingerReader. Grants: Led projects funded by institutions like NUS and Singapore’s innovation initiatives. Labs: Augmented Human Lab (founded 2011), focusing on humanizing technology through natural interfaces.
Dr. Ameer Abdelhadi is an Assistant Professor in the Department of Electrical and Computer Engineering at McMaster University. His research focuses on application-specific custom-tailored computer architectures, hardware-efficient deep learning, neurotechnology, and reconfigurable computing. He holds a PhD from the University of British Columbia and has held academic positions at the University of Toronto, Imperial College London, and Simon Fraser University, alongside industry experience in semiconductor design. Education: PhD in Computer Engineering (University of British Columbia, 2016). Research Interests: Hardware acceleration for machine learning and neurotechnology Reconfigurable computing and FPGAs/ASICs Asynchronous circuits and synchronization protocols VLSI physical design and CAD algorithms Publications span high-impact venues such as IEEE Journal of Solid-State Circuits, IEEE Hot Chips, and IEEE Micro. Notable achievements include the 2017 Best Paper Award at ASYNC for work on synchronization FIFOs. Teaching includes COMPENG 4DV4 (VLSI System Design) and ELECENG 4OI6B (Engineering Design). His lab focuses on advancing hardware systems for next-generation applications in AI and biomedical engineering.
Paolo Samorì is a full-time Professor at the Université de Strasbourg , where he serves as Director of the Nanochemistry Laboratory and Emeritus Director of the Institut de Science et d'Ingénierie Supramoléculaires (ISIS) . He is affiliated with multiple prestigious academies, including the German National Academy of Science and Engineering (ACATECH) , Royal Society of Chemistry (FRSC) , and European Academy of Sciences (EURASC) . Education: Laurea (MSc) in Industrial Chemistry (University of Bologna, 1995), PhD in Chemistry (Humboldt University Berlin, 2000, summa cum laude). His research focuses on Nanochemistry , 2D materials , and supramolecular systems at interfaces , with applications in organic electronics , optoelectronics , and sensing . He pioneered methods for scanning probe microscopies and photoresponsive nanodevices , including graphene-based systems and diarylethene molecular switches. His scientific awards include the ERC Advanced Grant (2019) , Blaise Pascal Medal (2018) , and Catalán-Sabatier Prize (2017) , among 20+ honors. He has trained over 130 students and researchers , including 34 professors now active globally.
Jakoah Brgoch is an Assistant Professor in the Department of Chemistry at the University of Houston. His research focuses on leveraging machine learning to design inorganic compounds for applications in LED-based lighting and superhard materials. Key areas include phosphor development, sparse data handling, and predicting material formation. He leads the Brgoch Group, which emphasizes interdisciplinary approaches combining computational modeling and experimental synthesis. Research interests span luminescent materials, crystal chemistry, and defect engineering, with a particular emphasis on optimizing phosphors for solid-state lighting and high-performance materials under extreme conditions. His work bridges data science and traditional materials discovery to accelerate innovation in optoelectronics and mechanical materials. Recent publications highlight advancements in cyan-emitting nitridation processes, machine learning-guided phosphor discovery, and understanding oxidation resistance in silicides. His team has developed novel phosphors like Na2CaZr2Ge3O12:Cr³⁺ for NIR bioimaging and explored luminescent properties of Sr-based solid solutions. Active in translational research, Dr. Brgoch collaborates on applications like smartphone-readable diagnostic platforms using nanophosphors and point-of-care testing. His lab emphasizes open science practices and has pioneered methods like Single-crystal automated refinement (SCAR) for structural determination.
Saurabh Bagchi is a Professor at Purdue University, West Lafayette, USA. He holds a PhD in Computer Science from the University of Illinois Urbana-Champaign (2001). His research focuses on distributed systems security, networking, and embedded systems. Key areas include IoT security, cyber-physical systems resilience, and machine learning applications in edge computing. Bagchi's work spans theoretical and applied domains, addressing challenges in distributed algorithms, fault tolerance, and secure communication protocols. His contributions to firmware analysis, serverless computing optimization, and anomaly detection in industrial IoT systems have been widely recognized. He has published over 300 papers in top-tier conferences and journals such as IEEE Transactions on Dependable and Secure Computing, ACM Transactions on Sensor Networks, and CVPR. He collaborates with researchers in academia and industry to advance resilient networked systems, including projects funded by NSF and industrial partnerships. His lab explores cutting-edge topics like federated learning security, edge computing architectures, and game-theoretic approaches to cyber defense.
