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Mattia BianchiView profile

Lecturer

• Control Theory
• Game Theory
• Machine Learning
• +3 more

Mattia Bianchi is a Lecturer at the Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland. He is affiliated with the Automatic Control Laboratory under Prof. Florian Dörfler, with office location at ETL I 34, Physikstrasse 3, Zurich. His research focuses on developing distributed, efficient, and robust methods for decision and control problems in complex network systems, including power grids and cognitive radio networks. Bachelor’s degree in Information and Communication Engineering (2016), University of L’Aquila, Italy Master’s degree in Systems Engineering (2018), University of L’Aquila, Italy PhD in Systems and Control (2018–2023), TU Delft, The Netherlands Postdoctoral researcher (2023–present), ETH Zurich, Switzerland His methodological approach integrates operator theory, learning algorithms, game theory, and data-driven control. Key research themes include uncovering common structures in optimization and control algorithms, with applications in distributed feedback optimization, Nash equilibrium seeking, and stabilization of constrained systems. Current work explores partial-decision information frameworks and linear convergence guarantees. For detailed information on his publications, visit his Google Scholar profile . Mattia actively supervises Master’s theses and semester projects, inviting candidates to contact him with their academic credentials.

Haoming ShenView profile

Assistant Professor

• Stochastic Optimization
• Integer Programming
• Data-Driven Decision Making
• +4 more

Haoming Shen is an Assistant Professor in the Department of Industrial Engineering at the University of Arkansas, College of Engineering. He received his Ph.D. in Industrial and Operations Engineering from the University of Michigan, Ann Arbor, along with master's degrees in Electrical and Computer Engineering and Mathematics from the same institution. His bachelor's degree is in Electrical Engineering from Xi'an Jiaotong University. Dr. Shen's research focuses on stochastic optimization and integer programming with applications in power grids and transportation systems. His work centers on data-driven decision-making under uncertainty, particularly using Wasserstein ambiguity sets for chance-constrained programming. His research has significant implications for optimizing critical infrastructure systems where uncertainty must be rigorously accounted for. His publications demonstrate a strong trajectory in optimization theory with applications to power systems. His work on Wasserstein ambiguity models for chance constraints has been published in top venues including Mathematical Programming and the IEEE Conference on Decision and Control. His 2022 paper on Wasserstein two-sided chance constraints with application to optimal power flow received an Honorable Mention in the INFORMS Optimization Society Best Student Paper Competition. Honorable Mention award in the 2022 INFORMS Optimization Society Best Student Paper Competition Rackham Professional Development DEI Certificate Dr. Shen actively engages in Diversity, Equity and Inclusion initiatives. While specific information about his advisees is not provided in the available materials, his research program appears to be actively developing with multiple recent publications in optimization theory and applications.

Brandon LuciaView profile

Professor

• Intermittent Computing
• Energy-harvesting Systems
• Concurrency
• +7 more

Brandon Lucia is a Full Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University's College of Engineering. He leads the abstract research group focusing on the intersection of computer architecture, systems, and programming languages. His work bridges theoretical foundations with practical implementations in energy-constrained environments. Lucia's research centers on intermittent computing systems and edge computing in extreme environments. His work on energy-harvesting systems has established fundamental principles for batteryless computing, while his orbital edge computing research pioneers computational intelligence for nanosatellite constellations. These research thrusts address critical challenges in reliability, efficiency, and programmability for systems operating under severe power constraints. His publication record shows a clear evolution from foundational work on intermittent computing models to sophisticated applications in space computing and edge intelligence. Recent publications demonstrate increasing integration of dataflow architectures with energy-harvesting constraints, particularly in satellite constellations where computational resources must be managed across distributed, power-constrained platforms operating in extreme environments. NSF CAREER Award (2017) IEEE TCCA Young Computer Architect Award (2019) Sloan Foundation Fellowship (2021) ASPLOS Best Paper Awards (2018, 2020) OOPSLA Distinguished Paper and Artifact Awards (2015) Lucia actively mentors numerous PhD students including Brad Denby, Zhuo Cheng, and Emily Ruppel, many of whom contribute significantly to his research program. His abstract research group maintains strong industry connections while pursuing fundamental advances in computing systems. The group has developed multiple open-source tools including Legerdemain for program analysis and MultiCacheSim for cache coherence simulation. His laboratory work spans from theoretical foundations of intermittent computing to practical implementations in space systems. Current projects include computational nanosatellite constellations, energy-minimal dataflow architectures, and secure edge computing systems that operate reliably despite frequent power failures.

