Find Academic Supervisors

Raju VatsavaiView profile

Associate Professor

• Geospatial Analytics
• Big Data Management
• Data Mining
• +5 more

Raju Vatsavai is an Associate Professor in the Department of Computer Science at North Carolina State University, affiliated with the Center for Geospatial Analytics. He joined NC State in 2014 as part of the Chancellor’s Faculty Excellence Program cluster hire in Geospatial Analytics. Education: PhD and MS in Computer Science from University of Minnesota Prior Roles: Lead Data Scientist at Oak Ridge National Lab, roles at University of Minnesota, IBM Research, AT&T Labs, and C-DAC (India) His research in geospatial analytics spans big data management , spatiotemporal data mining , deep learning for remote sensing , and high-performance computing , with applications in national security, climate change, and crop monitoring. Recent work includes deep learning frameworks for cloud imputation , multi-sensor satellite data harmonization , and transfer learning applications in crop classification . He has been a leading investigator on grants from the National Geospatial-Intelligence Agency, Department of Energy, and Department of Homeland Security. Labs: Associate Director of the Center for Geospatial Analytics Expertise: Spatial computing, Earth observation, nuclear proliferation detection via remote sensing

Ali KashaniView profile

Senior Lecturer

• Sustainable and low-carbon concrete
• Cementitious materials
• Robot-aided construction
• +8 more

Dr. Ali Kashani is a Senior Lecturer at the University of New South Wales (UNSW) within the School of Civil and Environmental Engineering. His research focuses on sustainable and low-carbon concrete materials, robot-aided construction (particularly 3D printing), and Circular Economy-aligned applications. Leadership in cementitious materials innovation Expertise in 3D printing for construction Advocate for waste valorisation and carbon capture Dr. Kashani has secured approximately $7 million in research funding and holds a patent in lightweight concrete foam. His work spans 70+ publications with 9,000+ citations, including media coverage in the Sydney Morning Herald and The Fifth Estate. He actively contributes to professional organizations such as MECLA, RILEM, and ASTM. Recent research trends include AI and optimization algorithms for sustainable concrete mix design, chloride diffusion modeling, and 3D printing performance analysis. His publications often address waste material integration, durability assessment, and eco-friendly construction practices. Scientific Awards: National and NSW Awards for 'Excellence in Concrete' (Technology and Innovation) from the Concrete Institute of Australia Churchill Fellowship for Digital Construction and 3D Printing sponsored by AVJennings Dr. Kashani serves as Co-Chair of the cement and concrete working group at MECLA and contributes to RILEM and ASTM committees. His email is ali.kashani@unsw.edu.au , and his office is located in the Civil Engineering Building (H20), Level 2, Room CE204, UNSW.

Thomas DC LittleView profile

Professor

• Visible Light Communications
• Optical Wireless Communications
• Indoor Positioning Systems
• +5 more

Thomas DC Little is a Professor of Electrical and Computer Engineering in the College of Engineering at Boston University. He serves as the Associate Dean for Educational Initiatives, driving the growth of the engineering master’s program and enhancing pedagogy through mobile and cloud technologies. Additionally, he is the Associate Director and Principal Investigator of the National Science Foundation Smart Lighting Engineering Research Center (LESA), a multi-institutional effort advancing visible light communication and smart lighting systems. Professor Little's research centers on ubiquitous computing and communications, with a focus on using optical cells to expand wireless data capacity for mobile devices. He pioneers ambient intelligence that enables environments to anticipate human needs. His key areas include Visible Light Communications (VLC), Optical Wireless Communications, Indoor Positioning Systems, and Smart Lighting. By integrating lighting infrastructure with communication networks, his work addresses the growing demand for wireless data and enables energy-efficient, responsive smart buildings and urban environments. Analysis of his recent publications (2019-2024) shows a strong trend toward occupancy sensing, indoor positioning, and hybrid RF/VLC networks. His team develops innovative solutions for people counting, zone-based positioning, and interference mitigation in dense optical wireless environments. There is increasing integration of machine learning for security and optimization, with applications in energy-efficient buildings and user-centric smart spaces. Scientific awards received by Professor Little include: Janetos Award for Continuous Indoor Air Quality Assessment for BU Buildings (2025) Professor Little actively mentors graduate students and postdocs, with notable advisees including Iman Abdalla (awarded Best Computer Engineering Dissertation, 2020-2021) and the MenuNav team (Societal Impact Award for a navigation app for the blind). He has secured significant research funding, including a $1M Department of Energy/ARPA-E project for occupancy sensing to reduce energy costs in commercial buildings and grants for indoor air quality sensor development. He leads the NSF Smart Lighting ERC (LESA), which develops COSSY people counting technology, sensory lighting systems, and dynamic light control applications. His team collaborates with industry and has spun off Helux Technologies, Inc. to commercialize dynamic lighting control. Current projects focus on creating safe, energy-efficient buildings through advanced sensor integration and wireless communication.