David Blaauw is the Kensall D. Wise Collegiate Professor of Electrical Engineering and Computer Science (EECS) at the University of Michigan. His research focuses on ultra-low-power analog/mixed-signal circuits, mm-scale sensors, neural networks, and biomedical applications. He leads the Blaauw Lab, which has pioneered innovations like the Michigan Micro Mote (M^3) and neural recording probes. His work emphasizes real-world deployability, with applications in environmental monitoring (e.g., monarch butterflies), medical devices, and robotics. Education: B.S. in Physics and Computer Science, Duke University (1986) Ph.D. in Computer Science, University of Illinois Urbana-Champaign (1991) Research Interests: Blaauw’s lab explores ultra-low-power computing, mm-scale systems, RF communication, in-memory computing, and genomics acceleration. Key projects include: Millimeter-scale computers (e.g., 0.04mm³ temperature sensors) Wireless neural interfaces for brain-machine communication Energy-efficient accelerators for edge AI and genomics Micro-robotics with sensing/actuation/computation Awards: IEEE Fellow 2016 SIA-SRC Faculty Award Motorola Innovation Award Best Paper Awards at ISSCC, ISCA, and RFIC Advising & Impact: Over 600 publications, 65 patents, and 4 startup companies spun from his lab. Current research includes genome sequencing accelerators (GenAx) and neural recording dust for brain mapping. He directs the Michigan Integrated Circuits Lab and chairs major conferences like ISSCC and DAC. Labs/Teams: Blaauw Lab (University of Michigan) Michigan Integrated Circuits Lab (MICAL)
Prof. Dr. Tunç ÇATAL is a Professor of Molecular Biology and Genetics at Üsküdar Üniversitesi. He holds a PhD from İstanbul Technical University (2008) and conducted postdoctoral research at Oregon State University and the National University of Ireland Galway. His expertise spans microbial biotechnology, molecular biology, and hydrogen production. Education: BSc in Biology, İstanbul University (2001) MSc in Biology, İstanbul University (2004) PhD in Molecular Biology-Genetics and Biotechnology, İstanbul Technical University (2008) Administrative Roles: Head of Molecular Biology and Genetics Department (English Program) Director of PROMER Research Center Bologna Coordinator and Erasmus Coordinator His research focuses on microbial electrochemical systems, bioremediation, and bioenergy. Notable contributions include optimizing hydrogen production using microbial electrolysis cells and studying the effects of pharmaceuticals on microbial fuel cell efficiency. He has supervised 3 graduate theses and holds TÜBİTAK awards for impactful publications. His work integrates environmental science and molecular biology, with applications in sustainable energy (e.g., hydrogen production) and wastewater treatment. Recent studies explore novel curcumin compounds for toxicity mitigation and marine mucilage-based bioelectrochemical systems.
Dr. Jennifer Koch is an Associate Professor at the Laboratory of Geo-information Science and Remote Sensing, part of Wageningen University & Research. Previously, she served as an Associate Professor and Associate Research Director at the University of Oklahoma's Data Institute for Societal Challenges. Her research integrates data-driven methods like simulation modeling to address socio-economic and climate change challenges, focusing on sustainable urbanization and environmental management. Education: She holds a Diplom (Univ.) in Geoecology from the University of Bayreuth and a Dr.-Ing. in Electrical Engineering/Computer Science from the University of Kassel. She teaches courses on geo-information management and data analytics. Research emphasizes multi-scale modeling, stakeholder engagement, and participatory approaches to socio-ecological systems. Recent work explores urban growth in Africa, methane emission monitoring, and renewable energy siting. Articles highlight interdisciplinary methods in GIS, climate policy, and community geography. Professional service includes roles with iEMSs, IALE, and the AAG. No ancillary activities reported. Her work bridges technical geospatial tools with societal challenges, emphasizing practical policy applications.
Sverre Steen is a Professor and Head of the Department of Marine Technology at the Norwegian University of Science and Technology (NTNU). He leads the Kongsberg Maritime University Technology Centre focused on 'Ship Performance and Cyber-physical Systems' and is a member of the standing committee for the Symposium of Marine Propulsors. His research emphasizes ship propulsion, hydrodynamics, and big data analysis of in-service vessel performance. Key interests include seakeeping, high-speed marine vehicles, and model testing techniques. Steen teaches TMR 4217 Hydrodynamics of High-Speed Marine Vehicles , covering cavitation, experimental hydrodynamics, and propulsion systems. He collaborates internationally on projects like the Norwegian Ocean Technology Centre. His recent work explores wave-energy extraction via hydrofoil vessels, resistance modeling for fast ferries, and propulsion efficiency in real sea states. He has contributed to global shipping emission models (MariTEAM) and reliability analysis of structural components under vibration. Steen's publications span propulsion in waves, engine-propeller dynamics, and data-driven methods for ship performance monitoring. His applied research bridges experimental testing and computational modeling to address challenges in sustainable maritime transport and operational safety.
