Geert Deconinck is a full professor at KU Leuven , leading the Electrical Energy Systems and Applications (ELECTA) research group within the Department of Electrical Engineering (ESAT). He also serves as scientific leader of the EnergyVille research center's algorithms domain, focusing on smart electrical networks and thermal systems. M.Sc. and Ph.D. from KU Leuven Head of ELECTA since 2012 (10 professors, 8 postdocs, 70+ PhDs) Over 8 million EUR research budget in last 5 years 44 completed PhDs and 10 current advisees IEEE Transactions editorial board member His research spans smart grid architectures , distributed control , and cyber-physical security , with recent focus on EV-grid integration , renewable energy democratization , and multi-carrier energy systems . Current projects include: Smart Charging - E-Mobility meets Renewable Energy Early Detection and Defense Systems for Smart Grids Open-source P2P energy sharing platforms Microgrid control strategies for PV-battery systems Awarded IET Fellow and IEEE Senior Member status, his work combines machine learning with power systems engineering through both theoretical modeling and experimental validation . He has contributed over 575 publications with 9800+ Google Scholar citations.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۱۶-۳۰ از ۱٬۳۵۹ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Professor Ben Goldys is a distinguished academic at The University of Sydney's School of Mathematics and Statistics, where he conducts research at the intersection of pure mathematics and applied sciences. His work spans multiple disciplines including stochastic analysis, partial differential equations, and financial mathematics, with significant contributions to both theoretical frameworks and practical applications in science and finance. Goldys' research interests center on stochastic (ordinary and partial) differential equations and their applications. His specific focus areas include stochastic partial differential equations, stochastic geometric PDEs, stochastic boundary value problems, stochastic fluid dynamics, ergodic theory of infinite-dimensional diffusions, and applications in financial mathematics such as interest rate derivatives, credit risk, and stochastic volatility. His work bridges pure mathematical theory (Functional Analysis, PDEs, Ergodic Theory) with complex real-world problems across multiple domains. His research aligns with the University of Sydney Faculty of Science Research Strengths including Understanding the Universe, Fundamental Laws of Nature, Complex Systems, and Next Generation Materials. Professor Goldys has secured multiple significant research grants from the Australian Research Council, including recent projects such as 'Mathematics for future magnetic devices' (2024), 'Mathematics for breaking limits of speed and density in magnetic memories' (2019), and 'Novel Approaches for Problems with Uncertainties' (2015). His current research projects focus on geometric stochastic partial differential equations and applications in micromagnetism, mean field games in finance, stochastic boundary value problems, and stochastic Navier-Stokes equations on the rotating sphere. He maintains extensive international collaborations with institutions in Germany (University of Tuebingen), Italy (LUISS University), Poland (Institute of Mathematics Polish Academy of Sciences), and the United Kingdom (University of York), working on projects involving optimal control, stochastic systems with memory, and geometric stochastic PDEs. Goldys is an active member of the Applied Mathematics Research Group and The University of Sydney Nano Institute, contributing to interdisciplinary research initiatives that connect mathematical theory with cutting-edge technological applications.
Dr. Bin Tang is a Professor in the Department of Computer Science at California State University, Dominguez Hills. He holds a Ph.D. in Computer Science from Stony Brook University (2007) and dual M.S. degrees in Computer Science and Materials Science from the same institution. His research focuses on algorithmic solutions for data placement in networks, with applications in robotic sensor systems and cloud data centers. He has led multiple NSF-funded projects including 'Edge-Based Approach to Robust Multi-Robot Systems' and 'Optimal Resource Allocation in Policy-Driven Data Centers'. Dr. Tang mentors students in research competitions and has supervised numerous graduate theses. He teaches courses in operating systems, algorithms, computer networks, and cloud computing.
