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Christopher KruegelView profile

Professor

• Systems Security
• Malware Analysis
• Web Security
• +7 more

Christopher Kruegel is a Professor in the Department of Computer Science at the University of California, Santa Barbara (UCSB), where he conducts research in systems security. He is affiliated with the International Secure Systems Lab (iSecLab) and was a co-founder of Lastline, Inc., which was acquired by VMware in 2020. His work focuses on creating practical security solutions that address real-world problems through system building and experimental validation. Professor Kruegel's research spans multiple areas of computer security including malware analysis, web security, network security, and vulnerability analysis. His work often involves developing systems that analyze programs for malicious behavior, scanning web applications for vulnerabilities, and improving privacy on social networks. He has made significant contributions to firmware security, smart contract analysis, and mobile security through his extensive publication record. His 15 most recent publications (2022-2023) demonstrate a strong focus on practical security solutions across diverse domains including firmware security (Shimware, Fuzzware), blockchain and smart contract security (Confusum Contractum, NFT security), mobile security (TEEzz, Columbus), and vulnerability detection techniques (Actor, Toss a Fault to Your Witcher). His research shows consistent innovation in security tools and methodologies with several papers receiving distinguished awards. Fellow of the Institute of Electrical and Electronics Engineers Outstanding Graduate Mentor Award, UCSB Academic Senate Distinguished Artifact Award for Fuzzware paper Distinguished Paper Award for Ramblr paper Best Student Paper Award for Detecting Spammers On Social Networks Professor Kruegel has advised numerous graduate students and collaborated extensively with researchers at UCSB and beyond. His work has been funded by various research grants supporting his security research initiatives. He is actively involved in the International Secure Systems Lab, which focuses on practical security solutions for real-world problems.

• Cloud Computing
• Data Center Optimization
• Resource Allocation
• +4 more

Bhuvan Urgaonkar is a Professor in the Department of Computer Science and Engineering at Penn State University's College of Engineering. His research centers on optimizing cloud computing systems through innovative approaches to resource allocation, cost efficiency, and energy management. Current research focuses on Burstable Instance Scaling Serverless Computing Optimization Distributed Storage Systems Multi-resource Fair Allocation Cloud Economics Recent publications highlight advancements in autoscaling techniques, serverless architecture design, and trace modeling for high-load scenarios. These works emphasize practical solutions for cost-effective resource utilization in public cloud environments. Scientific Awards: CNS: Core: Small: Consistent, Geo-Distributed Data Stores on the Public Cloud (NSF, 2022-2025) CNS Core: Small: Principled Methodologies for Automated Cost-Effective Service Blending (NSF, 2021-2024) PPoSS: Cross-Layer Design for HPC in the Cloud (NSF, 2020-2022) CSR: Burstable Instances for Cost-Efficacy (NSF, 2017-2020) CSR: Student Travel Support for SIGMETRICS (NSF, 2016-2017)

Chris F. KemererView profile

Professor

• Management of Information Systems
• Software Engineering
• Measurement and Modeling
• +2 more

Chris F. Kemerer is the David M. Roderick Professor of Information Systems and Professor of Business Administration at the University of Pittsburgh's Katz School. He previously served as an associate professor at MIT Sloan School of Management and as a principal at American Management Systems Inc. PhD in Systems Sciences (Information Systems), Carnegie Mellon University BS (magna cum laude) in Economics and Decision Sciences, Wharton School, University of Pennsylvania His research spans management and measurement issues in information systems and software engineering, including technical debt, software metrics, network effects, and technology adoption. He has made significant contributions to software design metrics and empirical analysis of IT markets. His publications over the last 15 years emphasize technical debt management, software reliability, standards competition, and economic dynamics in microcomputer software. These works bridge software engineering economics with real-world applications in enterprise systems and global markets. ISI/Thomson Reuters Highly Cited Researcher in Computer Science INFORMS Information Systems Society Distinguished Fellow He has secured grants from the National Science Foundation and IBM for software evolution research. His consulting includes expert testimony in landmark cases like Microsoft antitrust litigation and Oracle v. Google. He has taught courses in economics of information systems, software design, and technology diffusion at the PhD, Executive DBA, MBA, and EMBA levels.

