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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.

Kai Lin OngView profile

Assistant Professor

• Algebra
• Coding Theory
• Quantum Error-Correction
• +7 more

Kai Lin Ong is an Assistant Professor at the School of Mathematical & Computer Sciences, Heriot-Watt University, United Kingdom. He is actively engaged in teaching, research, and student development, with a focus on algebra and its applications in quantum computing and coding theory. He currently coordinates first-year programs and mentors students through various academic and personal development initiatives. First Year Coordinator of Studies (2021–present) Maths Gym Coordinator (2020–present) EmPOWER Champion and Impact Coach (2020–present) Student Societies Liaison (2020–2022) His research centers on algebraic structures such as idempotents, zero-divisors, and cyclotomic cosets, applied to quantum error-correcting codes and stabilizer code construction. He utilizes abstract algebra to develop robust coding mechanisms for quantum computing systems, with a strong emphasis on theoretical and practical applications in information processing. The recent publications reflect a consistent trend in quantum information science, particularly in algebraic coding theory. His work bridges pure mathematics with quantum computing, focusing on stabilizer codes, burst error correction, and structural analysis of ring-based codes. The integration of classical algebraic concepts into quantum frameworks highlights a deep interdisciplinary approach combining mathematics, computer science, and physics. Scientific Awards: HWU Teaching Excellence Award 2021 - Global Teaching Team Dr. Ong is actively involved in educational innovation, having led workshops and presentations on globally connected learning, student feedback systems like Gradescope, and sustainable communities in linear algebra education. He advises PhD students and contributes to curriculum development and academic governance through boards of studies and SSLC meetings. His educational philosophy emphasizes resilience, collaboration, and global engagement in learning. He is involved in multiple academic activities including oral presentations at workshops and seminars, promoting teaching excellence and student-centered learning. His initiatives like Maths Gym and EmPOWER support student success beyond the classroom, fostering holistic development.

Sylvester James Gates Jr.View profile

Professor

• Supersymmetry
• Supergravity
• String Theory
• +3 more

Sylvester James Gates Jr. is a distinguished theoretical physicist and academic, holding the Clark Leadership Chair in Science at the University of Maryland. He is also a Distinguished University Professor and Regents Professor in the Department of Physics. His research focuses on supersymmetry, supergravity, and string theory, with notable contributions including co-authoring Superspace: One Thousand and One Lessons in Supersymmetry . Dr. Gates earned BS degrees in physics and mathematics, and a PhD in physics from MIT. He has served on prestigious boards such as the U.S. President’s Council of Advisors on Science and Technology (PCAST) and the National Commission on Forensic Science. Among his accolades are the National Medal of Science and membership in the National Academy of Sciences. He advocates for STEM education and has led initiatives to promote diversity in physics. His work on Adinkra symbols bridges theoretical physics and mathematics, exploring foundational codes underlying reality.

Agis IliadisView profile

Professor

• Nanotechnology
• Semiconductor Devices
• CMOS IC Technology
• +5 more

Agis Iliadis is a Professor of Electrical and Computer Engineering at the University of Maryland, College Park, and Director of the Semiconductor Nanotechnology Research Laboratory. He holds affiliations with the Maryland NanoCenter and serves as a Senior Member of IEEE, Distinguished Lecturer in IEEE-EDS, and on multiple technical committees. His research focuses on nanotechnology, semiconductor devices, CMOS IC technology, wide band-gap semiconductors (e.g., ZnO, SiC), sensors, and electromagnetic interference (EMI) mitigation. Key contributions include self-assembled nanostructures, Schottky contacts, and nanocomposite materials integrated with CMOS processes. Education: Ph.D. and M.Sc. in Electrical Engineering from UMIST (UK). Research Labs: Semiconductor Nanotechnology Research Laboratory. Notable Awards: R.F. Bunshah Award (2004), Best Paper Award for biosensor research (2006), and multiple IEEE recognitions. Research Interests: Elemental/compound semiconductors, light-emitting processes, ohmic/schottky metallization, epitaxial growth. Recent work includes CMOS-compatible nanosensors, GaN betavoltaic devices, and quantum dot noise analysis. Publications: Over 100 peer-reviewed articles in journals like IEEE Trans. Electromagnetic Compatibility , Journal of Applied Physics , and Biosensors and Bioelectronics . Recent trends emphasize RF sensor design, EMI effects on CMOS circuits, and biofilm monitoring via SAW sensors. Grants & Outreach: Organized international conferences (e.g., ISDRS 2001, 2016), advised graduate students on nanotechnology and semiconductor topics, and contributed to MERIT projects on optical communication systems. Labs/Teams: Leads interdisciplinary teams in microelectronics, collaborating with institutions like SPIE and ECS. Active in industry partnerships for sensor and energy-harvesting applications.