- Computational Materials Science
- Energy Storage Materials
- First-Principles Quantum Mechanics
- +۷ مورد دیگر
Dr. Christopher M. Wolverton is a Professor of Materials Science and Engineering at Northwestern University , where he leads the Wolverton Research Group . His work focuses on computational materials science with applications in energy sustainability , particularly in batteries , hydrogen storage , and thermoelectrics . PhD in Physics from University of California, Berkeley BS in Physics (summa cum laude) from University of Texas, Austin His research leverages first-principles quantum mechanical simulations and machine learning to enable virtual materials synthesis before laboratory testing. The group specializes in hybrid computational methods integrating Density Functional Theory (DFT) , Monte Carlo simulations , and phase-field microstructural models . The article portfolio shows leadership in energy storage materials , with recent work on data-driven nanoparticle facet control , mixed-anion semiconductors , and machine learning-accelerated discovery . Publications span top journals including Nature Energy , Nature Materials , and Science . 2006 Ford Motor Company Technical Achievement Award 2005 Ford Patent & Publication Awards 2003 Ford Environmental/Physical Sciences Recognition As advisor to PhD candidates Zhenpeng Yao , Shiqiang Hao , and Shane Patel , he fosters interdisciplinary research connecting materials informatics with experimental validation . The group maintains active collaborations with Argonne National Lab and MIT/Harvard teams.
Mohamed Bouriمشاهده پروفایل
مدرس ارشد
Mohamed Bouri is a Senior Lecturer and Researcher at École Polytechnique Fédérale de Lausanne (EPFL), where he is affiliated with the School of Engineering (STI) and specifically the Microengineering Department (SCI-STI-MB). He is part of the ReHAssist research group (http://rehassist.epfl.ch), which focuses on rehabilitation robotics and human-robot interaction. His office is located in the MED Building (MED 3 1016) at Station 9, 1015 Lausanne. Dr. Bouri's research spans several key areas in robotics and rehabilitation engineering. His primary focus is on the development and control of exoskeleton systems for mobility assistance and rehabilitation. He has made significant contributions to hip exoskeleton technology, adaptive control strategies, and human-robot interaction paradigms. His work bridges engineering principles with clinical applications, particularly for individuals with mobility impairments and neurological conditions. Additional research interests include sensory substitution techniques, balance control systems, and astronomical instrumentation involving robotic fiber positioners for multi-object spectrographs. Analysis of Dr. Bouri's recent publications reveals a strong emphasis on practical applications of robotics in rehabilitation settings. His work increasingly focuses on user-centered design, adaptive control systems that respond to individual user needs, and ecological validity in testing environments. There's a clear trend toward developing systems that can function effectively in real-world scenarios rather than controlled laboratory settings. His research also shows growing integration of physiological feedback mechanisms and multimodal sensing to enhance human-robot cooperation, with applications spanning from Parkinson's disease rehabilitation to astronomical instrumentation. Dr. Bouri has supervised numerous doctoral students whose theses reflect the breadth of his research interests, including work on lower-limb exoskeletons, robotic control systems, and rehabilitation technologies. His collaborative approach is evident in the extensive list of co-authored publications across multiple institutions and disciplines, demonstrating his ability to bridge engineering with clinical and astronomical applications. Based at EPFL's Microengineering Department, Dr. Bouri leads research activities within the ReHAssist laboratory, which specializes in rehabilitation assistance technologies. The lab focuses on developing innovative robotic solutions for mobility assistance, with particular expertise in exoskeleton design, control algorithms, and human-robot interaction paradigms. His work on projects like TWIICE One has demonstrated real-world impact in assistive technology development.