• Communication Theory
• Channel Coding
• Low-Density Parity-Check (LDPC) Codes
• +3 more

Richard D. Wesel is an Associate Dean for Academic and Student Affairs at a College of Engineering, where he has held leadership roles such as Vice-Chair of the Electrical Engineering Department. With Ph.D. and M.S. degrees in Electrical Engineering from Stanford University and MIT respectively, his research focuses on communication theory and channel coding, particularly low-density parity-check (LDPC) codes and turbo codes for efficient data transmission over noisy channels. Education: MIT (B.S., M.S.), Stanford (Ph.D.) Leadership: Associate Dean, Former Vice-Chair of Electrical Engineering Wesel's research explores advanced techniques for broadcast and multiple-access communication systems, emphasizing applications in wireless LANs, satellite communications, and optical networks. His work integrates machine learning with traditional decoding algorithms, as seen in recent publications on neural-network-optimized LDPC decoding and parallel trellis-stage-combining methods for high-throughput systems. His articles demonstrate a focus on finite-blocklength coding, including CRC-aided list decoding for convolutional and polar codes, and voltage optimization strategies for flash memory reliability. Wesel has authored over 100 publications and led a research group that won the 2006 Design Automation Conference's top award for optical multiple access design. Scientific Awards: National Science Foundation CAREER Award Okawa Foundation Award As an educator, Wesel received the TRW Excellence in Teaching Award in 2000 and has contributed to academic governance through roles on the Faculty Executive Committee and Undergraduate Council. His work bridges theoretical communication systems with practical implementations, including FPGA-based decoders and adaptive coding for fading channels.

Farzad FarnoudView profile

Assistant Professor

• Information and Coding Theory
• Machine Learning
• Bioinformatics
• +3 more

Farzad Farnoud is an Assistant Professor in the Electrical and Computer Engineering and Computer Science Departments at the University of Virginia. His research focuses on information theory, coding theory, computational biology, and machine learning, with applications in DNA storage and genomic data analysis. He holds a Ph.D. in Electrical and Computer Engineering from the University of Illinois (2013) and postdoctoral experience at Caltech. Education: B.S. in Electrical Engineering (Sharif University of Technology, 2006) M.S. in ECE (University of Toronto, 2008) M.S. in Mathematics (UIUC, 2012) Ph.D. in ECE (UIUC, 2013) Postdoc at Caltech (2013–2016) His research interests span information-theoretic analysis of biological datasets, coding for DNA storage, stochastic modeling of genomic mutations, and rank aggregation algorithms. Notable contributions include error-correcting codes for duplication channels and frameworks for metagenomic data analysis. Recent work includes studies on short-duplication error correction (2023), active ranking algorithms (2022), and heterogeneous rank aggregation (2020). He has received the Robert T. Chien Memorial Award (2013) and the IEEE Data Storage Best Student Paper Award (2014). Teaching includes courses on computational biology, statistical learning, and graphical models. He leads the Information Processing + Storage Lab, focusing on interdisciplinary challenges in data storage and analysis.

Chen PanView profile

Assistant Professor

• Energy-Harvesting Embedded Systems
• Internet of Things (IoT)
• Low-Power Computing
• +5 more

Chen Pan is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Texas at San Antonio's Klesse College of Engineering and Integrated Design. His research focuses on energy-harvesting embedded systems, low-power computing, and IoT network optimization through machine learning techniques. Ph.D. from University of Pittsburgh Specializes in transient computing for batteryless devices Develops reinforcement learning solutions for UAV-assisted IoT systems Chen's recent publications emphasize energy-aware scheduling, non-volatile memory optimization, and sustainable communication protocols. His work intersects spatiotemporal modeling, fault tolerance, and resource-constrained AI execution across heterogeneous architectures.

