جست‌وجوی استاد و پژوهشگر

• Entrepreneurship
• STEM Education
• Computer Science
• +۳ مورد دیگر

Edgar Troudt, Ph.D., is the Assistant Dean for Research and Strategic Partnerships at Long Island University Brooklyn, where he serves on the entrepreneurship faculty. His work focuses on integrating entrepreneurship concepts into STEM fields through programs like the CUNY Community College Innovation Challenge and the Brooklyn Science Innovation Initiative. Doctor of Philosophy (Computer Science), CUNY Graduate Center Master of Philosophy (Computer Science), CUNY Graduate Center Master of Arts (Computer Information Systems), CUNY Brooklyn College Dr. Troudt’s research explores the intersection of STEM and entrepreneurship education, emphasizing virtual enterprise models, innovation in community colleges, and technology-driven curriculum development. His recent publications highlight strategies for embedding business skills into technical education. Scientific awards include the 2015 Homer Saunder’s Outstanding Paper Award, the 2011 CUNY Michael Ribaudo Award for technology innovation, and the 2008 Best of New York Award for creative technology applications. He has also received recognition for teaching excellence and NSF grant leadership.

Georgia Perakisمشاهده پروفایل

استاد

• Analytics/AI
• Optimization
• Machine Learning
• +۴ مورد دیگر

Georgia Perakis is the John C Head III Interim Dean of MIT Sloan School of Management and a Professor of Operations Management and Operations Research & Statistics. She has been on MIT Sloan's faculty since 1998, contributing extensively to research in analytics/AI, optimization, and machine learning applications in pricing, supply chains, healthcare, and energy. Recognized as a leading academic, she has won numerous awards, including the INFORMS Fellow and Distinguished MSOM Fellow, along with multiple best paper awards. Perakis has supervised 30 PhD and 59 master's students, fostering lifelong academic relationships. Her administrative roles include co-director of the Operations Research Center and Associate Dean for Social and Ethical Responsibilities of Computing. She currently serves as Editor-in-Chief of M&SOM and has held editorial leadership roles in top journals like Operations Research and Management Science. Her education includes a BS in Mathematics from the University of Athens and advanced degrees in applied mathematics from Brown University. Research Interests : Perakis focuses on solving complex problems at the intersection of optimization and machine learning, with applications in retail promotions, healthcare operations (e.g., emergency department management), and energy systems. Her work emphasizes practical solutions to real-world challenges, leveraging data-driven analytics and prescriptive models. Recent projects include optimizing patient placement in emergency departments and modeling demand for new products in retail. Grants & Awards : Her accolades include the NSF CAREER Award, PECASE Award, and over a dozen best-paper recognitions. Notable contributions include a finalist position in the JD.com Competition (2019) and winning first place for Johnson & Johnson’s demand-prediction work (2018). She has also pioneered methodologies for equitable resource allocation in healthcare. Education & Leadership : Perakis holds leadership roles in interdisciplinary initiatives like the MIT Initiative on the Digital Economy and the Food Supply Chain Analytics and Sensing Initiative. Her teaching excellence is underscored by awards such as the Jamieson Prize and Teacher of the Year (MIT Sloan). She has directed major programs like the MIT Leaders for Global Operations and the Executive MBA program. Labs & Teams : She is affiliated with the Operations Research Center (an interdepartmental PhD program) and collaborates with institutions like UMass Memorial Hospital on healthcare optimization projects. Her work integrates ethics into AI development, emphasizing fairness, bias mitigation, and societal impact.