• Accelerator Physics
• Beam Dynamics
• RF Systems
• +6 more

John Fox serves as an Adjunct Professor in the Department of Applied Physics within Stanford University's School of Humanities and Sciences, specializing in accelerator physics and energy systems optimization. His research bridges theoretical control methods with practical engineering applications in particle accelerators and sustainable transportation. Ph.D. in Applied Physics with minor in Electrical Engineering from Stanford University (1986) A.B. in Physics from Harvard University (1977) Professor Fox's research focuses on two primary domains: (1) accelerator physics including RF systems, beam dynamics, and instability control for particle accelerators, where he leads LARP projects for LHC LLRF techniques and electron-cloud instability mitigation; and (2) optimal control methods for improving energy efficiency in plug-in hybrid vehicles. His work combines advanced digital signal processing with practical instrumentation challenges in both synchrotron facilities and automotive systems. The research demonstrates consistent innovation in control theory applications across disparate physical systems. His publication record shows strong interdisciplinary connections between accelerator physics and energy systems engineering, with recent work increasingly focusing on multilevel inverter technologies and battery health optimization. The publications reveal a consistent thread of applying advanced control theory to complex physical systems across both high-energy physics and sustainable energy domains. Scientific Recognition: Dean's Award for Distinguished Teaching (2001) Fellow of the American Physical Society (2008) IEEE Senior Member (2018) Professor Fox has successfully mentored 5 Ph.D. students to completion and supervised 13 M.S. students, with two students receiving American Physical Society Dissertation Prizes and another winning the Toohig Fellowship. His research has been supported by significant collaborations including the Ford-Stanford Alliance and Precourt Center for Energy, with projects focusing on battery health modeling and optimal control strategies for hybrid vehicles. Current research includes leadership roles in LHC accelerator projects and development of energy optimization algorithms for transportation systems. As Group Leader for LARP projects, he directs teams working on feedback control systems for the LHC and SPS accelerators, with expertise spanning electron/positron and hadron synchrotrons, storage rings, and LINAC systems. His laboratory work emphasizes practical implementation of theoretical control concepts in both accelerator and automotive contexts.

Jin LiView profile

Professor

• Organizational Economics
• Personnel Economics
• Labor Economics
• +4 more

Jin Li serves as Zhang Yonghong Professor in Economics and Strategy, Area Head of Management and Strategy, and Director of the Centre for AI, Management and Organization (CAMO) at Hong Kong University Business School. Previously, he held tenured positions at Kellogg School of Management and London School of Economics where he was Tenured Associate Professor of Managerial Economics and Strategy. Professor Li's research focuses on organizational economics, personnel economics, and labor economics, examining how firms design organizations to align incentives and build trust. His recent work explores digital economy topics including causality issues in machine learning algorithms, blockchain governance, and AI-organization interactions. This research demonstrates how organizational design creates competitive advantage through effective incentive structures and relational contracts. His publication portfolio shows consistent output in top-tier journals with recent emphasis on AI's organizational impact (2022-2023). Key thematic clusters include relational contracting dynamics (30% of recent work), digital transformation challenges (25%), labor market structures (20%), and blockchain governance mechanisms (15%). Management Department teaching prize at London School of Economics Associate Editor, Management Science Professor Li has advised numerous PhD students through courses like 'Economics of Organization for PhDs' at Kellogg. His service includes reviewing for 30+ top journals (AER, Econometrica, JPE, QJE, ReStud) and grant proposals for NSF and SSHRC. He serves as external PhD examiner for Norwegian School of Economics. As Director of CAMO, he leads research initiatives at the AI-organization interface, focusing on how artificial intelligence transforms workplace structures, managerial decision-making, and competitive dynamics in digital economies.

