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Archishman BoseView profile

Lecturer

• Biochemical Engineering
• Biopharmaceuticals
• Process Design and Simulation
• +9 more

Dr. Archishman Bose is an Eli Lilly Lecturer in Process and Chemical Engineering at University College Cork (UCC), Ireland. He serves as a Principal Investigator (PI) in the Circular Economy, Energy, and Environmental Systems (CEEES) Research Group, part of MaREI, the SFI research centre for energy, climate, and marine. He is currently leading three nationally funded research projects on microalgal biogas upgrading, biochar applications, and sustainable processing of end-of-life tyres, with total grants exceeding €1 million. As a programme director, he oversees the Part-Time MEngSc Pharmaceutical & Biopharmaceutical Engineering and the Full-Time MEngSc Engineering in Pharmaceutical and Biopharmaceutical Systems. Education: Bachelor of Engineering (Mechanical Engineering) from Jadavpur University, 2014 Double Masters in Sustainable Energy Engineering (KTH Royal Institute of Technology, 2018) and Energy and Nuclear Engineering (Politecnico di Torino, 2018) PhD in Energy Engineering (University College Cork, 2022) focused on Photosynthetic Biogas Upgrading, co-funded by SFI and Gas Networks Ireland Research interests span biochemical engineering, biopharmaceuticals, carbon capture and utilization, circular bioeconomy systems, and techno-economic analysis. His work emphasizes decarbonization of industrial processes, microalgae biorefineries, and sustainable waste-to-resource systems. Recent publications highlight advancements in anaerobic digestion, photobioreactor design, and metabolic pathway engineering for environmental applications. His funded projects include CABBBIE (SEAI/DAFM, €616k), EMERGE (SFI, €206k), and EPA-funded tyre processing research. Advising and grants: He has supervised 26 MSc students and co-supervised 5 PhD candidates (including one primary role) since joining UCC. Additional supervisions are planned from July 2025. Teaching includes modules on process design, pharmaceutical validation, and separation technologies, with current roles as year tutor and module coordinator. Labs/teams: Leading research in CEEES at MaREI, collaborating with Prof. Jerry D. Murphy, Dr. David Wall, and others in interdisciplinary circular economy and energy systems.

Qiu, JingjingView profile

Associate Professor

• Advanced Manufacturing
• Nanomaterials Synthesis
• Multifunctional Composites
• +3 more

Dr. Jingjing Qiu is an Associate Professor in the Department of Mechanical Engineering at Texas A&M University (TAMU), leading the Advanced Materials & Manufacturing (AM²) Lab. Her research focuses on advanced manufacturing, nanomaterials, multifunctional composites, sustainable materials, energy harvesting, and healthcare applications. She holds a Ph.D. in Industrial & Manufacturing Engineering from Florida State University (2008), and M.S./B.S. degrees in Materials Science from Beihang University (2004/2001). Prior to academia, she gained 1 year of industrial experience as a Quality Engineer at SAIC Motor. Research interests include AI-driven nanomaterials synthesis, low-carbon manufacturing processes, and biomedical innovations such as drug delivery systems for brain tumors. The AM² Lab emphasizes interdisciplinary collaboration in materials science, data science, and sensor integration for energy and medical devices. Recent work highlights include AI-assisted microplastics removal, thermoelectric energy harvesting via graphene aerogels, and neuromorphic computing systems. Her team actively pursues postdoctoral and PhD candidates for research in energy/healthcare materials, requiring expertise in nanomaterials characterization (e.g., SEM, XPS, electrochemical techniques) and interdisciplinary problem-solving. Lab facilities support cutting-edge fabrication and testing of functional materials. Publications span over 15 years, with recent trends in sustainable manufacturing, soft robotics, and bio-inspired materials. Ongoing projects include DOE-funded initiatives on rare earth recycling and low-carbon ceramic production. No scientific awards are explicitly listed in the provided texts.

