جستجوی استاد راهنمای دانشگاهی

Melih Sefa YAVUZمشاهده پروفایل

استادیار

• Finance
• Banking
• Digital Finance
• +۱۴ مورد دیگر

Melih Sefa YAVUZ is an Assistant Professor in the Department of Finance and Banking at Istanbul Beykent University, Faculty of Economics and Administrative Sciences. He has been actively contributing to academic and administrative duties, including serving as Deputy Director of the Institute and working in the Strategy Development and Planning Department. His teaching responsibilities include Investment Analysis and Portfolio Management, Digital Finance, and Financial Statement Analysis, all delivered in Turkish. His research interests span a wide range of topics in finance and economics, including digital finance, blockchain technology, ESG performance, firm performance, digital literacy, financial decision-making, and macroeconomic influences on equity markets. These interests are reflected in his extensive publication record in both national and international peer-reviewed journals. His recent scholarly work focuses on the impact of ESG performance on financial outcomes, behavioral aspects of financial decisions, digital transformation in finance, and the interplay between blockchain initiatives and stock prices. He frequently collaborates with scholars such as Gozde Bozkurt, Hasan Sadik Tatli, and Mehmetcan Suyadal, producing empirical studies grounded in Turkish and international financial markets. Dr. YAVUZ has published in journals such as the Journal of Entrepreneurship, Management and Innovation, EMAJ: Emerging Markets Journal, and Turkish Studies - Economics, Finance, Politics. His work appears in databases including ESCI, TR INDEX, EBSCO, and JournalPark. He has also contributed to scientific books on sustainable finance, digital transformation, and public procurement. Scientific Awards: No awards mentioned in the provided text. He advises and collaborates with various researchers and co-authors, though no formal PhD or Master’s students are listed. He does not appear to have led any externally funded grants explicitly mentioned in the text. He is involved in academic administration and curriculum development, particularly in digital finance and investment-related courses. There is no mention of specific labs or research centers, but his work suggests engagement with digital finance and financial market research teams.

Janick Edingerمشاهده پروفایل

استاد

• Distributed Operating Systems
• Edge Computing
• Computation Offloading
• +۷ مورد دیگر

Prof. Dr. Janick Edinger is a Professor of Distributed Operating Systems at the Department of Informatics, Faculty of Mathematics, Informatics and Natural Sciences, University of Hamburg, Germany. He leads a research group focused on distributed, context-aware, and adaptive computing systems, with a strong emphasis on edge computing, computation offloading, and assistive technologies. Education: PhD in Computer Science, University of Mannheim Studies at National Taiwan University Studies at University of Alberta, Canada Research stays at University of British Columbia, Hong Kong Polytechnic University, and Georgia State University, USA His research explores how edge computing and computation offloading can enable efficient, privacy-preserving processing of sensor and video data close to their sources, particularly in dynamic environments. He investigates the integration of autonomous and heterogeneous systems—such as drone fleets and mobile devices—into scalable middleware platforms for real-time monitoring and decision-making in logistics and industrial operations. His work also emphasizes societal impact, contributing to accessible routing, adaptive interfaces, and crowd-sourced mapping. The recent publications reflect a strong trend in edge computing, federated learning, privacy-preserving analytics, and assistive technologies. Topics include WebAssembly-based offloading, emotion prediction via eye tracking, real-time traffic detection, and predictive maintenance in Industry 4.0, showcasing a blend of foundational systems research and applied human-centered computing. Scientific Awards: PerCom 2021 Mark Weiser Best Paper Award Best Paper Award at IEEE PerCom 2021 for 'Voltaire: Precise Energy-Aware Code Offloading Decisions with Machine Learning' Prof. Edinger actively advises students and leads research projects involving grants and collaborations. His team includes PhD candidates and researchers working on middleware, edge systems, and context-aware applications. He has served on conference program committees, such as shadow PC member for EuroSys 2021, and publishes in top venues including IPDPS, PerCom, CHIIR, and COMPSAC. Labs and Teams: He leads the Distributed Operating Systems research group at the University of Hamburg, where he mentors students and collaborates on projects involving edge computing, IoT, and adaptive systems.