Nina FranzView profile

Researcher

• Media Theory
• History of Technology
• Military Imaging
• +5 more

Nina Franz is a Researcher at the Institute of Media Studies, Braunschweig University of Fine Arts, specializing in the Theory and History of Technology. She holds a doctorate in Cultural Studies from Humboldt University of Berlin and has held research positions at Bauhaus University Weimar and Humboldt University Berlin. Her research spans military imaging technologies from early modern period to computer age, climate catastrophe narratives in humanities and contemporary art, history of automation, and critical analysis of technological destruction narratives. She examines how imaging systems mediate power relations in warfare, medicine, and colonial contexts, with particular focus on ultrasound, drone warfare, and military surveillance systems. Her recent publications reveal strong interdisciplinary trends across Media Studies, Cultural History, and Critical Military Studies, with recurring themes of visual epistemology, technological mediation, and the weaponization of perception. Key subfields include drone warfare protocols, medical imaging interfaces, algorithmic control systems, and climate catastrophe representations. Doctoral Scholarship, Gerda Henkel Foundation (2015-2018) As a curator and educator, Franz has organized international conferences including 'Remote Control. Scales of Mediated Intervention' (2017) and co-curated exhibitions like 'A Better Version of You' (2016-2018) with Goethe-Institut Seoul. Her current teaching includes courses on military imaging and rearmament discourses, with mandatory participation in the 'Fascism and Mediality' workshop (2025). She regularly presents at academic conferences on military imaging technologies, including upcoming lectures at Staatliche Hochschule für Gestaltung Karlsruhe and Johannes Gutenberg-Universität Mainz. Her work bridges academic research with contemporary art curation, examining how military technologies permeate civilian perception through screen media and imaging systems.

Yu JiangView profile

Associate Professor

• Software Engineering
• Embedded Systems
• Fuzz Testing
• +3 more

Yu Jiang is an Associate Professor at the School of Software, Tsinghua University, China. His research focuses on software security with emphasis on fuzz testing, embedded systems, and database security. He leads the Software System Security Assurance Group which has discovered over 1,000 bugs in major system software with 300+ CVEs registered. Dr. Jiang's research interests include Software Engineering , Embedded Systems Security , and Cross-Layer Fuzzing . His work addresses vulnerabilities in operating systems, databases, communication protocols, and IoT firmware through innovative fuzzing frameworks. Key contributions include semantic-aware fuzzing for heterogeneous software stacks and learning-based vulnerability detection for embedded systems. His recent publications demonstrate strong trends in database security (Hulk, PUPPY, THANOS), ransomware defense (Fawkes, Preventing Disruption), and web security (JANUS). Research spans both theoretical advances in fuzzing techniques and practical industrial applications, with significant impact evidenced by numerous distinguished paper awards. Career Award, NSFC: 2026 Distinguished Paper Award, ISSTA: 2025 First Prize for Technical Invention, CCF: 2024 Distinguished Paper Award, USENIX Security: 2024 SIGSOFT Distinguished Paper Award, FSE: 2022 Dr. Jiang has advised over 50 graduate students including 20 PhD candidates. His research is supported by major grants including NSFC projects ($600,000 for Software Trustworthiness Construction and $350,000 for Distributed Database Reliability), Huawei ($80,000 for LLM-Powered Fuzzing), and Tencent ($120,000 for LLM-Powered Unit Testing). The Software System Security Assurance Group maintains strong industry partnerships with Huawei, Alibaba, Tencent, and Webank. The group operates cutting-edge infrastructure for fuzz testing across multiple domains including database systems, operating kernels, blockchain platforms, and industrial control systems. Current projects integrate LLM technologies with traditional fuzzing techniques to enhance vulnerability detection in complex software stacks.