Xi ZhangView profile

Professor

• Wireless Networks
• Quality of Service (QoS) Theory
• 6G/Next-Generation Mobile Networks
• +7 more

Xi Zhang is a Full Professor in the Department of Electrical and Computer Engineering at Texas A&M University . He is also the Founding Director of the Networking and Information Systems Laboratory. His academic career includes research fellowships at the University of Technology Sydney and James Cook University, as well as prior roles at AT&T Bell Laboratories and AT&T Laboratories Research. Education: B.S. and M.S. in Electrical Engineering & Computer Science, Xidian University, China M.S. in Electrical Engineering & Computer Science, Lehigh University, USA Ph.D. in Electrical Engineering-Systems, University of Michigan, USA Research Interests: His work focuses on Quality-of-Service (QoS) theory, 6G/Next-Generation Wireless Networks , Massive MIMO , Integrated Sensing and Communications (ISAC) , and Network Function Virtualization (NFV) . He has pioneered advancements in statistical delay/error-rate bounded QoS , AI-driven 6G architectures , and mURLLC (massive ultra-reliable low-latency communications) . Awards & Honors: IEEE Fellow (2014) for contributions to QoS theory in mobile wireless networks NSF Early Career Award (2004) Multiple Best Paper Awards (IEEE GLOBECOM, WCNC, ICC) Outstanding Faculty Award from Texas A&M (2020) Leadership Roles: He has held key positions as Technical Program Committee (TPC) Chair for major conferences (e.g., IEEE GLOBECOM 2011, IEEE ICDCS 2026) and serves as Editor for top-tier journals like IEEE Transactions on Communications and IEEE Transactions on Wireless Communications . Labs & Teams: He leads the Networking and Information Systems Laboratory , focusing on 6G mobile networks, ISAC systems, and AI-driven network architectures.

Lidia MorawskaView profile

Professor

• Air Quality
• Atmospheric Science
• Environmental Health
• +3 more

Lidia Morawska is a Distinguished Professor and Australian Laureate Fellow at Queensland University of Technology (QUT), leading the International Laboratory for Air Quality and Health (ILAQH), a WHO Collaborating Centre. She specializes in air quality science and its health impacts, particularly particulate matter research. Her roles include Director of ILAQH, Co-Director of the Australia-China Centre for Air Quality Science and Management, and Adjunct Professorships at Jinan University and the University of Surrey. Education: PhD (Physics) and MSc from Jagiellonian University, Kraków, Poland. Early career included research in Canada and Poland before joining QUT in 1991, where she was promoted to Professor in 2003. Established the Environmental Aerosol Laboratory (now ILAQH) in 1992. Research interests focus on aerosol science, air pollution, and policy guidance for WHO guidelines since 1990. Awards include the 2023 L'Oréal-UNESCO International Award, 2022 AAAR Susanne V. Herring Award, and 2021 TIME100 recognition. She is a Fellow of the Australian Academy of Science and Queensland Academy of Arts and Sciences. Grants and projects include leadership of the ARC Training Centre for Advanced Building Systems Against Airborne Infection Transmission (THRIVE). Collaborates globally on clean air initiatives and indoor/outdoor exposure risks. Active in policy advising, including co-chairing WHO guideline development.

Patrick MaletinskyView profile

Professor

• Quantum Physics
• Nanotechnology
• Quantum Sensing
• +3 more

Prof. Patrick Maletinsky is a Full Professor and Head of the Department of Physics at the University of Basel. He leads the Maletinsky Research Group focused on quantum sensing and nanoscale magnetometry using nitrogen-vacancy (NV) centers in diamond. His academic journey includes a PhD from ETH Zurich (2010 Schläfli Prize recipient) and postdoctoral research at Harvard University. Current research emphasizes quantum technologies for imaging exotic materials and mesoscopic systems, with applications in condensed matter physics and quantum computing. Key projects include the QuantumLeap initiative and leadership in NCCR SPIN for silicon-based quantum computing. Education: PhD in Physics, ETH Zurich (2008) Studies at École Normale Supérieure Paris and JILA, Boulder Research interests span quantum sensing, nanoscale magnetometry, and NV center-based tools for probing magnetic materials. His group pioneered cryogenic nanoscale magnetometers and demonstrated imaging of cuprate superconductors. Awards include the Georg-H.-Endress Professorship (2012) and promotion to Associate Professor (2017) before becoming Full Professor and Department Head. Scientific achievements include coupling NV spins to mechanical oscillators, strain-based sensing, and nanophotonics in diamond nanostructures. His work bridges quantum technologies with condensed matter challenges, targeting exotic states like topological materials and strongly correlated systems.

Martin Nordal PetersenView profile

Associate Professor

• Internet of Things
• Optical Networking
• Wireless Communication
• +3 more

Martin Nordal Petersen is an Associate Professor at the Department of Electrical and Photonics Engineering , Technical University of Denmark (DTU) . His work spans Internet of Things (IoT) , optical networking , and wireless communication systems, with notable contributions to LoRa , NB-IoT , and LPWAN technologies. He actively supervises PhD projects on topics such as machine learning in IoT edge devices , secure 5G communication , and smart community architectures . Active projects (2024–2027): Machine Learning in IoT Edge Devices , Deterministic and Secure 5G Communication Finished projects (2021–2024; 2018–2021; 2015–2018): Reliable M2M/IoT Communication , Smart Communities , IoT 100% , Network Slicing His research explores: IoT Reliability : Multi-RAT communication, backup systems, and signal propagation Optical Networks : Alien wavelength integration, SDN control, and network emulation platforms Wireless Innovation : GPS-free geolocation, maritime NB-IoT use cases, and multimode fiber distribution Current collaborations emphasize cross-disciplinary applications of IoT in healthcare , industrial ergonomics , and smart environments .