• Networking
• Communications
• Machine Learning
• +۷ مورد دیگر

Christopher G. Brinton is the Elmore Associate Professor of Electrical and Computer Engineering at Purdue University, where he leads the ION research lab. He is affiliated with the Department of Electrical and Computer Engineering in the College of Engineering at Purdue University's West Lafayette campus. Dr. Brinton received his PhD from Princeton University, where he was previously the Associate Director of the EDGE Lab and a Lecturer of Electrical Engineering. His research focuses on the intersection of networking, communications, and machine learning, with particular emphasis on Fog computing systems, the Internet of Things (IoT), NextG Wireless, and social learning networks. His research integrates foundational techniques including convex and non-convex optimization, machine learning, and signal processing to address challenges in networked intelligent systems. The ION lab under his leadership develops both theoretical frameworks and practical implementations for next-generation networking solutions, with strong industry collaborations including Qualcomm, Nokia, Intel, Cisco, Dell, and Ericsson. Recent publications reveal a strong trend toward federated learning, decentralized algorithms, and edge intelligence, with significant contributions to model partitioning, communication-efficient learning, and robust network architectures. His work increasingly bridges traditional communication theory with modern machine learning techniques to solve emerging challenges in distributed networked systems. NSF CAREER Award ONR Young Investigator Program (YIP) Award DARPA Young Faculty Award (YFA) AFOSR Young Investigator Program (YIP) Award Intel Rising Star Faculty Award (RSA) Dr. Brinton teaches several courses including ECE 647: Performance Modeling of Computer Communication Networks, ECE 301: Signals and Systems, and ECE 547: Introduction to Computer Communication Networks. He has co-authored the book 'The Power of Networks: Six Principles That Connect Our Lives' and taught three Massive Open Online Courses (MOOCs) with over 400,000 cumulative students. While not currently actively recruiting students, he remains open to connecting with highly motivated individuals. Dr. Brinton leads the ION (Intelligent Optimization and Networking) research lab, which focuses on creating theoretical foundations and practical implementations for next-generation networked systems. The lab has recently published significant work on 6G taxonomy in collaboration with major industry partners and continues to push boundaries in distributed learning and network optimization.

Elliot J. Crowleyمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Automated Machine Learning
• Neural Architecture Search
• +۳ مورد دیگر

Elliot J. Crowley is a Senior Lecturer (Associate Professor) at the School of Engineering, University of Edinburgh, where he co-leads the Bayesian and Neural Systems research group. He serves as Programme Manager for Electronics and Electrical Engineering and has developed a comprehensive machine learning course for 4th year electronic engineering students at the University of Edinburgh. Dr. Crowley's research focuses on simplifying machine learning systems with specific expertise in automated machine learning, low-resource deep learning, and engineering applications of machine learning. His work bridges theoretical advances with practical implementations, particularly in neural architecture search and computer vision applications, with emphasis on making complex ML systems more accessible and efficient. His recent publications demonstrate significant contributions to neural architecture search spaces, training-free instance segmentation, and state space models for visual recognition, appearing in top venues including NeurIPS 2024, BMVC 2024, and AutoML 2025. These works show a consistent focus on developing practical ML solutions that can operate effectively in resource-constrained environments. Selected awards and grants: EPSRC New Investigator Award Investigator on the dAIEdge Horizon Network Co-investigator on the EPSRC AI Hub for Causality in Healthcare AI Dr. Crowley currently supervises several researchers including Postdoc Linus Ericsson and PhD students Miguel Espinosa, Shiwen Qin (with Shay Cohen), and Cameron Barker (with Henry Gouk). His former students include Chenhongyi Yang (now a Research Scientist at Meta) and Jack Turner (now a Software Engineer at Qualcomm). He actively seeks new PhD students with strong research proposals and available funding for UK students through CDTs. His research group, the Bayesian and Neural Systems group, focuses on developing practical machine learning solutions that can be deployed in resource-constrained environments, with particular emphasis on making complex ML systems more accessible to engineers and practitioners.

Nezihe Merve Gürelمشاهده پروفایل

استادیار

• Machine Learning
• Computer Science
• Pattern Recognition
• +۴ مورد دیگر

Nezihe Merve Gürel is an Assistant Professor in Computer Science at Delft University of Technology (TU Delft), affiliated with the Pattern Recognition & Bioinformatics Group within the Intelligent Systems Department of the Faculty of Electrical Engineering, Mathematics and Computer Science. Her research focuses on developing robust, reliable, and efficient machine learning methods with enhanced reasoning capabilities, bridging theoretical rigor and practical applications. She emphasizes data-centric approaches to improve ML systems. Education: PhD in Computer Science from ETH Zurich, MSc from EPFL (Switzerland). Research Interests: ML robustness, reliability, reasoning, data-centric ML, federated learning, and explainable AI. Her recent work includes certified robustness for retrieval-augmented models and time-efficient learning algorithms. She has contributed to the Journal of Data-centric Machine Learning Research as an executive editor and served as a reviewer for top ML conferences (NeurIPS, ICML, ICLR). She previously held roles at IBM Research, Stanford University's Human-Centered AI Lab, and Westlake Institute for Advanced Study. Her awards include the Generation Google Scholarship and Cisco Research Funding . Scientific Awards : Generation Google Scholarship (2021) Cisco Research Center University Funding Labs & Teams : She leads research in the Pattern Recognition Laboratory at TU Delft and collaborates with international institutions like Stanford and Westlake Institute for Advanced Study.