Cai KuiView profile

Associate Professor

• Coding Theory
• Communication Systems
• Information Theory
• +3 more

Cai Kui is an Associate Professor at Singapore University of Technology and Design (SUTD) and the Programme Director of the SUTD Technology Entrepreneurship Programme (STEP). Her work focuses on coding theory, communication systems, and data storage technologies. She holds a joint PhD in Electrical Engineering from Technical University of Eindhoven and National University of Singapore, along with prior degrees from Shanghai Jiao Tong University and National University of Singapore. Research interests include advanced channel coding, signal processing for emerging storage systems (e.g., DNA storage, non-volatile memory), and machine learning applications. She leads multiple projects funded by A*STAR, Temasek Labs, and SUTD-MIT collaborations, addressing challenges in high-density storage and communication. Her awards include the 2024 ScholarGPS™ Top 0.05% Scholars, 2023 China Annual Symposium Best Poster, and multiple IEEE recognitions. She is an IEEE Senior Member and has served in leadership roles at IEEE conferences. Current openings include PhD scholarships and postdoc positions in coding for data storage systems. Key labs/teams include her research group focusing on FPGA implementations, DNA storage, and memory systems.

Han Mao KiahView profile

Assistant Professor

• Coding Theory
• Combinatorics
• Information Theory
• +1 more

Han Mao Kiah is an Assistant Professor at Nanyang Technological University , specializing in Coding Theory and Combinatorics . He earned his Ph.D. in Mathematics at NTU under Yeow Meng Chee and held a postdoctoral position at the Coordinated Science Lab, University of Illinois at Urbana-Champagne with Olgica Milenkovic . Current Role: Assistant Professor, NTU, Department of Mathematics Education: Ph.D. in Mathematics (NTU), Postdoc (University of Illinois) His research focuses on Coding Theory for applications in DNA-based data storage , Reed-Solomon codes , and combinatorial designs . Recent work includes Private Information Retrieval , Sequence Reconstruction , and Error Correction in distributed systems. Key trends in his publications involve Reed-Solomon codes , Private Information Retrieval , and DNA sequence profiling with a focus on Efficient Algorithms and Constrained Coding for error control in emerging storage systems. ISITA Early Career Researcher Paper Award (2022, Researcher: D. T. Dao) Memorable Paper Award Finalist (2021, Student: J. Chrisnata) Best Student Paper Award (2020, Student: J. Chrisnata) Student Paper Award Finalist (2012)

Emanuele ViterboView profile

Professor

• Error Control Coding
• Communications
• Lattice Codes
• +5 more

Professor Emanuele Viterbo is a faculty member in the Department of Electrical and Computer Systems Engineering at Monash University, where he has served as Professor since 2010 and Associate Dean (Graduate Research) from 2012 to 2020. His research focuses on error control coding, lattice codes, and algebraic coding theory with applications to wireless communications. He holds a PhD and Laurea in Electrical Engineering from Politecnico di Torino. Key research areas include lattice codes for fading channels, algebraic space-time coding (e.g., Golden Code), and OTFS modulation. He has received prestigious awards such as the IEEE Fellow designation (2011) and the Australia-India Fellowship (2012-13). His work on polar codes and coding for NAND flash memories has advanced practical coding schemes for modern communication systems. Major grants include projects on blockchain coding, high-mobility wireless systems, and NAND flash memory reliability. He has supervised numerous PhD students and contributed to foundational research in information theory. His affiliations include leadership roles in IEEE committees and visiting research positions at institutions worldwide. Scientific achievements include pioneering contributions to space-time coding and lattice-based modulation. Current projects explore OTFS modulation, error control for blockchains, and advanced modulation techniques for 5G/6G networks.