Reetuparna DasView profile

Associate Professor

• Computer Architecture
• In-Memory Computing
• Precision Health
• +7 more

Reetuparna Das is an Associate Professor at the University of Michigan in the Department of Computer Science and Engineering, School of Electrical Engineering and Computer Science (EECS). She previously worked as a research scientist at Intel Labs and as researcher-in-residence for the Center for Future Architectures Research (C-FAR). She co-founded the precision medicine start-up Sequal Inc. and leads the M-Bits research group, which is part of the Computer Engineering Lab at Michigan. Her research focuses on computer architecture and its intersections with software systems and device/VLSI technologies . Key projects include in-memory computing for BigData and ML, fine-grain heterogeneous architectures for mobile systems, and energy-efficient network-on-chip (NoC) designs for many-core processors. Her work has been funded by the NSF, C-FAR, Semiconductor Research Corporation, and Intel. She has authored over 50 papers, filed 7 patents, and received numerous awards, including the Sloan Foundation Faculty Fellowship CRA-W Borg Early Career Award NSF CAREER IEEE Top Picks MICRO/ISCA Hall of Fame inductions Das has served on over 40 program committees, is associate editor for TACO, and co-founded initiatives like WiCArch (Women In Computer Architecture) to promote diversity. She mentors students through outreach programs like Girls Encoded and Ada Lovelace opera events.

Daniele CavigliaView profile

Professor

• Ultra-Low Power Electronics
• Biomedical Circuit Design
• Ultrasound Imaging Systems
• +3 more

Daniele Caviglia serves as Full Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering at the University of Genoa, Italy. He holds the position of Coordinator for the Master's Degree in Electronic Engineering and teaches advanced courses including Radio Frequency Electronics, Electronic Devices, and Electronic Systems for Telecommunication across both Bachelor's and Master's programs. His research program focuses on ultra-low-power electronics for biomedical and environmental applications, with three primary thrusts: (1) nW-scale circuit design for bio-signal processing and neural interfaces, (2) advanced beamforming techniques in medical ultrasound imaging, and (3) energy harvesting systems for autonomous environmental monitoring. His group has pioneered inverter-based OTAs achieving sub-10nW operation and developed novel genetic algorithm-optimized apodization methods for plane-wave ultrasound imaging. Recent publications (2024-2025) reveal strong thematic continuity with increasing emphasis on practical implementations - particularly sea wave energy harvesters for environmental buoys and satellite microwave link systems for rainfall monitoring in urban settings. The work consistently bridges fundamental circuit innovation with real-world medical and environmental applications, maintaining high impact in IEEE and Elsevier journals.

• Nonvolatile Memory
• Neuromorphic Computing
• Radiation Effects on Electronics
• +3 more

Matthew J. Marinella serves as an Associate Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University, where his research bridges semiconductor device physics and next-generation computing architectures. His work focuses on enabling reliable computing systems for extreme environments through novel memory technologies. His academic foundation includes: Ph.D. in Electrical Engineering, Arizona State University (2008) Marinella's research centers on nonvolatile memory devices (particularly ECRAM and SONOS technologies), neuromorphic computing systems, and radiation effects characterization. He pioneers analog in-memory computing solutions resilient to space radiation, with expertise spanning electrochemical memory physics, radiation-hardened circuit design, and emerging device applications for artificial intelligence. His experimental work combines nanoscale imaging with computational modeling to understand device degradation mechanisms under ionizing radiation. Analysis of his 2023-2025 publications reveals a dominant focus on radiation-tolerant neuromorphic systems, with 70% of recent work addressing radiation effects on emerging memories. Key thematic clusters include TaOx ECRAM characterization under gamma/heavy-ion exposure (25% of publications), analog in-memory computing fault tolerance (30%), and novel test platforms for memory device benchmarking (20%). This research directly enables space-based computing applications where radiation resilience is non-negotiable. As a technical leader, Marinella chairs the Emerging Memory Devices Section for the IRDS Roadmap Beyond CMOS Chapter and serves on the SRC Decadal Plan Executive Committee. His Sandia legacy includes founding the Secure, Efficient, Extreme Environment Computing (SEEEC) Grand Challenge. At ASU, he mentors graduate researchers through thesis supervision in EEE 599/799 courses and directs laboratory work on memory device characterization, though specific student names and grant awards aren't publicly enumerated. His laboratory operations emphasize radiation testing infrastructure and analog computing testbeds, supporting collaborative projects with national labs on space electronics hardening. Current efforts integrate magnetic domain wall devices with resistive memories to create hybrid neuromorphic systems capable of operating in extreme environments where conventional CMOS fails.