• Memory Systems Design
• High-Performance Computing
• Exascale Systems Architecture
• +7 more

Bruce Jacob is a Keystone Professor and Full Professor in the Department of Electrical & Computer Engineering at the University of Maryland College Park's College of Engineering. His research primarily focuses on memory systems design and exascale computing architectures, with significant contributions to DRAM simulation and high-performance computing systems. Dr. Jacob received his A.B. in Mathematics from Harvard University (1988), followed by his M.S. and Ph.D. in Computer Science & Engineering from the University of Michigan (1995 and 1997 respectively). His research interests include memory systems design, exascale computing architectures, embedded systems, circuit integrity, and algorithmic composition. His recent publications demonstrate a strong focus on next-generation memory technologies, particularly ReRAM and advanced DRAM architectures. His work bridges the gap between theoretical modeling and practical implementation, with significant contributions to memory system simulation through projects like DRAMsim. His research shows a consistent trajectory toward solving the memory bottleneck problem in high-performance computing systems. Named Fellow, IEEE (2021) Multiple University of Maryland Research Leader awards (2006, 2010, 2012, 2016, 2017) Clark School of Engineering Keystone Professor (2006) National Science Foundation CAREER Award (2000) University of Maryland Award for Teaching Excellence (2004) Dr. Jacob has led significant research initiatives including the University of Maryland Exascale Systems Research and Memory-Systems Research groups. He has developed important computational artifacts such as DRAMsim (a public-domain DRAM-system simulator) and BioBench (a set of bioinformatics workloads). His work has influenced both academic research and industry practices in memory system design.

Nikos HardavellasView profile

Professor

• Computer Architecture
• Quantum Computing Systems
• Parallel Systems
• +4 more

Nikos Hardavellas is a Professor of Computer Science and Electrical and Computer Engineering at Northwestern University, affiliated with the McCormick School of Engineering. He leads the Parallel Architecture Group at Northwestern (PARAG@N), focusing on energy-efficient parallel computing and quantum systems. His research spans quantum computing systems, fault-tolerant quantum error management, memory-centric architectures, and photonics-based interconnects. Education: Ph.D. Computer Science, Carnegie Mellon University (2009) M.S. Computer Science, Carnegie Mellon University (2006) M.S. Computer Science, University of Rochester (1997) B.S. Computer Science, University of Crete (1995) Research Interests: Quantum system software stack and error mitigation Memory-centric computing and programmable memory systems Energy-efficient architectures and dark silicon Photonics and optical interconnects Parallel systems and compiler-hardware co-design Key Contributions: Developed SupermarQ, a scalable quantum benchmark suite Pioneered optical cache hierarchies (Pho$) and energy-proportional photonic networks Advanced compiler-driven virtual memory systems (CARAT) and MPI autotuning (ACCLAiM) Awards & Honors: NSF CAREER Award (2015) Future CRA Leader (2024) Best Paper Awards at HPCA (2022) and ISLPED (2021 nomination) Test-of-Time Award at EDBT (2019) Grants & Service: Secured $4.8M in research funding from NSF, industry partners, and university initiatives Executive Committee member of Northwestern’s INQUIRE Institute for Quantum Research General Co-chair of IEEE/ACM MICRO 2022 Extensive service on departmental committees and thesis advisory boards Labs & Teams: Directs PARAG@N, collaborating on quantum computing, photonics, and energy-efficient architectures. Engages with industry partners like AMD, Intel, and Synopsys.