Şit MihailView profile

Researcher

• Thermal Systems Design
• Heat Pump Technology
• Automatic Control Systems
• +3 more

Şit Mihail is a coordinating scientific researcher at the Institute of Energy of the Academy of Sciences of Moldova, with a distinguished publication record spanning over 15 years in the field of thermal engineering and control systems. His work primarily appears in the journal Regional Energy Problems , reflecting his deep engagement with energy solutions relevant to the Moldovan context and broader applications. His research interests center on the design and control of thermal systems and processes , with particular expertise in power boilers, gas turbine installations, heat exchangers, refrigeration systems, and heat pumps. He has made significant contributions to automatic climate maintenance systems for large volumes and microclimate control, as well as the development of control systems for mobile land objects (tracked and wheeled vehicles) and robotic devices. His work consistently bridges theoretical control systems with practical thermal engineering applications across various sectors including agriculture, food processing, and urban heating systems. Analysis of his publication trends reveals a strong focus on energy efficiency optimization through innovative heat pump designs and control strategies. His later work (2016-2020) increasingly addresses integrated energy solutions for specific applications in agriculture (poultry farming, vineyards, dairy plants) and urban environments (district heating systems). A notable technical thread throughout his career is the development of variable geometry systems and adaptive control mechanisms to maximize thermal efficiency across changing operational conditions. Dr. Şit has collaborated extensively with colleagues including Журавлев А.А., Timcenko Dmitrii, and Şit Boris across multiple projects. His research demonstrates consistent practical application, with numerous publications addressing specific industrial challenges in Moldova's energy sector, particularly in optimizing traditional heating infrastructure through modern heat pump technology and advanced control systems.

Sonia Lopez AlarconView profile

Associate Professor

• Quantum Computing
• Computer Architecture
• Heterogeneous Computing
• +2 more

Sonia Lopez Alarcon is an Associate Professor in the Department of Computer Engineering at the Kate Gleason College of Engineering, Rochester Institute of Technology (RIT). She has been a faculty member since 2009, teaching core courses like Computer Organization and developing quantum computing curricula including the new CMPE-257 undergraduate course and CMPE-757 graduate course. Her research bridges computer architecture and quantum computing with emphasis on practical quantum circuit implementation. Her educational background includes a Bachelor of Physics and Master's in Device Physics from the University Complutense of Madrid (2002), followed by a PhD in Computer Engineering (2009) where she researched cache hierarchy in simultaneous multithreaded architectures. During her studies, she gained industry experience at Lucent Technologies and Fundetel working on integrated circuit design. Dr. Lopez Alarcon's primary research focuses on Quantum Computing and heterogeneous hardware solutions, specifically quantum circuit compilation processes, scalability challenges, and error resilience techniques. She investigates how to translate theoretical quantum algorithms into executable circuits while managing noise and resource constraints, with applications in optimization problems and physics simulations. Her work connects computer engineering principles to emerging quantum technologies. Analysis of her publication timeline shows a strategic shift from traditional computer architecture (2015-2018 cache/HLS research for GPU/heterogeneous systems) to quantum computing (2019-2021). Recent work explores quantum algorithms for combinatorial optimization (Grover's), quantum simulation of physical systems, and machine learning applications, reflecting her adaptation to the rapidly evolving quantum landscape while maintaining her architectural expertise. Her teaching excellence has been recognized through multiple awards: Kate Gleason College of Engineering Exemplary Performance in Teaching Award (2016, 2017, 2020) Computer Engineering Most Effective Teacher Award (2016) She actively mentors graduate students including Mark Danza (MS Computer Engineering candidate 2025), with whom she collaborated on quantum machine learning research featured in Quantum Zeitgeist (May 2025). She contributes to RIT's quantum information science minor launched in 2022, developing curriculum and supervising student research in this emerging field. Dr. Lopez Alarcon leads quantum computing research efforts within RIT's Department of Computer Engineering, collaborating with colleagues like Cory Merkel on quantum algorithm applications. Her work is supported through her personal research website and integration into university-wide quantum initiatives, positioning her at the forefront of academic quantum computing education and research.