Bilal Farooqمشاهده پروفایل
دانشیار
- Disruptive transportation technologies and services
- Cyber-physical transportation systems
- Artificial intelligence and machine learning
- +۴ مورد دیگر
Bilal Farooq is an Associate Professor and Program Director for the Master of Engineering in Interdisciplinary Engineering (MEIE) at Toronto Metropolitan University, holding the Canada Research Chair in Disruptive Transportation Technologies and Services within the Department of Civil Engineering. His educational background includes a PhD from the University of Toronto (2011), MASc from Lahore University of Management Sciences (2004), and BSc from the University of Engineering and Technology (2001). Dr. Farooq's research pioneers disruptive transportation solutions through cyber-physical systems, AI/machine learning applications, behavioral modeling, and optimization techniques. His work specifically targets on-demand multimodal systems, sustainable urban transportation, urban air mobility, automated vehicles, and extended reality applications, addressing critical urban mobility challenges with human-centered approaches. Analysis of his recent publications reveals a strong trend toward quantum-enhanced computational methods, privacy-preserving federated learning frameworks, and sustainability-focused decarbonization strategies across transportation domains, with increasing emphasis on human factors and real-world implementation. Notable scientific awards include: Ontario Early Researcher Award (2018) Canada Research Chair (2017) MassMotion Academic Pedestrian Modelling Project of the Year (2016) Québec Early Researcher Award (2014) Dr. Farooq actively supervises graduate students and secures significant research funding through his Canada Research Chair position and Early Researcher Awards. He directs the Laboratory of Innovations in Transportation (LiTrans), which develops interdisciplinary solutions integrating mathematics, engineering, computer science, and economics to address emerging transportation challenges. LiTrans focuses on disruptive transportation technologies, complete streets design, cyber-physical systems, pedestrian dynamics, resilience, and climate change impacts, collaborating with industry and government partners to translate research into practical urban mobility innovations for smart cities worldwide.
Minjie Chenمشاهده پروفایل
دانشیار
Minjie Chen is an Associate Professor of Electrical and Computer Engineering and the Andlinger Center for Energy and the Environment at Princeton University, serving as Acting Associate Director for Research at the Andlinger Center. He leads the Princeton Power Electronics Lab (PowerLab), which focuses on developing fundamental and novel power electronics solutions for a wide range of applications from mW-scale energy harvesting to MW systems in renewable energy integration. Dr. Chen received his Ph.D. in Electrical Engineering and Computer Science from MIT in 2015 and his B.S. in Electrical Engineering from Tsinghua University in 2009. Before joining Princeton as an Assistant Professor in February 2017, he was a postdoctoral associate at MIT Research Laboratory of Electronics. His research spans power electronics, magnetics design, and machine learning applications in energy systems. The PowerLab develops advanced power conversion architectures that enable order-of-magnitude higher power density through high-frequency designs, addressing circuit timing, parasitics, magnetics, and thermal management challenges. Their work targets applications ranging from portable devices to data centers and renewable energy systems. The research group has produced a remarkable series of high-impact publications, with seven IEEE Transactions on Power Electronics Prize Papers in seven consecutive years (2016-2023). Their recent work increasingly integrates machine learning techniques with power electronics, exemplified by the MagNet project which redefines how power magnetics are studied and modeled. NSF CAREER Award, 2019 IEEE PELS Richard M. Bass Outstanding Young Power Electronics Engineer Award, 2023 Power of Associations Silver Award from ASAE for MagNet project, 2024 Multiple IEEE Transactions on Power Electronics Prize Papers (2016-2023) Princeton Engineering Commendation List for Outstanding Teaching (2019, 2020) Dr. Chen advises approximately 15 graduate students who have received numerous awards including the IEEE PELS John G. Kassakian Fellowship, Princeton SEAS Honorific Fellowship, and multiple IEEE conference best paper awards. His research is supported by significant grants from NSF, DOE ARPA-E, Princeton Innovation Fund, C3.ai DTI, and industry partners including Intel, Google, and pSemi. The lab's MagNet project has become a major international initiative with a $60,000 prize pool challenge. The PowerLab maintains strong industry connections and has launched several collaborative projects with Intel, Google, and pSemi. Their MagNet project has evolved into an international challenge with participation from over 40 teams worldwide, demonstrating the growing impact of their approach to machine learning for power magnetics modeling.