Janis Nötzelمشاهده پروفایل

پژوهشگر

• Quantum Information Theory
• Machine Learning
• Sensor Networks
• +۳ مورد دیگر

Dr. Janis Nötzel is a senior researcher at the Chair of Theoretical Information Technology (Technische Universität München) and leads his independent Emmy Noether research group. Previously, he held a postdoctoral position at Universitat Autónoma de Barcelona and contributed to 5G practical implementations at TU Dresden's 5G Lab. His research spans quantum information theory, physical layer security, and machine learning applications. Key focuses include Quantum channel capacities under adversarial conditions Entanglement-assisted communication Quantum software frameworks (QuNetSim, QuReed) Interplay between classical and quantum communication Security analysis for 6G networks Resource optimization in quantum systems Recent publications (2023-2025) showcase innovations in Quantum satellite communication architectures Hybrid quantum-classical clustering algorithms Photonic processor instability modeling Covert capacity of compound channels Quantum key distribution resilience Free-space Bessel beam communication He actively collaborates with 6G-life research hub and contributes to quantum network simulation tools. Grants include funding from DFG (Leibniz Program), BMBF (6G-life, Q.Link.X), and StMWi (6G Zukunftslabor Bayern).

• Architectural Humanities
• Domestic Spaces and Technologies
• Urban Infrastructure
• +۷ مورد دیگر

Barbara Penner is Professor of Architectural Humanities at University College London's Bartlett School of Architecture, where she serves as Co-Director of the MA Architectural History program and supervises PhD students. Her academic appointments include Senior Lecturer positions at UCL since 2000 and previous roles at University of East London, Middlesex University, and Chelsea College of Art. Her educational background comprises a PhD from Birkbeck College (2003), MSc from University College London (1996), and BA from McGill University (1994). Penner's research focuses on the social and cultural dimensions of everyday spaces, examining how domestic environments, urban infrastructure, and commercial architecture shape social identities. Her interdisciplinary approach integrates architectural history with anthropology, literary theory, and cultural studies, particularly exploring gender dynamics in spaces like bathrooms, kitchens, hotels, and housing. Her publications reveal consistent engagement with themes of gender, domesticity, and infrastructure across historical periods. Key works include Bathroom (2013), Newlyweds on Tour (2009), and co-edited volumes on public toilets and gender. Recent scholarship examines social scientific research in home design, urine diversion systems, and historical housing models. RIBA President’s Award for Outstanding University-Located Research (2014) Leverhulme Major Fellowship (2021-2023) Provost Teaching Award, UCL (2013) Council of Editors of Learned Journals Best New Journal Award (2009) Penner actively supervises doctoral research on topics including Billy Butlin’s holiday camps and Gulf female shoppers' impact on London retail. She has completed twelve PhD supervisions and examined nearly thirty theses internationally. Her professional activities include serving on the Architectural Association Publications Committee, as North American Editor for Architectural History, and as External Examiner at University College Dublin. She participates in the 'Insurgent Domesticities' research group at Columbia University and contributes to Places Journal as a contributing editor.

Duncan Wilsonمشاهده پروفایل

استاد

• Internet of Things (IoT)
• Artificial Intelligence (AI)
• Smart Cities
• +۷ مورد دیگر

Duncan Wilson is a Professor of Connected Environments at the Bartlett Centre for Advanced Spatial Analysis (CASA) at University College London. His work bridges academia and industry, focusing on IoT, AI, and spatial analysis to enhance understanding of built and natural environments. Current role: Professor of Connected Environments at UCL Education: PhD in Artificial Intelligence and Machine Vision (UCL, 1997), BEng (Hons) in Electrical Engineering (Loughborough University, 1993) Research interests include: Cognitive computing at the network edge Extraordinary sensory systems for data capture Spatial reasoning and digital twins IoT for healthcare and biodiversity Edge AI and TinyML Recent articles span digital twin development , IoT for biodiversity monitoring , and smart healthcare infrastructure . He has received recognition for collaborative R&D approaches during his directorship at Intel's Sustainable Connected Cities institute. Teaching: Leads MSc Connected Environments and modules on IoT ethics, AI on microcontrollers, and sensor network deployment Projects: IoT Living Lab at UCL, Project Hercules for eye clinic analytics, and Shazam for Bats environmental monitoring Professional activities: Former Director of Intel Collaborative Research Institute (2012-2018), ex-member of Smart London Board (2017-2022)