Rob PooleView profile

Professor

• Rheology
• Fluid Mechanics
• Non-Newtonian Fluid Mechanics
• +5 more

Professor Rob Poole holds the Harrison Chair in Mechanical Engineering at the University of Liverpool’s School of Engineering, part of the Faculty of Science and Engineering. Previously Head of Department (2017–2021), he co-edits the Journal of Non-Newtonian Fluid Mechanics . His research focuses on rheology, fluid mechanics, and turbulence, with recent work on polymeric drag reduction, superhydrophobic surfaces, and viscoelastic instabilities. Education: BEng (Hons) and PhD in Mechanical/Aerospace Engineering. Research Interests: Non-Newtonian fluid mechanics Elastic turbulence and viscoelastic instabilities Polymer solutions and additive effects Heat transfer in porous media Constitutive equation development Awards & Fellowships: EPSRC Complex Fluids and Rheology Fellowship (2015–2021) British Society of Rheology Annual Award (2018) 2015 Best Paper Award (Theoretical and Applied Mechanics Letters) Grants & Projects: Funded projects include Flexible Heat Pump development (£1.5M), Instabilities in Complex Fluid Flows (£1.2M), and Superhydrophobic Surface Drag Reduction (£0.8M) Industry collaborations: Schlumberger, Procter & Gamble, National Nuclear Laboratory Professional Activities: Editorial roles: Journal of Non-Newtonian Fluid Mechanics (Co-Editor-in-Chief), Physics of Fluids External examiner at Warwick, Strathclyde, and multiple Indian Institutes of Technology

Paul O'GormanView profile

Professor

• Atmospheric Dynamics
• Climate Change
• Hydrological Cycle
• +3 more

Paul O'Gorman is a Professor at the Department of Earth, Atmospheric and Planetary Sciences (EAPS) at the Massachusetts Institute of Technology. He currently serves as the Faculty Chair of the EAPS Committee on Education and as the EAPS Graduate Officer. His research focuses on understanding how climate change affects atmospheric circulation and precipitation patterns, particularly extreme events. Education: BA in Theoretical Physics, Trinity College Dublin MSc in High-Performance Computing, Trinity College Dublin PhD in Aeronautics with Minor in Applied Mathematics, California Institute of Technology Research Interests include atmospheric dynamics, hydrological cycle responses to climate change, moist convection, and the application of machine learning to climate modeling. His work addresses regional variability in extreme precipitation, vertical warming profiles in the tropics, and the fluid dynamics of land-ocean warming contrasts. Scientific Awards : Bernhard Haurwitz Memorial Lectureship (2023), American Meteorological Society MIT School of Science Graduate Teaching Prize (2018) Recent Contributions include co-leading the MIT Climate Grand Challenges flagship project "Preparing for a new world of weather and climate extremes" , which develops tools for predicting climate extremes and transitioning to low-carbon resources. He has also explored the asymmetrical generalization capabilities of machine learning algorithms in climate models under warming versus cooling scenarios.