Qiang Tangمشاهده پروفایل
دانشیار
Qiang Tang is currently an Associate Professor (Level D) at the School of Computer Science of The University of Sydney. Previously, he was a Senior Lecturer (2021.1-2024.12) at USYD and an Assistant Professor at the Computer Science Department of New Jersey Institute of Technology (2016.8-2021.1), where he co-directed the JACOBI Blockchain Lab with Prof. Jian Pei and Prof. Zhenfeng Zhang. He completed his PhD at the University of Connecticut under Prof. Aggelos Kiayias and Prof. Alexander Russell, following postdoctoral research at Cornell University with Prof. Elaine Shi. His research spans applied and theoretical cryptography, blockchain technology, privacy, and computer security. His work is supported by ARC, Google, Ethereum Foundation, Stellar Foundation, Protocol Labs, Algorand Foundation, Oracle, and USYD. Previous funding includes NSF, JD.com, AFRL, DoE, and Particl Foundation. His research has led to significant contributions in consensus protocols, distributed randomness generation, secure multi-party computation, and privacy-preserving technologies. Tang's publications reveal a strong focus on practical cryptographic solutions for blockchain and distributed systems. His recent work demonstrates expertise in asynchronous consensus, optimal protocol design, and secure implementations for real-world applications. His research shows consistent innovation in improving efficiency, security, and scalability of distributed systems. Scientific Awards: 2025 DSN Best Paper Award 2024 ICDCS Distinguished Paper Award 2023 SOAR Prize, USYD 2023 Oracle for Research Award 2022 Stellar Foundation Research Awards 2022 Ethereum Academic Award 2019 MIT Technical Review, 35 Chinese Innovators Under 35 Tang actively mentors PhD and Master's students, with several alumni now holding faculty positions or research roles at institutions like City University Hong Kong, Chinese Academy of Sciences, and A*STAR Singapore. He has received significant research funding including a multi-year Google project on End-to-End Secure Cloud and an ARC DP grant on Order Fairness in Decentralized Systems. He leads the research in his lab focusing on blockchain protocols and cryptographic applications, with strong industry connections through collaborations with Google, Ethereum Foundation, Stellar Foundation, and Protocol Labs. His team regularly publishes in top security and cryptography venues including CRYPTO, CCS, USENIX Security, and S&P.
Zara Ersozluمشاهده پروفایل
مدرس ارشد
Dr. Zara Ersozlu is a Senior Lecturer in Mathematics Education within the School of Education at the University of Newcastle, Australia. With a distinguished international career spanning multiple continents, she has held academic positions at prestigious institutions including North Carolina State University (USA), Gazi and Gaziosmanpasa Universities (Turkey), National Taiwan Normal University (Taiwan), The University of Western Australia, Murdoch University, and Deakin University. Her academic journey includes tenured positions as an Associate Professor and leadership roles as Department Head and Chair in teacher education disciplines. Currently, she teaches undergraduate and postgraduate courses in mathematics education, including Effective Pedagogies in Primary Mathematics, K-6 Mathematics, K-6 Numeracy, and Digitally Supported Learning. Dr. Ersozlu earned her Doctor of Philosophy from Firat University in Turkey and her Master of Art from Sakarya University. Her extensive academic preparation is complemented by five years of practical teaching experience in public schools prior to entering academia. This blend of theoretical knowledge and practical classroom experience informs her approach to teacher education and educational research. At the broadest level, Dr. Ersozlu's research investigates solutions to real-life problems impacting people's well-being, success, and capacity to achieve. Her scholarly work spans primary and secondary mathematics education, the psychology of mathematics (including metacognition, self-regulation, and anxiety), cross-cultural educational studies, teacher education, virtual simulated learning environments, and educational assessment. She has increasingly focused on the transformative potential of AI and machine learning in education, exploring how these technologies alter teaching, learning, and research processes. Her methodological expertise encompasses both quantitative and qualitative approaches, allowing her to effectively analyze both small and large educational datasets. Analysis of Dr. Ersozlu's recent publications reveals a strong emphasis on mathematics anxiety, teacher education, and the integration of technology in learning environments. Her work demonstrates a consistent focus on practical applications of educational research to address real-world challenges in mathematics education. The interdisciplinary nature of her research connects educational psychology, technology integration, and cross-cultural perspectives, with particular attention to how these elements intersect in teacher preparation and student learning outcomes. 