Roel C.G.M. Loonenمشاهده پروفایل

دانشیار

• Building Performance Simulation
• Energy Engineering
• Adaptive Facades
• +۷ مورد دیگر

Roel C.G.M. Loonen is an Associate Professor at the Unit Building Physics and Services within the Department of the Built Environment at Eindhoven University of Technology (TU/e), Netherlands. He holds joint appointments with EAISI High Tech Systems and EIRES Research groups, focusing on building performance simulation and energy systems. His work bridges academic research with practical applications through collaborations with SMEs in the building industry. Loonen received his BSc and MSc (cum laude) in Building Services from Eindhoven University of Technology, followed by a PhD in 2018 with a dissertation on 'Approaches for computational performance optimization of innovative adaptive facade concepts.' His educational background has positioned him as a leading expert in building performance simulation and sustainable building technologies. His research interests center on developing and applying modeling and simulation strategies to support decision-making for designing buildings that combine high indoor quality with minimal environmental impact. Key areas include adaptive facades, building-integrated renewable energy systems, and energy-efficient building envelopes. He specializes in creating and validating new building performance simulation models to advance innovative building technologies. His recent publications demonstrate a strong focus on practical applications of building performance simulation, with emphasis on residential energy efficiency, photovoltaic systems, and occupant-centered approaches to building design. The work shows increasing integration of machine learning techniques with traditional building simulation methods, particularly for sensitivity analysis and optimization of building performance. REHVA Young Scientist Award (2021) Best PhD supervisor award from Department of the Built Environment, TU/e (2018) First prize - REHVA International student competition (2011) Smart daylight control for optimal building performance (NWO Take-off award, 2018) Best paper award (2021) Loonen actively supervises PhD and Master's students, evidenced by his Best PhD Supervisor Award in 2018. He manages multiple research projects including Sustainable Summer Comfort (2024-2027), Modeling Innovative Use Scenarios for Future Domestic Comfort (2023-2026), and Just Prepare (2022-2026), with funding from sources including the Dutch Research Council (NWO). His professional service includes being a board member of the Dutch-Flemish IBPSA affiliate and co-chair of IBPSA World's website committee, plus reviewing for 35 academic journals. He leads research within the Building Performance group, focusing on creating practical tools and methodologies that bridge the gap between theoretical building performance models and real-world implementation in the construction industry. His work particularly emphasizes the integration of occupant behavior and practices into building performance models, recognizing that human factors are critical to achieving sustainable building performance in practice.

Mahnoosh Alizadehمشاهده پروفایل

دانشیار

• Control Systems
• Cyber-physical Systems
• Smart Grids
• +۹ مورد دیگر

Mahnoosh Alizadeh is an Associate Professor in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara (UCSB), affiliated with the Institute for Energy Efficiency and the Center for Control, Dynamical Systems and Computation (CCDC). She directs the Smart Infrastructure Systems laboratory and focuses on scalable control frameworks, data analytics, and market mechanisms for sustainable cyber-physical systems in smart grids and electric transportation. PhD in Electrical and Computer Engineering from UC Davis (2014) Recipient of the National Science Foundation CAREER award (2019) Associate Editor for IEEE Transactions on Control of Network Systems and IEEE Open Journal of Control Systems Her research spans theoretical work in networks, optimization, and AI, with applications in smart grids , electric transportation , and resilient infrastructure . She has contributed to safe optimization algorithms, decentralized learning, and game-theoretic approaches in resource allocation. Recent publications highlight advancements in safe optimization (safe linear bandits, conservative linear bandits), decentralized learning (robust federated learning), game theory (General Lotto games, resource allocation), and smart charging (mobility-aware EV scheduling). These works emphasize real-time decision-making under constraints, security, and robustness in cyber-physical systems. NSF Early CAREER Award Northrop Grumman Excellence in Teaching Award Her research group includes PhD students Spencer Hutchinson, Arghavan Zibaei, Nanfei Jiang, and Sajjad Ghiasvand, with alumni placed at institutions like Apple, Toyota, and the University of Colorado.