Tian Liمشاهده پروفایل

استادیار

• Federated Learning
• Distributed Optimization
• Trustworthy Machine Learning
• +۴ مورد دیگر

Tian Li is an Assistant Professor of Computer Science at the University of Chicago. She holds a Ph.D. in Computer Science from Carnegie Mellon University and undergraduate degrees in Computer Science and Economics from Peking University. Her research focuses on distributed optimization, federated learning, and trustworthy machine learning, emphasizing algorithm design that addresses accuracy, scalability, and privacy concerns in practical systems. Key areas of expertise include federated learning systems, privacy-preserving technologies, and scalable distributed algorithms. She has contributed to foundational work on tilted empirical risk minimization and decentralized knowledge propagation. Notable achievements include winning the Best Paper Award at the ICLR Workshop on Secure Machine Learning Systems and First Place in the U.S. Privacy-Enhancing Technologies Pandemic Challenge (2023). Her academic trajectory includes recognition as a Rising Star in Machine Learning/Data Science and participation in prestigious workshops like the EECS Rising Stars Program. Her work bridges theoretical advancements with practical applications, aiming to enhance both the robustness and accessibility of machine learning systems.

Wenhu Chenمشاهده پروفایل

استادیار

• Natural Language Processing
• Deep Learning
• Multimodal Learning
• +۵ مورد دیگر

Wenhu Chen is an Assistant Professor at the University of Waterloo's Computer Science Department and a CIFAR AI Chair at the Vector Institute. He also holds a part-time role as a Senior Research Scientist at Google DeepMind (20% allocation). His research focuses on natural language processing, deep learning, and multimodal reasoning, with contributions to models like MAmmoTH, OpenCoderInterpreter, and VISTA. He received awards including the Canada CIFAR AI Chair (2022) and the UCSB CS Outstanding Dissertation Award (2021). Education: PhD in Computer Science from the University of California, Santa Barbara (under William Wang and Xifeng Yan). Research interests include complex reasoning, controllable GenAI, and multimodal benchmarks like MEGABench and MMMU. Grants include CIFAR AI Chair Funding (2022-2027), NSERC Discovery Fund (2023-2028), and multiple NRC Canada grants. He directs the TIGER Lab, advancing generative models in text, images, videos, and music. Recent talks include presentations on multimodal reasoning at Apple and NeurIPS workshops.

Gene Tsudikمشاهده پروفایل

استاد

• Computer and network security
• Cryptopoetry
• Internet security and privacy
• +۲ مورد دیگر

Gene Tsudik is a Distinguished Professor of Computer Science at the University of California, Irvine (UCI), with a career spanning over two decades. He obtained his Ph.D. in Computer Science from the University of Southern California (USC) in 1991, focusing on access control in the Internet. His research spans multiple areas including computer and network security, applied cryptography, and digital privacy, with a recent emphasis on database privacy, genomic privacy, and usable security. His notable contributions include the Inter-Domain Policy Routing (IDPR) protocol, KryptoKnight for network security, and Tree-Based Group Key Agreement protocols. He has over 210 publications and 8 patents. From 2002 to 2007, he served as Associate Dean of Research and Graduate Studies at UCI's School of Information and Computer Sciences and currently directs the UCI Secure Computing and Networking Center (SCONCE). Research Keywords : Cybersecurity, Cryptography, Privacy, Network Security, Digital Signatures, Genomic Data Protection. Scientific Awards : IEEE Fellow (2012), ACM Fellow (2014), AAAS Fellow (2016), Fulbright Senior Scholar (2007), and IFIP Fellow (2020). Professor Tsudik has supervised 18 PhD students and held visiting positions at universities across Europe and Asia. His recent publications focus on secure hardware attestation, biometric authentication, and social media data privacy.

Yannis Chronisمشاهده پروفایل

استادیار

• Database Systems
• Hardware-Software Co-design
• Data Processing Efficiency
• +۳ مورد دیگر

Yannis Chronis is an incoming Assistant Professor at the Department of Computer Science , ETH Zurich (starting August 2025), where he will join the ETH Systems Group . Prior to this, he spent 3 years as a Systems Researcher at Google's Systems Research Group in Sunnyvale, USA. He holds a Ph.D. in Computer Science from the University of Wisconsin-Madison (advised by Prof. Jignesh Patel) and a Bachelor's/Master's from the University of Athens, Greece (advised by Prof. Yannis Ioannidis). His research focuses on optimizing databases and data processing for modern hardware through software-hardware co-design. Key areas include database efficiency in memory-centric architectures, learned query optimizers, and cloud resource management. His work is supported by a Facebook Fellowship and has been recognized with the EDBT 2016 Medal for best paper. Teaching: Taught CS 564 - Database Management Systems at UW-Madison (Spring 2022). Service: Served on program committees for SIGMOD, VLDB, CIDR, and others, and chairs the CIDR Proceedings Committee. Key Publications: His recent work includes studies on memory-centric computing for databases, cardinality estimation benchmarks, and adaptive query processing techniques.