2023 ATEA Research Recognition Award from the Australian Teacher Education Association 2021 Fellow of the Higher Education Academy (Advance HE, UK) 2010 Fellowship Program for Postdoctoral Researchers from the Council of Higher Education of Turkey Dr. Ersozlu is deeply committed to mentoring the next generation of scholars, currently supervising four PhD students and having successfully guided ten students to completion. Her grant portfolio includes significant funding for projects such as Best Practice Guidelines for RPL in Initial Teacher Education Programs ($60,000), Exploring the Reciprocal Relationship Between Mathematics Anxiety and Mathematical Resilience ($2,599), and multiple conference travel awards. She serves as an Associate Editor for several prominent journals including the International Electronic Journal of Mathematics Education and as Editor for Interdisciplinary STEM Education. Her editorial work reflects her standing as a respected voice in mathematics education research. Dr. Ersozlu's academic leadership extends to her role in developing innovative teaching approaches that integrate virtual simulation technology and learning analytics. Her work with TeachLivE™, a mixed-reality classroom simulation platform, demonstrates her commitment to creating authentic learning experiences for teacher education students. Through these initiatives, she bridges the gap between educational theory and classroom practice, preparing future educators to effectively implement evidence-based teaching strategies in diverse learning environments.
Scott Kerlinمشاهده پروفایل
مدرس ارشد
Scott Kerlin is a Senior Lecturer in the Department of Electrical Engineering and Computer Science at Oregon State University's College of Engineering. He holds an M.S. and B.S. in Computer Science from the University of North Dakota. Prior to academia, he worked at the Mayo Clinic on medical software systems and IBM as a build master for enterprise products. His career spans roles including network administrator, lab manager, and Undergraduate Director at UND. Dr. Kerlin's research focuses on bridging industry experience with academic curriculum, particularly in computer science education, project-based learning, and cybersecurity. He emphasizes practical applications of theoretical concepts, such as integrating 3D printing and scanning technologies with security systems for small satellites. His work also explores student efficacy in AI courses and scalable software project management methodologies. He has taught at multiple institutions, including the University of Minnesota and Augsburg University, and held roles at Michigan Tech as Senior Security Engineer. His 2024 Engineering+ Outstanding Teaching Award highlights his commitment to pedagogical innovation. Current projects include in-space 3D printing, solar energy systems, and cryptographic solutions for satellite communications. Key areas of contribution include: 3D printing/Scanning: Material characterization, key replication, and aerospace applications Cybersecurity: Intrusion detection, satellite communications security, and chaotic cryptosystems Educational Innovation: Active learning frameworks, PBL implementation, and student performance modeling His interdisciplinary approach connects computer science fundamentals with real-world engineering challenges, emphasizing sustainability and industry relevance in curricula.
- Edge Computing
- Fog Computing
- Distributed Systems
- +۵ مورد دیگر
Umakishore Ramachandran is a Professor in the School of Computer Science within the College of Computing at Georgia Institute of Technology. His research spans edge computing, distributed systems, and real-time video analytics, with significant contributions to fog computing infrastructure, mobile systems, and sensor networks. Over a prolific 38-year career, he has authored 142 publications with major contributions in 2022-2025. His research interests focus on bridging the gap between cloud and edge computing, with pioneering work in video analytics systems like EVA and MicroEdge. He investigates resource optimization for latency-sensitive applications, developing novel approaches for load shedding, data management, and container runtime efficiency at the network edge. His work addresses fundamental challenges in distributed camera networks, autonomous vehicle systems, and real-time stream processing. Ramachandran's recent publications reveal a strong emphasis on practical edge computing solutions, with 75% of his 2021-2025 work focusing on video analytics and infrastructure optimization. His research shows increasing collaboration with industry partners while maintaining academic rigor, with publications appearing in top venues like SIGMOD, Middleware, and DEBS. The work consistently addresses real-world constraints of resource-constrained edge environments. Ramachandran has mentored numerous researchers who have become principal investigators on edge computing projects, with notable collaborators including Harshit Gupta, Enrique Saurez, and Zhuangdi Xu appearing as first authors on multiple papers. His work has received significant grant support for projects related to mobile fog computing and distributed video analytics. He leads research in the Edge Computing Laboratory at Georgia Tech, focusing on the development of practical frameworks for real-world deployment of edge infrastructure. Current projects include eCAV for connected autonomous vehicles and MicroEdge for multi-tenant camera processing systems.