Ryan P. Huangمشاهده پروفایل

دانشیار

• Computer Systems
• Operating Systems
• Distributed Systems
• +۷ مورد دیگر

Ryan P. Huang is an Associate Professor in the Computer Science & Engineering department at the University of Michigan, College of Engineering, where he leads the Order Lab. Previously, he was an Assistant Professor at Johns Hopkins CS department from 2017 to 2022. His research focuses on computer systems, particularly operating systems and distributed systems, with emphasis on reliability, efficiency, and defensibility across cloud data centers and mobile devices. Dr. Huang's research interests center on pushing the boundaries of cloud systems availability and observability. His work addresses critical challenges such as gray failures and partial failures in distributed systems, developing principled techniques for failure detection and localization. His research spans multiple thrusts including Panorama for enhanced observability, Watchdog for runtime checking, OmegaGen for partial failure localization, and Narya for predictive failure mitigation. He also investigates energy-efficient mobile systems and system misconfiguration prevention. His recent publications demonstrate a strong trend toward addressing silent failures in distributed systems, with multiple papers accepted to top-tier conferences including SOSP and OSDI in 2025. His work bridges theoretical principles with practical system implementations, focusing on real-world challenges in cloud infrastructure and distributed computing environments. NSF CAREER award recipient Multiple Best Paper Awards (OmegaGen, Argus, LeaseOS) CRA Outstanding Undergraduate Researcher Award honorable mentions for advisees Dennis Ritchie doctoral dissertation award honorable mention Dr. Huang actively mentors PhD students including Yuzhuo Jing, Wanning He, Yuxuan Jiang, and others. His lab has produced graduates who have gone on to faculty positions at institutions like University of Virginia and Boston University. He serves on program committees for major systems conferences including SOSP, OSDI, and NSDI, contributing significantly to the academic community. The Order Lab maintains active research collaborations and regularly publishes in top-tier venues, with multiple papers accepted to SOSP and OSDI in 2025.

Thomas Le Goffمشاهده پروفایل

استادیار

• Artificial Intelligence Regulation
• Environmental Law
• Digital Technology Law
• +۵ مورد دیگر

Thomas Le Goff is an Assistant Professor of Law & Technology at Télécom Paris – Institut Polytechnique de Paris, affiliated with the Interdisciplinary Institute of Innovation (i3) and the Digital, Organization and Society (DTOS) research team. His work bridges legal frameworks and technological advancements, focusing on AI regulation, environmental sustainability, data protection, and cybersecurity. Education: PhD in Private Law, Université Paris Cité Master’s in Law, Université Paris Cité LLM, University of Exeter (UK) Licence and Magistère, Université de Rennes 1 His research explores the intersection of AI and sustainability, emphasizing how legal principles can guide environmentally responsible technology. Key themes include the AI Act’s implications, data center energy demands, and regulatory strategies for balancing digital growth with net-zero targets. His work has been presented at international forums like BILETA and contributes to EU think tanks such as CERRE. Recent publications address AI’s environmental footprint, nuclear energy’s role in powering AI, and legal frameworks for sustainable digital infrastructure. Collaborations with institutions like the Center on Regulation in Europe (CERRE) highlight his focus on comparative analyses of global regulatory practices.

Chang Hyun Parkمشاهده پروفایل

استادیار

• Virtual Memory Systems
• Address Translation
• Cache Hierarchy
• +۷ مورد دیگر

Chang Hyun Park is an Assistant Professor at the Department of Information Technology, Uppsala University, where he is part of the Uppsala Architecture Research Team. His research focuses on computer architecture with emphasis on memory systems, virtualization, and system software optimization. Dr. Park completed his doctoral studies at KAIST (Korea Advanced Institute of Science and Technology) in South Korea, where he was advised by Professor Jaehyuk Huh. Prior to his current position, he served as a post-doctoral researcher at Uppsala University working with Professor David Black-Schaffer. Dr. Park's research spans several critical areas in computer architecture and systems: Virtual memory systems and address translation mechanisms Cache hierarchy optimization and memory systems design Support for non-volatile memory and heterogeneous memory systems Virtualization technology and optimizations for cloud environments High-speed I/O device integration and accelerator support His publication record demonstrates a consistent focus on improving memory system performance, particularly in virtualized environments. Over the past decade, his work has evolved from fundamental virtual memory optimizations to addressing challenges in emerging memory technologies and large-scale system architectures. Recent publications show increasing emphasis on heterogeneous memory systems, graph processing workloads, and hardware-software co-design approaches. Dr. Park actively collaborates with researchers at Uppsala University, particularly with Professor David Black-Schaffer, and maintains connections with his alma mater KAIST. His work appears regularly in top-tier computer architecture conferences including ISCA, MICRO, ASPLOS, and MEMSYS.