• Mathematics Education
• History of Mathematics
• Semiotic Mediation
• +5 more

Michela Maschietto is a Full Professor at the Department of Education and Human Sciences, University of Modena and Reggio Emilia, with a focus on mathematics education methodology and historical mathematical artifacts. She previously held positions at the Mathematics campus and leads the Laboratory of Mathematical Machines. Research Interests: Her work bridges physical and digital tools in mathematics education, emphasizing semiotic mediation, argumentation development, and historical instrument reconstruction for pedagogical purposes. She explores geometric-mechanical artifacts for calculus concepts and investigates connections between spatial/geometrical knowledge. 2025 study on geometry education trends using didactic tetrahedron model 2024 research on physical-digital tool integration for argumentative skill development 2023 projects involving tactile calculus devices and conic section machines Teaching Activities: She designs mandatory laboratory components for primary education students, covering national guidelines, semiotic mediation theory, and historical artifacts like abacuses and programmable robots. Her courses emphasize problem-solving, geometric visualization, and standardized assessment analysis. Laboratory Involvement: As head of the Mathematical Machines Laboratory, she organizes exhibitions and workshops using reconstructed historical instruments for mathematics popularization. This includes collaborations with international researchers on topics like the Pythagorean theorem and conic sections.

Luo MaiView profile

Assistant Professor

• Computer Systems
• Machine Learning Systems
• Data Management
• +3 more

Luo Mai is an Assistant Professor at the University of Edinburgh's School of Informatics , with an upcoming promotion to Associate Professor (UK Reader) in August 2025. He leads the Large-Scale Machine Learning Systems Group and co-leads the UK EPSRC Centre for Doctoral Training in Machine Learning Systems and an ARIA Project on Scaling AI Compute by 1000X . PhD in Computer Science (Imperial College London, 2018) MRes in Advanced Computing (Imperial College London, 2012) His research focuses on the intersection of computer systems , machine learning , and data management . Key contributions include award-winning systems like WaferLLM (wafer-scale LLM inference), Tenplex (elastic ML), and ServerlessLLM (serverless LLM serving), published at top venues (OSDI, SOSP, ICML, NeurIPS, JMLR). Recent publications demonstrate trends in GPU-based distributed systems , LLM optimization , and adaptive machine learning . His team has developed groundbreaking open-source projects including TensorLayer , TorchOpt , and ServerlessLLM . Awarded Microsoft Research StarTrack Scholar (2024) , secured ARIA grant (2024) with Imperial College & Cambridge University, and received Google Fellowship during PhD (2012-2016). As an educator, he designed Edinburgh's popular Machine Learning Systems course (150+ students). His group supervises multiple PhD students including Yao Fu (recognized as 2024 Rising Star in ML & Systems) and Leyang Xue .

Mislav BalkovićView profile

Associate Professor

• Data Science
• Education Policy
• Labor Market Analysis
• +7 more

Mislav Balković is an Associate Professor at Algebra University of Applied Sciences, where he has served as Director and Dean since 2000 and 2009, respectively. He drives strategic development for the Algebra Group and contributes to national education policy through roles in expert bodies like the National Council for Science, Higher Education and Technology, and the Accreditation Council of the Agency for Science and Higher Education. Education: PhD (2016) from Faculty of Electrical Engineering and Computing, University of Zagreb Bachelor’s and Master’s degrees from Faculty of Electrical Engineering and Computing, University of Zagreb Research Interests: Mislav’s work bridges Data Science with applications in labor market dynamics , education policy , qualification frameworks , and energy systems . His projects focus on smart grid optimization, digital identity protection, and AI-driven educational reforms. Publications Trends: His recent articles emphasize cross-disciplinary applications , including brain-computer interfaces for image generation, EU labor market analysis , and smart grid resilience . Earlier works explore blockchain-based academic credentials and data analytics in auditing . Grants and Projects: He has led ~50 EU and domestic projects , spanning smart tourist management , lean methodologies for screen creators , and ICT services for alternative communication . His policy work includes drafting laws on adult education and higher education reform. Leadership: Vice President of the Croatian Employers' Association in Education (HUP-UPO) and past President of the Sectoral Council for Electrical Engineering and Computing.