Özer Özkahraman is a postdoctoral researcher at the Division of Robotics, Perception and Learning (RPL) at KTH Royal Institute of Technology. He works under Ivan Stenius and John Folkesson, focusing on underwater mission planning, simulation, and integration of autonomous systems. His email is ozero@kth.se . He completed his PhD at KTH under Petter Ögren, researching large-scale multi-agent coverage planning for autonomous underwater vehicles (AUVs). Current projects include the SMaRCSim multi-domain simulation platform and development of underwater vehicles like LoLo, SAM, and Evolo. Research interests span autonomous underwater systems, multi-agent coordination, control systems, and simulation infrastructure. He emphasizes modular, accessible frameworks for vehicle testing and real-world deployment. His work bridges theoretical methods (e.g., control barrier functions) with practical applications in marine robotics. Publications focus on AUV navigation, environmental sensing, and adaptive control. Projects like Real2Sim aim to align simulation with real-world vehicle dynamics using motion capture data. He collaborates internationally on topics like data-driven damage detection and model compression for resource-constrained robots. No academic awards are explicitly mentioned. He actively seeks collaborators for projects in sonar simulation, flow field modeling, and cyber-physical system integration.
Meagan Wengrove is an Associate Professor in the Department of Civil and Construction Engineering at Oregon State University’s College of Engineering. She leads the Coastal Boundary Dynamics Research Group, focusing on coastal engineering with nature, boundary layer physics, and innovative ocean sensing technologies. Her work integrates field experiments, laboratory studies, and numerical modeling to address pressing coastal challenges related to climate change, sea level rise, and storm resilience. Her research interests include coastal dune morphodynamics, sediment transport in vegetated environments, ice-ocean boundary layer interactions, and the application of distributed fiber optic sensing (DAS) for real-time ocean monitoring. She investigates how natural systems such as coastal dunes, dynamic revetments, and submerged aquatic vegetation can be leveraged for sustainable coastal protection. Dr. Wengrove’s recent publications highlight interdisciplinary work on glacier melt physics and coastal dune behavior. Her research shows that pressurized air bubbles in glacier ice significantly enhance melting rates, with major implications for climate models. Another key finding reveals that newly planted vegetation can accelerate dune erosion during extreme storms, challenging conventional wisdom in coastal management. She mentors a diverse team of graduate and undergraduate researchers, including PhD students Nadia Cohen and Kaelan Weiss, and has advised former PhD student Liz Holzenthal. Her research is funded by the National Science Foundation, Keck Foundation, National Geographic Society, Office of Naval Research, U.S. Army Corps of Engineers, and Oregon Sea Grant. Dr. Wengrove teaches courses in coastal dynamics, coastal engineering with nature, programming and sensors, and fluid mechanics. She is actively involved in outreach and science communication, with features in Nature Geoscience , AGU EOS , National Geographic , and Oregon Public Broadcasting.
Youngwoo Seo is a Professor at The University of Toledo within the College of Engineering , specifically the Department of Chemical Engineering . His research focuses on molecular-scale bioadhesion, biofilm control in water systems, environmental sensor development, and sustainable water treatment technologies. Education: Ph.D. in Environmental Engineering, University of Cincinnati (2008) M.S. in Civil & Environmental Engineering, Sungkyunkwan University (2001) B.S. in Civil & Environmental Engineering, Sungkyunkwan University (1999) Research and Teaching Interests: span biofilm dynamics, nanoparticle interactions, disinfection by-product control, membrane biofouling, and sustainable bioremediation. He develops environmental sensors for microenvironmental monitoring and applies these tools in water systems and medical device contexts. Scientific Awards: WMAO Distinguished Service Award (2021) Undergraduate Research Mentor Award (2021) US Air Force Summer Faculty Fellowship (2016) Kohler International Travel Award (2015) Sigma Xi Young Investigator Research Award (2014) Faculty Research Excellence Award (2014) GCAT-SEEK Workshop Travel Award (2014) ASEE Faculty Early Career Award (2013) Undergraduate Research Recognition Award (2012) ASCE/EWB-USA Sustainable Development Award (2011) US EPA P3 Competition Honorable Mention (2011) Faculty Excellence Award (2010) His research group explores microbial interactions with engineered materials and environmental systems. Contact him at youngwoo.seo@utoledo.edu or via phone at (419) 530-8131.