Robert Pilawa-Podgurskiمشاهده پروفایل

استاد

• Power Electronics
• Renewable Energy Applications
• Electric Vehicles
• +۴ مورد دیگر

Robert Pilawa-Podgurski is a Professor in the Electrical Engineering and Computer Sciences Department at UC Berkeley and founding director of the Berkeley Power and Energy Center (BPEC). He earned BS, MEng, and PhD degrees from MIT. His research focuses on power electronics, including renewable energy systems, electric vehicles, and high-efficiency power converters. He has received prestigious awards such as the IEEE Fellow (2024), Bakar Fellows Spark Award (2024), and the IEEE Richard M. Bass Outstanding Young Power Electronics Engineer Award (2014). His work emphasizes experimental validation through hardware prototypes. Education: BS in Physics and EECS (MIT, 2005), MEng (MIT, 2007), PhD in EECS (MIT, 2012). Research interests include power electronics for renewable energy, electric vehicles, energy harvesting, and advanced converter topologies. His lab has developed high-power density converters and innovative control techniques for flying capacitor multilevel converters. Recent publications focus on hybrid switched-capacitor architectures, voltage balancing, and ultra-high-current applications. Awards include over 17 IEEE prize papers and teaching accolades like the 2023 UC Berkeley EECS Outstanding Teaching Award. His group has advised numerous students, including postdocs and PhD candidates working on cutting-edge power electronics projects. Labs/Teams: Pilawa Research Group at UC Berkeley, collaborating on power electronics for clean energy and high-performance computing.

Goran Mashanovichمشاهده پروفایل

استاد

• Silicon Photonics
• Photonics Integrated Circuits
• Sensors
• +۲ مورد دیگر

Professor Goran Mashanovich is a leading academic in silicon photonics at the University of Southampton's Optoelectronics Research Centre (ORC) , Faculty of Engineering and Physical Sciences. With a Dipl. Ing. and MSc from the University of Belgrade and a PhD from the University of Surrey, he serves as head of the ORC's Mid-IR silicon photonics group. His expertise spans passive and active photonic devices in silicon and germanium for communication and sensing systems. Education: Dipl. Ing. in Optoelectronics, University of Belgrade MSc in Optoelectronics, University of Belgrade PhD in Silicon Photonics, University of Surrey MSc in Innovative Teaching, University of Surrey His research focuses on Silicon Photonics , Photonics Integrated Circuits , and Sensor Development , particularly in mid-infrared applications. His recent publications demonstrate advancements in waveguide engineering, perovskite integration, and nonlinear optical effects optimization through computational methods. As Principal Investigator on grants exceeding £20 million from EPSRC and industry partners, his collaborative projects include MISSION (mid-infrared healthcare sensors), CORNERSTONE 2.5 , and PIXEurope . He also contributes to global education initiatives as a visiting professor at the University of Belgrade's Faculty of Electrical Engineering.

James Bremerمشاهده پروفایل

استاد

• Numerical Analysis
• Acoustic and Electromagnetic Scattering Problems
• Integral Equation Methods
• +۵ مورد دیگر

James Bremer is a Professor in the Department of Mathematics and holds a cross-appointment in the Department of Computer and Mathematical Sciences at the University of Toronto's Scarborough campus. His research focuses on developing efficient numerical algorithms for solving elliptic boundary value problems, integral equations, and special function transforms.