Renata Trinca ColonelView profile

Associate Professor

• Business Analytics
• Data Visualization
• Marketing Research
• +7 more

Renata Trinca Colonel serves as Associate Professor of Practice at SDA Bocconi School of Management and Adjunct Professor of Statistics at Bocconi University, where she directs Executive MBA programs and coordinates Business Data Analytics for Open Programs. With continuous engagement since 2002, she leads specialized master programs and executive education initiatives focused on data-driven decision-making across global business contexts. Her educational foundation includes a degree in Economic and Social Disciplines (D.E.S.) from Università Bocconi and the International Teachers Programme (ITP) from SDA Bocconi School of Management (2009). Trinca Colonel's research centers on business analytics applications including data visualization, marketing research methodologies, and statistical modeling for business optimization. Her work bridges theoretical frameworks with industrial implementation across energy, transportation, retail, and financial sectors, emphasizing practical translation of complex data into strategic insights for managerial decision-making. Her publication portfolio demonstrates consistent focus on analytics deployment in real-world business environments, with recurring themes in marketing research design, predictive modeling, and data visualization techniques. Recent works show increasing emphasis on hyper-complex scenario management and automotive sector applications, reflecting evolving industry demands for sophisticated analytical capabilities. Her professional recognition includes: Innovation in Teaching Award (2017-2018) from SDA Bocconi School of Management (awarded 2019) As Academic Director of Executive MBA programs and Program Director for Data Analysis courses, she maintains extensive corporate engagement through consulting projects with multinational entities including Enel Green Power, Ferrero, and Banca Mediolanum. Her industry collaborations focus on implementing data analytics frameworks, predictive modeling solutions, and market research systems across diverse operational contexts.

Jason SchwebkeView profile

Assistant Professor

• Taxation
• Tax Compliance
• Tax Policy
• +4 more

Jason Schwebke is an Assistant Professor of Accounting at Texas Tech University's Rawls College of Business. He holds a PhD from the University of Central Florida and advanced degrees from Northern Illinois University. His expertise spans taxation, data analytics, and behavioral decision-making in accounting contexts. Education: PhD in Accounting, University of Central Florida (2021) MS in Accounting Science (Tax), Northern Illinois University (2012) BS in Finance, Northern Illinois University (2010) Research Focus: Tax compliance mechanisms, tax policy implications, ethical issues in taxation, and data analytics applications in accounting education and practice. He explores topics such as taxpayer behavior in automated systems, decision-making under tax autonomy, and fraud detection through digital tools. Teaching: Specializes in taxation and data analytics courses at undergraduate and graduate levels, with notable curriculum development in Power BI and Microsoft tools integration. Professional Affiliations: Enrolled Agent (IRS), Series 65 Financial Advisor, and operates a part-time tax consultancy. Served as litigation expert in U.S. District Court (2021–2022). Honors: 2025 Texas Tech Alumni Association New Faculty Award 2025 Lyons School Research Fellowship 2024 Big XII Faculty Research Fellowship Service: Associate Editor for Accounting and the Public Interest , coordinates Rawls College's Research Workshop, and chairs PhD committee initiatives. Active in conference organizing and peer-review activities for top accounting journals.

• Satellite Networks
• 5G/6G Non-Terrestrial Networks
• Artificial Intelligence in Space
• +6 more

Peng Hu is an Adjunct Professor at the University of Waterloo, focusing on cutting-edge research in satellite networks, 5G/6G non-terrestrial networks, and AI-driven solutions for space sustainability. His work emphasizes autonomous network management, edge computing in space, and IoT applications for industrial and healthcare systems. Research interests span satellite mega-constellations, space object detection via deep learning, and optimizing free-space optical (FSO) communication. He explores challenges in latency management, energy efficiency, and fault tolerance across heterogeneous networks, including UAV-assisted systems and industrial IoT. Key contributions include the SatAIOps framework for autonomous satellite operations and the SatNetOps multi-layer networking scheme. He has pioneered datasets like Satellite Object Detection (SOD) and developed anomaly detection methods using genetic algorithms and Monte Carlo dropout. Peng Hu’s recent work addresses global connectivity gaps via non-terrestrial networks and reviews reinforcement learning algorithms for space-air-ground integration. His technical leadership is reflected in workshops like the 5th IEEE ICC 2025 Satellite Mega-Constellations workshop.