• Signal Processing
• Wireless Communications
• Underwater Acoustic Communications
• +7 more

Professor Yue Rong is a Full Professor at Curtin University's Department of Electrical and Computer Engineering, within the School of Electrical Engineering, Computing and Mathematical Sciences. He holds editorial roles at IEEE Transactions on Signal Processing and IEEE Wireless Communications Letters. His research focuses on signal processing for communications, underwater acoustic systems, wireless networks, and healthcare IoT. Rong has authored over 140 journal and conference papers and received multiple awards, including the 2010 Young Researcher of the Year Award. Education: B.E. (Electrical Engineering), Shanghai Jiao Tong University (1999) M.Sc. (Electrical Engineering), University of Duisburg-Essen (2002) Ph.D. (Electrical Engineering), Darmstadt University of Technology (2005) Research Interests: Rong's work spans cooperative MIMO communications, underwater acoustic systems, OFDM modulation, radar-based healthcare monitoring, and secure wireless protocols. His innovations include adaptive modulation schemes for underwater environments and radar-based vital signs detection. Recent trends in his publications emphasize AI-driven signal processing for healthcare IoT and underwater optical communication systems. Awards: Best Paper Awards (WCSP 2011, APCOMM 2010) Chinese Government Award (2004) DAAD/ABB Fellowship (2001-2002) Grants & Labs: His research is supported by grants focusing on UAV-enabled data collection and underwater network optimization. He leads projects in the Distributed Data Fusion and Emerging Technologies (DDFE) lab, advancing radar-cardiography and wearable health monitoring systems.

Jason D. BakosView profile

Professor

• Computer Architecture
• Reconfigurable Computing
• High-Performance Computing
• +4 more

Dr. Jason D. Bakos is a Professor in the Department of Computer Science and Engineering at the University of South Carolina's Molinaroli College of Engineering and Computing. His research focuses on high-performance domain-specific architectures, including reconfigurable computing, embedded systems, and machine learning acceleration. He has held academic positions since 2005, progressing from Assistant to Associate Professor before becoming a full Professor in 2017. Education : Ph.D., Computer Science, University of Pittsburgh (2005) B.S., Computer Science, Youngstown State University (1999) Research Interests : Dr. Bakos specializes in computer architecture at multiple levels (circuit, micro-architectural, and system) with a focus on VLSI design, reconfigurable computing, high-performance computing, and applications in embedded systems. His recent work includes FPGA acceleration of machine learning algorithms, structural health monitoring systems, and real-time signal processing. Awards : 2018 Teaching Award in Computer Science and Engineering 2009 NSF CAREER Award Multiple design competition awards for innovative chip and circuit designs Grants & Funding : He leads and co-leads projects funded by NSF, Savannah River National Laboratory, and industry partners like Texas Instruments. Recent grants focus on edge computing for real-time machine learning, FPGA-based accelerators, and corrosion analysis of nuclear materials. Labs & Teams : His research group collaborates on projects involving embedded systems, FPGA design, and interdisciplinary applications in structural engineering and bioinformatics. He advises a dynamic team of graduate students and post-doctoral researchers.

Sujan Kumar RoyView profile

Academic

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +6 more

Sujan Kumar Roy is an Assistant Teaching Professor in the Department of Computer Science at Michigan Technological University. He holds a Ph.D. in Machine Learning with Computer Engineering and Signal Processing from Griffith University, Australia, and has earned multiple academic distinctions, including the 'Award of Excellence in the Research Thesis' and consideration for the 'Chancellor's Medal for Excellence in Ph.D. Thesis 2021.' Dr. Roy's teaching focuses on Computational Intelligence, Foundations of Data Science, Machine Learning, Data Mining, and Introduction to Data Science. His research explores applications of AI, ML, and Data Science in Cybersecurity, Medical Image Analysis, Healthcare Systems, and Speech Enhancement. He has contributed extensively to speech enhancement techniques, integrating Kalman filters with machine learning and deep learning approaches. Recent research trends in his publications emphasize the development of robust algorithms for speech enhancement in noisy environments, fusion datasets for hate speech detection, and adaptive filtering methods. His work bridges signal processing and AI, aiming to improve real-time system performance and noise robustness. Awards: Award of Excellence in the Research Thesis Consideration for Chancellor's Medal for Excellence in Ph.D. Thesis 2021 In teaching, Dr. Roy emphasizes foundational concepts and their practical applications. His grants and collaborations focus on advancing AI-driven solutions for healthcare and cybersecurity challenges. He is affiliated with the Department of Computer Science at Michigan Tech, contributing to both academic and research missions.