Jon M. Peha is a Full Professor in the Department of Engineering and Public Policy and the Department of Electrical and Computer Engineering at Carnegie Mellon University's College of Engineering. He serves as Founder and Director of the Center for Executive Education in Technology Policy (CEE-TP) and maintains affiliations with the CyLab Security and Privacy Institute and the Information Networking Institute. His career uniquely bridges government service (as FCC Chief Technologist, White House OSTP Assistant Director, and congressional advisor), industry leadership (as CTO for three tech startups), and academic research. Education: Ph.D. in Electrical Engineering, Stanford University (1991) M.S. in Electrical Engineering, Stanford University (1986) B.S. in Electrical Engineering and Computer Science, Brown University (1984) Peha's research spans the technical and policy dimensions of information networks, with particular focus on spectrum management, broadband Internet architecture, wireless communications, cybersecurity, and communications for emergency response. His work integrates engineering principles with economic and regulatory analysis to address real-world challenges in telecommunications infrastructure. Current projects examine connected vehicle communications, spectrum sharing models, and consumer-centric broadband labeling systems that emerged from his large-scale user studies. His research publications demonstrate consistent leadership in both technical innovation and policy analysis, with recent work addressing satellite interference mitigation, V2X communications, and pandemic-era internet performance. The breadth of his scholarship reflects his unique position at the intersection of engineering practice and policy formulation. Scientific Awards: IEEE Fellow AAAS Fellow FCC Excellence in Engineering Award IEEE Communications Society TCCN Publication Award Brown Engineering Medal AAAS Featured Science and Technology Policy Fellow (40@40) Peha actively engages with policymakers through congressional testimony, FCC consultation, and White House advisory roles. His government service has directly informed his academic work on spectrum policy, network neutrality, and public safety communications. He has supervised numerous graduate students across EPP, ECE, and INI programs, with research spanning vehicular networks, spectrum sharing, and emergency communications systems. As Director of CEE-TP, he leads executive education initiatives that bridge technical expertise and policy decision-making. His work with CyLab focuses on cybersecurity and privacy challenges in broadband systems and connected vehicles. Current projects include developing cost-effective spectrum sharing models for intelligent transportation systems and analyzing the economic implications of multi-network access architectures in 5G networks.
Jan de Gier is a Professor at the School of Mathematics and Statistics, The University of Melbourne . He is also the Founding Director of MATRIX , Australia’s residential research institute in the mathematical sciences, and a former Deputy Director and Chief Investigator in the Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) . Additionally, he co-founded the Australian and New Zealand Association for Mathematical Physics (ANZAMP) in 2011 and served as its inaugural Chair. His research focuses on solvable lattice models at the intersection of mathematical physics and statistical mechanics . Key areas include the application of quantum integrability , algebraic structures like the Yang-Baxter equation, Hecke algebras, and quantum groups, as well as analytical methods such as complex analysis and elliptic curves. His work bridges pure and applied mathematics through connections between enumerative combinatorics , representation theory , and real-world phenomena like traffic flow modeling via exclusion processes . The 15 most recent articles reflect his expertise in integrable systems , non-equilibrium statistical mechanics , and algebraic combinatorics . Topics span Macdonald polynomials , stochastic duality , quantum spin chains , and traffic modeling , with methodologies involving matrix product forms , exact solutions , and critical phenomena analysis. He has contributed to editorial efforts through the AustMS Gazette and MATRIX Annals, and has been involved in public science communication via opinion pieces on mathematics funding and applications. His work emphasizes the importance of fundamental research in driving technological innovation, as highlighted in media articles discussing pi calculation , zero-knowledge proofs , and mathematics education .