Chaitanya Swamyمشاهده پروفایل

استاد

• Combinatorial Optimization
• Approximation Algorithms
• Algorithmic Game Theory
• +۴ مورد دیگر

Chaitanya Swamy is a Professor and University Research Chair in the Department of Combinatorics & Optimization at the University of Waterloo, Canada. His primary affiliation is within the Faculty of Mathematics, and he holds positions in both the Department of Combinatorics & Optimization and the School of Computer Science. He obtained his Ph.D. in Computer Science from Cornell University under the supervision of David Shmoys, followed by postdoctoral research at Caltech's Center for the Mathematics of Information. Swamy’s research focuses on algorithms, particularly in combinatorial optimization, approximation algorithms, algorithmic game theory, stochastic optimization, network design, scheduling, and online algorithms. His work spans theoretical contributions and practical applications, including algorithm design for facility location, network routing, and mechanism design. He has contributed to foundational results in approximation algorithms, such as the development of primal-dual methods and LP-rounding techniques. Swamy has held significant editorial roles, including as an associate editor for Discrete Optimization and SIAM Journal on Computing . He has organized major conferences like CanaDAM 2021 and sessions at ISMP 2018. His teaching record includes courses on combinatorial optimization, scheduling, and algorithmic game theory. He has advised numerous Ph.D. and Master’s students, many of whom have gone on to prestigious academic and industry positions. Swamy’s research has been recognized through awards for his students, including the University of Waterloo Alumni Gold Medal. He actively contributes to the academic community through committee work for conferences like STOC, APPROX, and SODA, and his publications reflect a deep engagement with both theoretical and applied aspects of algorithms and optimization.

Yuvraj Agarwalمشاهده پروفایل

استاد

• Systems
• Embedded Systems
• Security
• +۷ مورد دیگر

Yuvraj Agarwal is a Professor in the School of Computer Science at Carnegie Mellon University , where he leads the SYNERGY Labs . His research focuses on Systems and Networking with emphasis on Embedded Systems , Security , and Energy Efficiency in computing environments. He has been recognized with the NSF Expeditions in Computing Award for Computational Decarbonization research and multiple best paper awards. Education : PhD in Computer Science from University of California, San Diego Research Leadership : Founder/Director of SYNERGY Labs; Executive Director of NSF Expeditions in Variability (2010-2013) Research Trajectory : Recent publications highlight his work on Privacy-preserving smart classroom systems (EduSense, ClassID) IoT security labeling frameworks Audio privacy protection mechanisms Computational decarbonization of infrastructure His research combines hardware-software co-design with societal impact considerations. Scientific Recognition : NSF Expeditions in Computing Award for CoDec (2024) Ubicomp/IMWUT Distinguished Paper Award (2024) CHI Best Paper Honorable Mention (2022) Advising & Collaboration : Mentors students in IoT systems , privacy research , and green computing . Collaborates with institutions including University of Massachusetts Amherst and industry partners like Johnson Controls. Grants include NSF funding for multi-university research initiatives.

Peter Pietzuchمشاهده پروفایل

استاد

• Distributed Systems
• Cloud Computing
• Big Data Processing
• +۵ مورد دیگر

Peter Pietzuch is a Professor in the Department of Computing at Imperial College London, where he leads the Large-Scale Data & Systems (LSDS) group. He also serves as the Director of Research and is a Visiting Researcher at Microsoft Research Cambridge. Pietzuch holds a Ph.D. from the University of Cambridge and a B.A. from Girton College. His research spans distributed systems, cloud computing, big data processing, and systems security. Key interests include: Scalable architectures for cloud-native applications Efficient stream processing and machine learning systems Trusted execution environments and secure cloud infrastructure Optimization of serverless computing and distributed databases His recent publications focus on adaptive machine learning frameworks, secure cloud resource management, and high-performance stream processing systems. Trends show strong emphasis on hardware-software co-design, confidential computing, and fault-tolerant architectures. Awards include: Best Paper Award at Middleware'03 He actively advises PhD students and secures grants for projects like Faasm (serverless computing) and Teechain (blockchain security). His LSDS group collaborates with industry partners including Microsoft Research. Pietzuch teaches undergraduate and graduate courses including Scalable Systems for the Cloud and Operating Systems . He co-founded the ACM DEBS conference and serves on steering committees for EuroSys and Middleware.