Jason TrelewiczView profile

Professor

• Materials Science
• Nuclear Engineering
• Advanced Materials for Extreme Environments
• +4 more

Jason Trelewicz is a Professor at Stony Brook University’s Department of Chemical & Molecular Engineering and holds joint faculty status at Oak Ridge National Laboratory. His research focuses on interface-engineered materials for extreme environments, leveraging advanced processing, characterization tools, and multiscale modeling. He received his Ph.D. in Materials Science from MIT (2008) and previously served as Research Director at MesoScribe Technologies. His work emphasizes fusion materials, nanocrystalline alloys, additive manufacturing, and radiation effects. Awards include the DOE Early Career Award (2017), NSF CAREER Award (2016), and multiple best paper awards (2022). His lab, the Engineered Microstructures and Radiation Effects Laboratory, explores topics like ceramic composite moderators and plasma-facing materials. Education: Ph.D., Materials Science & Engineering, MIT (2008) Affiliations: Oak Ridge National Laboratory (Joint Faculty) Key research areas include thermal-mechanical evaluation of fusion reactor components, alloy design for additive manufacturing, and radiation tolerance of nanocrystalline materials. He has pioneered studies on helium bubble dynamics in tungsten and stability of doped nanocrystalline alloys. Awards: DOE Early Career Award, NSF CAREER Award, 2022 Best Paper Awards in Nuclear Materials and Asian Ceramics. Grants/Projects: Supported by DOE, NSF, and collaborative initiatives with Japan (FRONTIER). His group investigates corrosion behavior in 3D-printed steels and develops novel composite moderators for high-temperature reactors. Ongoing work includes multiscale modeling for fusion materials and in-situ TEM studies of irradiation effects.

Justin GottschlichView profile

Academic

• Machine Programming
• Artificial Intelligence
• Software Engineering
• +3 more

Justin Gottschlich is an Adjunct Lecturer in the Computer Science Department at Stanford University, where he teaches the graduate course Machine Programming (CS 329M) . He also serves as Founder, CEO, and Chief Scientist of Merly Inc., a startup focused on machine programming systems to improve software development efficiency and quality. Previously, he led the Machine Programming Research group at Intel Labs, pioneering advancements in automating software development through a fusion of machine learning, programming languages, and systems research. His academic roles include prior positions as Adjunct Professor at University of Colorado-Boulder and Adjunct Assistant Professor at University of Pennsylvania. He has advised numerous graduate students across institutions, contributing to their research in machine programming and related fields. Gottschlich has authored dozens of research papers and holds multiple patents, with his work highlighted by prominent outlets like the Wall Street Journal and Communications of the ACM. He actively contributes to academic committees, including serving as Steering Committee Chair for the ACM SIGPLAN Machine Programming Symposium (MAPS). His research interests span machine programming, autonomous software development, formal methods, and the integration of AI into software engineering practices. Education: PhD in Computer Science from University of Colorado-Boulder Keynote Engagements: LADSIOS (2021), MIT DSAIL (2021), Penn PRECISE (2019) Labs/Teams: Intel Labs Machine Programming Research Group, Merly's R&D Team Grants & Funding: Extensive industry and academic research funding through Intel Labs and Merly