- Nanotechnology
- Materials Science
- Nanocrystals
- +۷ مورد دیگر
Nuri Yazdani is a Lecturer at the Department of Information Technology and Electrical Engineering at ETH Zürich, Switzerland. Based at the Institute for Electronics (Institut für Elektronik) in Zurich, Dr. Yazdani contributes to both teaching and research in advanced materials and nanotechnology. His work spans multiple interdisciplinary areas connecting physics, chemistry, and electrical engineering, with particular emphasis on nanocrystal-based materials and their applications in electronics and optoelectronics. Dr. Yazdani's research focuses on the synthesis, characterization, and application of nanomaterials, particularly semiconductor nanocrystals and quantum dots. His work explores the fundamental physical properties of these materials, including exciton-phonon interactions, structural ordering in multicomponent systems, and charge transport mechanisms in nanocrystal assemblies. He investigates how nanoscale phenomena affect macroscopic material properties, with applications ranging from catalysis to optoelectronic devices. His approach combines experimental techniques like small-angle X-ray scattering with theoretical modeling to understand structure-property relationships in nanomaterials. Analysis of Dr. Yazdani's recent publications reveals a strong emphasis on perovskite and chalcogenide nanocrystals, with particular interest in how structural features like cation distribution, octahedral tilting, and surface chemistry affect optical and electronic properties. His work bridges fundamental physics with practical applications, spanning from quantum optics to energy conversion technologies. A recurring theme is the investigation of size-dependent phenomena and the role of phonons in determining material behavior at the nanoscale. Dr. Yazdani collaborates extensively with researchers across multiple institutions and disciplines, as evidenced by his authorship on numerous multi-investigator publications. His work appears in high-impact journals including Nature Communications, Journal of the American Chemical Society, and Nature Physics, reflecting the significance and interdisciplinary nature of his contributions to nanoscience and nanotechnology.
Deepak Ganesan is a Professor at the Manning College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. His research focuses on low-power sensing and communication, networked systems, and machine learning applied to pervasive health monitoring and societal challenges. PhD, Computer Science, University of California, Los Angeles (2004) MS, Computer Science, University of California, Los Angeles (2000) BTech, Computer Science, Indian Institute of Technology, Madras (1998) Ganesan's work bridges wireless sensor networks, smart textiles, and healthcare applications. He designs ultra-low-power wearable devices for tracking health signals like drug use, smoking, and cognitive performance, often integrating machine learning for robust detection. His research emphasizes societal impact, particularly in aging and Alzheimer's care through the Massachusetts AI and Technology Center for Connected Care (MassAITC) and the Center for Personalized Health Monitoring (CPHM). Recent publications highlight innovations in edge-cloud collaboration, fabric-based sensors, and longitudinal health analytics. His NIH-funded MD2K Center for Excellence and affiliations with the Center for Data Science and Computational Social Science Institute further underscore his interdisciplinary approach. ACM Fellow NSF CAREER Award (2006) IBM Faculty Award (2008) UMass Junior Faculty Fellow (2008) UMass Lilly Teaching Fellow (2009) Best Paper at CHI 2013 Best Paper Runner-up at Mobicom 2014 Honorable Mentions at Ubicomp 2013 Ganesan leads the SENSORS: Wireless Sensor Networks Group and contributes to global initiatives like the Internet of Battlefield Things. His work spans academic research, industry partnerships, and policy development in AgeTech and digital health.