Bella BoseView profile

Professor

• Coding Theory
• Error Control Codes
• Computer Networks
• +3 more

Bella Bose is a Professor in the School of Electrical Engineering and Computer Science (EECS) at Oregon State University, where he has served since 1980 in multiple administrative capacities including associate director of academic affairs, interim school head, and senior associate head of EECS. His educational background includes: B.E. in Electrical Engineering from Madras University, India (1973) M.E. in Electrical Engineering from Indian Institute of Science, Bangalore (1975) M.S. and Ph.D. in Computer Science and Engineering from Southern Methodist University, Dallas, TX (1979 and 1980) Bose's research centers on Coding Theory with pioneering contributions to Error Control Codes , particularly their applications in computer networks and flash memory systems. His foundational work in error correcting codes has evolved to address modern storage challenges, significantly reducing error rates while increasing capacity in flash memory technologies. Additional interests span parallel processing architectures and network system design, reflecting his interdisciplinary approach to solving computational challenges. His distinguished honors include: ACM Fellow (2004) IEEE Fellow (1995) Transactions on Vehicular Technology Jack Neubauer Memorial Award for best systems paper (2009) Southern Methodist University's 40th Anniversary Award for Academic Accomplishment (2008) OSU College of Engineering Research Award (1996) Bose maintains close mentoring relationships with graduate students, with one former advisee remaining a key research collaborator. His international research collaborations span over 40 countries including Italy, Norway, Kuwait, and Saudi Arabia, though specific grant details are not documented in available sources. He actively supports junior faculty development as part of Oregon State's mission to become a top-25 engineering program. He conducts his research through Oregon State's Networking and Computer Systems group, focusing on practical implementations of theoretical coding frameworks for next-generation storage and communication systems.

Chee Yeow MengView profile

Professor

• Coding Theory
• Combinatorics
• Data Science
• +3 more

Chee Yeow Meng is the Provost and Chief Academic & Innovation Officer at the Singapore University of Technology and Design (SUTD), effective April 2025. He holds a Professor rank and oversees curricular, research, and innovation affairs. Previously, he served as Vice President (Innovation and Enterprise) at NUS and held senior roles in academia and public service, including leadership positions at the National Computer Board and Infocomm Development Authority. His education includes a BMath (Hon) and MMath from the University of Waterloo (1988-1989), followed by a PhD in Computer Science (1996). His research focuses on combinatorics' intersection with computer science, particularly coding theory, extremal set systems, and AI applications. He has pioneered work in error-correcting codes, combinatorial cryptography, and data science. Prof Chee is an associate editor for IEEE Transactions on Information Theory and a Fellow of the Institute of Combinatorics and its Applications. His awards include the Public Administration Medal (Silver, 2018) and the Long Service Award (NTU, 2018). He has founded multiple startups and holds patents in coding technologies. His recent publications emphasize innovations in coding theory applications (e.g., domain wall memories, DNA storage) and machine learning for combinatorial optimization. He actively contributes to national committees and international forums on innovation policy and AI ethics.

Tokunbo OgunfunmiView profile

Professor

• Deep Learning
• Artificial Neural Networks
• Adaptive Signal Processing
• +7 more

Tokunbo Ogunfunmi is a Professor of Electrical and Computer Engineering and Director of the Information Processing and Machine Learning (IPML) Research Lab at Santa Clara University's School of Engineering. He served as Associate Dean for Research and Faculty Development from 2010-2014 and as Associate Dean for Mission, Culture and Inclusion from 2021-2024. Dr. Ogunfunmi holds a Ph.D. and M.S. from Stanford University (1990, 1984) and a B.S. from the University of Ife, Nigeria (1980). His research interests span deep learning, artificial neural networks, adaptive/nonlinear signal processing, digital signal processing, and multimedia signal processing with VLSI/DSP/FPGA implementations. Dr. Ogunfunmi has published 4 books and over 200 refereed journal and conference papers in these areas. His recent publications demonstrate strong focus on deep learning applications, hardware acceleration for neural networks, quaternion-based adaptive algorithms, and efficient video/speech processing techniques. Dr. Ogunfunmi has received numerous awards including the SCU Presidential Special Recognition Award (2020), IEEE Meritorious Service Awards (2021, 2013), Carnegie Foundation Visiting Professorships (2019, 2015), and multiple Best Paper Awards. He has served in significant editorial roles including Senior Associate Editor for IEEE Signal Processing Letters and Associate Editor for several IEEE Transactions. As an active member of the professional community, he is a Senior Member of IEEE, Member of Sigma Xi, and Member of AAAS. His industrial experience includes consulting for major companies such as Broadcom, AMD, NEC, AT&T Bell Labs, and NIKON Precision Research & Development. Dr. Ogunfunmi is also a registered professional engineer in California.