• Optical Networking
• High-Speed Networks
• Data Center Technologies
• +6 more

Emmanouel (Manos) Varvarigos is a Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), where he leads the High Speed Communication Networks Laboratory. He holds a Diploma from NTUA (1988) and an M.S./Ph.D. from MIT (1990/1992). Prior roles include Professorships at UC Santa Barbara (1992-1998) and Delft University (1998-1999), and leadership at the University of Patras (1999-2015). He has coordinated over 30 EU research projects, including H2020 initiatives like ORCHESTRA and FLEXGRID. His research focuses on optical networking, cloud computing, smart energy grids, and high-speed network protocols. He has published over 450 papers and serves on numerous conference committees. Awards include the NSF Research Initiation Award. His lab employs 5 postdocs and 10+ PhD students, addressing challenges in networking, data centers, and grid computing. Education: Ph.D., Electrical Engineering and Computer Science, MIT, 1992 M.S., Electrical Engineering and Computer Science, MIT, 1990 Diploma in Electrical and Computer Engineering, NTUA, 1988 Research Interests: Optical networking, high-speed network protocols, data center architectures, cloud computing, smart energy grids, wireless networks, and distributed systems. Grants & Projects: Coordinated 7 EU projects (e.g., FLEXGRID, ORCHESTRA) and participated in 35+ others. National projects include roles as Scientific Director of the Greek School Network and CTI’s Network Technologies Division. Labs & Teams: Directs the High Speed Communication Networks Lab (HSCNL), collaborating with global institutions on optical networks, edge cloud, and smart grids. The lab’s work includes EU-funded projects on 5G, data centers, and renewable energy integration.

Juan AlonsoView profile

Professor

• Aerospace System Design
• Computational Fluid Dynamics
• Multi-Disciplinary Optimization
• +7 more

Prof. Juan Alonso is the Vance D. and Arlene C. Coffman Professor and James & Anna Marie Spilker Chair in the Department of Aeronautics & Astronautics at Stanford University. He directs the Aerospace Design Laboratory (ADL), focusing on high-fidelity computational methods for aerospace system design. His expertise spans transonic/supersonic/hypersonic aircraft, rotorcraft, and launch vehicles. Alumni include record-holding teams for human-powered watercraft and lightweight unmanned aerial vehicles. Education: PhD (1997) from Princeton University in Mechanical & Aerospace Engineering; M.A. (1993) Princeton; B.S. (1991) MIT Aeronautics/Astronautics. Research emphasizes multi-disciplinary optimization, numerical methods, and parallel computing applied to advanced aircraft design, sustainable aviation, and UAS systems. Notable contributions include computational design frameworks like SU2 and SUAVE, and initiatives in curriculum development for engineering education. Recent work focuses on: GPU-accelerated CFD solvers, multi-fidelity surrogate models (e.g., VortexNet), contrail simulation frameworks, and battery degradation modeling for electric aircraft. Active in urban air mobility and high-fidelity trajectory optimization for hypersonic systems. Labs/Teams: Aerospace Design Laboratory (ADL) leading open-source computational tools development. Involved in NASA-funded projects and industry partnerships for advanced propulsion systems.

Gianluca PiazzaView profile

Professor

• MEMS/NEMS
• Nanotechnology
• Piezoelectric Devices
• +7 more

Gianluca Piazza is the STMicroelectronics Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in Mechanical Engineering. He directs the John and Claire Bertucci Nanotechnology Laboratory (CMU Nanofab). Previously, he was the Wilf Family Term Assistant Professor at the University of Pennsylvania. His research focuses on piezoelectric micro/nano electromechanical systems (M/NEMS) for RF communication, optomechanics, chemical/biological sensing, and mechanical computing. Key projects include nanorelays for low-power computing, ultrasound-based wireless powering, and piezoelectric MEMS for energy harvesting. Education: PhD (2005) in Electrical Engineering from UC Berkeley; MS (2001) from University of Texas at Austin and Politecnico di Milano (Italy). Research Interests: M/NEMS design, micro/nano fabrication, piezoelectric materials, mechanical switches, and energy-efficient electronics. His work bridges fundamental science and applied engineering, with patents in micromechanical resonators and awards including the IBM Young Faculty Award (2006) and multiple IEEE Best Paper Awards. Grants & Collaborations: NSF LEAP-HI grant ($2M) for nanorelay development (2020); CMU Kavčić-Moura Endowment funding. Collaborates with Maarten de Boer (Mechanical Engineering) and institutions like the University of Pennsylvania and City University of Hong Kong. Labs & Teams: Leads the Piazza Micro and Nano Systems Laboratory, focusing on NEMS/MEMS innovation. Active in CMU’s Center for Silicon System Implementation and Engineering Research Accelerator.