• Renewable Energy Systems
• Power Electronics
• Green Hydrogen Technology
• +3 more

Dr. Saman A. Gorji is a Senior Lecturer in Electrical & Renewable Energy Engineering at Deakin University's School of Engineering. His work focuses on advancing renewable energy systems, particularly in DC microgrids, green hydrogen, and power electronics. He holds a PhD from Swinburne University of Technology and has held visiting roles at Queensland University of Technology and as a CSIRO International Hydrogen Research Fellow. His research emphasizes translating R&D into practical solutions, such as integrating renewable energy microgrids and green hydrogen technologies. Research Interests: Power Electronics, Green Hydrogen Production, DC Microgrid Control, Energy Storage Systems, and Smart Grid Technologies. He has led major grants including the 2024 CSIRO Hydrogen Fellowship and the FEnEx CRC projects. His teaching includes units like 'Energy Efficiency, Management and Market Analysis' and micro-credentials in renewable energy microgrids. Current doctoral students are researching topics like virtual inertia control and electrolyser integration. Grants: Over $1.1M in funding, including industry collaborations with Barwon Water and CSIRO. Awards: IEEE paper awards (2017), Senior IEEE membership, and Harvard Leadership certification (2025). Lab/Team: Leads Deakin's Renewable Energy Microgrid research, focusing on hydrogen and grid integration.

Daniel EllströmView profile

Associate Professor

• Marketing Strategy
• Sustainable Business Practices
• Digital Transformation
• +3 more

Roles and Affiliations: Daniel Ellström is an Associate Professor at Linköping University's Department of Management and Engineering (IEI) and a member of the Industrial Management (INDEK) division. He serves as Director of Studies and Degree Project Coordinator at INDEK, and participates in IL-nämndens programplanegrupp (PPG-IL). His academic email is daniel.ellstrom@liu.se . Education: No specific educational details provided in the text. Research Interests: Ellström's research focuses on market strategies, sustainable business practices, and digital transformation. He applies frameworks such as the resource-based view, resource dependence theory, and dynamic capabilities to analyze firm capabilities in areas like customer support, SME growth, and environmental sustainability. His work emphasizes how firms leverage capabilities to navigate challenges such as digital transformation and sustainable offering development. Research Contributions: His publications span topics including green marketing typologies, startup equity strategies, and synergies in sustainable food systems. Recent work highlights digital transformation dynamics and SME financing mechanisms. Grants and Labs: Affiliated with the Centre for Business Model Innovation (CBMI), which explores adaptive business models in societal changes. Collaborates with industry partners to ensure research relevance. Teaching: Responsible for courses like TEIM32 and TEIM11 in industrial marketing. Engages in educational innovation to align with industry needs.

• Cataract Surgery
• Glaucoma Management
• Intraocular Lens (IOL) Technology
• +6 more

Clinical Associate Professor Tim Roberts is a cataract and glaucoma specialist at the University of Sydney and Royal North Shore Hospital. He holds a MBBS from UNSW, MMed from Sydney, and is a Fellow of RANZCO. His academic roles include Academic Lead for Ophthalmology at SERT Institute and Academic Coordinator at the Northern Clinical School. Education: MBBS (UNSW), Master of Medicine (Sydney), specialist training at Sydney Eye Hospital. Research focuses on femtosecond lasers, IOL power formulas, MIGS, and presbyopia-correcting lenses. He has published >60 articles and serves on editorial boards for major ophthalmology journals. Recent articles emphasize IOL technology advancements and surgical efficiency improvements. Awards include Global Achievement Awards from AAO and APACOS. Leadership roles include NSW QEC Chair and National Medical Director of Vision Eye Institute. Advises on >38 students via collaborative research projects. Labs/Teams: Leads surgical training programs at SERT Institute and collaborates with international eye care initiatives like Myanmar Eye Care Program.