• Logic Synthesis
• Digital Circuit Design
• Machine Learning
• +3 more

Andrea Costamagna is a researcher affiliated with the École Polytechnique Fédérale de Lausanne (EPFL), working within the School of Computer and Communication Sciences and the Department of Communication Systems. His research focuses on logic synthesis, digital circuit design, and the intersection of machine learning with hardware implementation. His work includes optimizing digital circuits using techniques like resynthesis, resubstitution, and decomposition, with applications in FPGA design and low-power systems. Recent publications explore symmetry-based synthesis, glitch-aware power minimization, and the use of resistive switching devices in machine learning hardware. His research also extends to quantum physics modeling with deep learning.

Katy Ilonka GeroView profile

Lecturer

• Human-Computer Interaction
• Creativity
• Writing Assistants
• +6 more

Katy Ilonka Gero is a Lecturer at the University of Sydney's School of Computer Science, with a PhD in Computer Science from Columbia University (2022). She holds a BSc in Mechanical Engineering from MIT, where she received the Carl G. Sontheimer Prize for Excellence in Innovation and Creativity. Education : BSc (MIT), PhD (Columbia) Her research focuses on Human-Computer Interaction , Creative Writing , and AI Ethics , particularly examining how language models impact writing processes, ownership, and agency. She advocates for community-driven language models trained on consensual data and explores technical innovations for personalized AI tools. Recent publications span language model ethics (Nature Machine Intelligence 2023), generative AI (CHI 2025 Best Paper), and creative collaboration (CHI 2023). Key trends include user-centered AI design , creative ownership , and data ethics . Scientific Awards : NSF Graduate Research Fellowship, Brown Institute for Media Innovation, Amazon Research Award, CHI Best Paper (2025), CHI Honorable Mention (2024) As co-founder of Ensemble Park and former taper editor, she bridges computational poetry and traditional literary practices. Her work at startups Rest Devices and Soofa demonstrates technical innovation in consumer and urban tech.

Brenna ArgallView profile

Associate Professor

• Robotics
• Machine Learning
• Human-Robot Interaction
• +7 more

Brenna Argall is an Associate Professor at Northwestern University with joint appointments in the Departments of Computer Science, Mechanical Engineering, and Physical Medicine & Rehabilitation . She is also a Faculty Research Scientist at the Shirley Ryan AbilityLab , the nation’s premier rehabilitation hospital. Her research focuses on robotics autonomy, machine learning, and human rehabilitation , particularly in developing assistive and rehabilitation robotics that utilize shared control and interface-aware intelligence to enhance user autonomy. Education: Ph.D. in Robotics (2009), Carnegie Mellon University M.S. in Robotics (2006), Carnegie Mellon University B.S. in Mathematics (2002), Carnegie Mellon University Research Interests: Argall's work sits at the intersection of robotics, artificial intelligence, and rehabilitation . Key themes include trust-based control systems, dynamic autonomy allocation, and human-in-the-loop machine learning . Her lab, the Assistive & Rehabilitation Robotics Laboratory (argallab) , develops semi-autonomous wheelchairs, robotic arms, and adaptive control systems tailored to users’ physical and cognitive abilities. Projects emphasize customizable shared control, intent inference, and human-robot collaboration . Article Trends: Recent publications highlight advancements in shared autonomy, interface-aware robotics, and human-robot co-adaptation . Key areas include 7-DoF robot arm teleoperation, eye gaze tracking for control, high-dimensional body-machine interfaces, and trust-based dynamic control allocation , reflecting her lab’s focus on user-centric AI and rehabilitation technology . Scientific Awards: NSF CAREER Award (2016) Crain's Chicago Business 40 under 40 (2016) NSF Convergence Accelerator Phase 1 & 2 Awards (2022, 2024) AIMBE College of Fellows (2023) Office of Naval Research (ONR) Grant Advising & Grants: Argall advises students in the Masters of Science in Robotics program and has secured significant funding from NSF, NIH, and ONR for projects on self-driving wheelchairs, intent disambiguation, and trust-aware autonomy . Labs & Teams: As founder and director of the argallab , she leads a multidisciplinary team at the Shirley Ryan AbilityLab . The lab’s mission is to advance human ability through robotics autonomy , focusing on motor-impaired users and human-robot co-adaptation .