Thomas Walterمشاهده پروفایل

استاد

• Biomedical Image Analysis
• Machine Learning
• Computational Pathology
• +۴ مورد دیگر

Thomas Walter is a Professor at Mines ParisTech and Director of the Centre for Computational Biology (CBIO) , a research group affiliated with the Institut Curie and INSERM . His work focuses on applying Machine Learning and Computer Vision to biomedical image analysis, particularly in high-content screening and computational pathology . He also serves as Deputy Director of the Computational Oncology (U1331) unit and leads the Statistical Learning and Modeling of Biological Systems team. PhD in Medical Image Analysis (2003, Mines ParisTech) Postdoctoral work at EMBL (European Molecular Biology Laboratory) Director of CBIO since 2018 Holder of a PRAIRIE Chair (Paris Artificial Intelligence Research Institute) since 2019 Dr. Walter's research bridges biomedical imaging , machine learning , and cancer genomics . Key areas include: Statistical reconstruction of biological networks Prediction of tumor progression at genomic/transcriptomic levels Development of deep learning methods for cell cycle analysis Integration of multi-omics data for precision oncology Tools for spatial transcriptomics (e.g., autoFISH, RNA2seg) Recent publications highlight his work in spatial transcriptomics , immunotherapy outcome prediction , and deep learning for digital pathology . His team has developed open-source tools like FISH-quant and pyHiM for single-molecule RNA imaging analysis. Scientific Honors: PRAIRIE Chair (2019) for AI research in life sciences Dr. Walter actively contributes to teaching deep learning for image analysis in multiple graduate programs across France, including courses at Mines ParisTech , Université Paris-Saclay , and Institut Curie . His software tools (FISH-quant, pyHiM) and methodological frameworks (e.g., Cut-Detector, PointFISH) have become standard resources in bioimage informatics.

Guangyao Siمشاهده پروفایل

دانشیار

• Mining Engineering
• Mine Ventilation
• Rock Mechanics
• +۶ مورد دیگر

Dr. Guangyao Si serves as an Associate Professor at the School of Minerals and Energy Resources Engineering, University of New South Wales (UNSW). With extensive international experience studying and working across three continents, he has established himself as a prominent researcher in mining engineering disciplines. His educational background includes graduating as the top student from China University of Mining Technology in 2010, followed by a PhD at Imperial College London under Professor Sevket Durucan. After completing his thesis in 2015, he continued as a Research Associate at Imperial College London until December 2017, when he joined UNSW. Mining Engineering Mine Ventilation Rock Mechanics Mine Safety Coal Mine Methane Geomechanics and resources geotechnical engineering Applied geophysics Dr. Si's research program focuses on developing safer, smarter, and more sustainable mining technologies. His work spans coal seam gas capturing and utilization, goaf management, spontaneous combustion prevention, multiphysics coupled simulation, mining-induced seismicity management, and machine learning applications in mining. His research integrates reservoir engineering, geophysics, geostatistics, and geomechanics to address modern mining industry challenges. With over AUD 12 million secured in research funding as lead or co-investigator, his projects include significant ARC Linkage and ACARP grants addressing critical mining safety and efficiency issues. His work demonstrates strong industry relevance through collaborations with major mining companies including Anglo American, Glencore, BMA, South32, and Centennial. Research Excellence (Early Career) Award-Faculty of Engineering UNSW Excellent Scientific Editor (JRMGE, 2022) Best Reviewer (IJCS&T, 2022) High Impact Paper Award (Engineering Journal) MINESOC Best Lecturer (2018) Unearthed Young Innovator Award (2018) Dr. Si actively supervises numerous PhD students across mining health and safety, mining geomechanics, mining-induced seismicity, and mine ventilation research areas. He teaches core mining engineering courses including Mining Geomechanics (MINE3310), Mine Ventilation (MINE3510), Mining Systems (MINE3430), and Advanced Mine Ventilation (MINE4510). He serves on the Editorial Board of the Journal of Rock Mechanics and Geotechnical Engineering and is a member of the International Rock Mechanics Society, Australasian Institute of Mining and Metallurgy, and Society of Mining, Metallurgy and Exploration.