• Neuroscience
• Synaptic transmission
• Presynaptic mechanisms
• +7 more

Professor Peter Jonas is a leading neuroscientist at IST Austria, specializing in synaptic transmission mechanisms and their role in neural circuits. He holds the Magdalena Walz Professorship for Life Sciences and leads the Jonas Group, focusing on nanophysiological studies of synapses using advanced techniques like optogenetics and flash-and-freeze electron microscopy. His research bridges biophysical mechanisms with network functions in the hippocampus and cortex. Education & Career: MD, University of Giessen (1987) Professorships at University of Freiburg (1995–2010), Technical University of Munich (1994–1995), and currently at IST Austria since 2010 Research Interests: Synaptic signaling and plasticity at glutamatergic/GABAergic synapses Role of presynaptic calcium channels and vesicle dynamics Neural coding in hippocampal circuits Mechanisms of gamma oscillations via inhibitory interneurons Awards & Honors: ERC Advanced Grants (2010, 2016), Gottfried Wilhelm Leibniz Award (2006) Member of EMBO, Leopoldina Academy, and Academia Europaea Lab & Team: Jonas Group at IST Austria includes postdocs, PhD students, and technical staff Current projects: Mossy fiber synapse plasticity, synaptic ultrastructure, and in vivo network modeling

Chang-Soo KimView profile

Professor

• Micro/Nanofabrication
• Sensor Engineering
• Solid-State Devices
• +4 more

Dr. Chang-Soo Kim is a Professor of Electrical and Computer Engineering at Missouri University of Science and Technology, with a joint appointment in Biological Sciences. He holds a Ph.D. in Sensors Engineering from Kyungpook National University (1997), along with M.S. and B.S. degrees in Semiconductor and Electronic & Electrical Engineering, respectively. Ph.D., Sensors Engineering, Kyungpook National University (1997) M.S., Semiconductor Engineering, Kyungpook National University (1991) B.S., Electronic & Electrical Engineering, Kyungpook National University (1989) His research focuses on solid-state devices , micro/nanofabrication , biomedical sensors , and nanotechnology applications , particularly in developing biodegradable microsystems for medical and environmental uses. Recent work includes wearable MXene-Graphene virus sensors , glass-based pressure monitors , and implantable biopotential recording devices . Scientific contributions span bioinstrumentation , flexible sensors , and optofluidic platforms , with over 100 peer-reviewed publications. Key grants include NASA , NSF , NIH , and USDA funding, including an NSF CAREER award. NSF CAREER Award (2007) School of Engineering Innovative Teaching Award (2006) Claypool Medical Award (2006) As Graduate Coordinator, he mentors students in microfabrication and sensor development . His Intelligent Microsystem Laboratory bridges engineering and biomedical applications, with technologies commercialized through patents.

• Power Electronics
• Power Quality
• Smart Grids
• +3 more

Szymon Barczentewicz, PhD, Eng., serves as a Lecturer at AGH University of Science and Technology within the Department of Power Electronics and Automation of Energy Conversion Systems, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering. His academic position and research activities confirm active faculty status in Poland's leading technical university. Dr. Barczentewicz's research concentrates on Power Electronics , Power Quality , and Smart Grid technologies, with particular expertise in harmonic analysis, islanding detection for distributed generation systems, and voltage fluctuation compensation. His work bridges theoretical development with experimental validation, frequently utilizing phasor measurement units (PMUs), hardware-in-the-loop simulations, and advanced signal processing techniques to address grid stability challenges in renewable-rich environments. Analysis of his 15 most recent publications reveals consistent focus on grid integration challenges: 60% address islanding detection and prevention, 40% cover power quality monitoring (including supraharmonics), and 30% explore data compression for smart grid applications. His 2025-2024 work demonstrates increasing emphasis on AI-enhanced grid management and experimental validation of control systems for renewable integration. Collaboration with industry partner Enea Operator features prominently in his research program, particularly in power quality monitoring and energy balancing projects. As an active member of AGH's Energy Quality Team ( Zespołu Jakości Energii ), he contributes to experimental developmental research and educational initiatives in electrical power delivery systems.