Benedikt Bünzمشاهده پروفایل

استادیار

• Applied Cryptography
• Blockchain Technology
• Consensus Algorithms
• +۴ مورد دیگر

Benedikt Bünz is an Assistant Professor of Computer Science at New York University's Courant Institute of Mathematical Sciences. He is also a co-founder and chief scientist of Espresso Systems, where he applies his research expertise to real-world blockchain solutions. His academic work bridges theoretical cryptography with practical blockchain implementations, focusing on enhancing privacy, security, and usability of decentralized systems. Dr. Bünz's research centers around applied cryptography, consensus mechanisms, and game theory as they relate to cryptocurrencies. His work spans zero-knowledge proofs, verifiable delay functions, secure multi-party computation, and privacy-preserving protocols. He has made significant contributions to Bulletproofs, a zero-knowledge proof system deployed on blockchains like Monero, and pioneered research in verifiable delay functions which are now part of Ethereum 2.0's design. His recent work focuses on recursive proof systems, accumulation schemes, and efficient verification techniques for blockchain scalability. His publication record shows a consistent progression from foundational cryptographic primitives to practical blockchain implementations. Recent work demonstrates increasing sophistication in recursive proof systems (ProtoStar, HyperPlonk), novel accumulation techniques (ARC, DewTwo), and foundational work on randomness generation (VDFs). His research consistently bridges theoretical cryptography with real-world blockchain applications, resulting in protocols that are both theoretically sound and practically implementable across multiple blockchain platforms. Dr. Bünz actively contributes to the academic community through teaching and mentorship. He teaches courses on cryptography of blockchains and computer security at NYU, providing students with hands-on experience in blockchain security and cryptographic protocols. His industry engagement through Espresso Systems demonstrates his commitment to translating academic research into practical solutions for the blockchain ecosystem.

• Embedded Machine Learning
• High-Performance Computing
• Computer Architecture
• +۶ مورد دیگر

Holger Fröning is a full professor at Heidelberg University’s Institute of Computer Engineering (ZITI), where he leads the Hardware and Artificial Intelligence (HAWAII) Lab. His research focuses on embedded machine learning , high-performance computing , and hardware-software co-design , with emphasis on resource efficiency, power optimization, and emerging architectures like analog , photonic , and resistive memory systems. He has held leadership roles including Managing Director of ZITI (2023–present) and Dean of Studies for Computer Science (2019–2022) , and has collaborated with institutions such as NVIDIA Research, Chinese Academy of Sciences, and Graz University of Technology. Research Trends : His recent publications explore Bayesian neural networks , green machine learning , analog computing noise mitigation , and GPU/FPGA optimization . Articles highlight photonic computing for AI , memory-efficient training , and hardware-aware DNN compression . Scientific Awards : 2025 HiPEAC Paper Award (Nature Computational Science) 2014 Google Faculty Research Award Multiple Best Paper Awards (IPDPS, ICPP, ECML-PKDD workshops) Leadership & Service : Organized workshops (WEML, ITEM, F4HD), chaired tracks at EuroPar and ISC, and served on program committees for ICPR, ECAI, and FPL. Education & Affiliations : PhD and MSc from University of Mannheim (2007/2001). Sponsors include DFG, FWF, FFG, NVIDIA, SAP, and XILINX.

Fred B. Schneiderمشاهده پروفایل

استاد

• Trustworthy Systems
• Fault-Tolerant Distributed Systems
• System Security
• +۶ مورد دیگر

Fred B. Schneider is the Samuel B. Eckert Professor of Computer Science at Cornell University , where he has been a faculty member since 1978. His career spans foundational work in trustworthy systems , fault-tolerant distributed systems , and system security . He served as department chair from 2014–2018 and previously earned a B.S. in Engineering from Cornell (1975) and a Ph.D. in Computer Science from Stony Brook University (1978).