Zachary TatlockView profile

Associate Professor

• Programming Languages
• Formal Verification
• Compiler Design
• +4 more

Zachary Tatlock is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering , University of Washington , with a focus on Programming Languages . His research spans formal verification , compiler design , floating-point accuracy , and machine learning frameworks , unified by themes of making tricky code easier to write and ensuring correctness through rigorous proofs and empirical systems. His recent work includes unifying Datalog and equality saturation (PLDI 2023), exploring LLM-driven document markup (Programming with AI 2024), and advancing floating-point error analysis via interactive tools like Odyssey (UIST 2023). He leads the UW PLSE research group and co-organizes events like EGRAPHS and FPTalks . Key collaborations include verifying distributed systems in CakeML (ECOOP 2022) and developing egglog , an e-graph library with relational extensions (PLDI 2023). His teaching includes Solver-Aided Programming (CSE 507) and Grad PL (CSE 505), emphasizing both Greek (formalism) and graphs (empiricism) .

Pierre-Marie PédrotView profile

Researcher

• Type Theory
• Programming Languages
• Theoretical Computer Science
• +3 more

Pierre-Marie Pédrot is a researcher affiliated with INRIA, specializing in type theory and programming languages. His work bridges theoretical computer science with practical proof assistant development. Involvement in major conferences: POPL, CPP, ICFP, CoqPL, LAFI. Committee member for CPP and WITS program committees. Research Interests: Focus on type systems, differentiable programming, and formal verification. His contributions include advancements in dependent types, effect handling, and Coq-based tools. Recent Publications: Explores intersections of type theory, differentiable programming, and proof assistant automation. Notable works on sort polymorphism, Martin-Löf type theory implementations, and OCaml extraction correctness. 2025: Sort Polymorphism for Proof Assistants 2024: Martin-Löf à la Coq 2023: Dialectica Differentiable Typing

• Machine Learning
• Wireless Communications
• Federated Learning
• +4 more

Mohammad Mohammadi Amiri is an Assistant Professor in the Computer Science Department at Rensselaer Polytechnic Institute (RPI), joining in Fall 2023. Previously, he held postdoctoral positions at MIT Media Lab (2022–present) and Princeton University (2019–2021), working with Prof. Vincent Poor and Prof. Sanjeev Kulkarni. He earned his Ph.D. in Electrical and Electronic Engineering from Imperial College London (2019), with prior degrees from Iran University of Science and Technology (B.Sc., 2011) and the University of Tehran (M.Sc., 2014). His research focuses on decentralized intelligence, federated learning, and wireless edge computing. He explores enabling distributed machine learning while preserving privacy, particularly in IoT and smart systems. Key areas include federated learning over wireless channels, data valuation, and optimization of edge computing resources. His articles address topics like federated learning convergence, device selection in wireless systems, and decentralized data valuation. Recent work includes papers accepted at AAAI 2023, CISS 2023, and IEEE Transactions on Wireless Communications. Awards : IEEE Communications Society Young Author Best Paper Award (2022) Best PhD Thesis Award (2019), IEEE Information Theory Chapter Eryl Cadwallader Davies Prize (2019), Imperial College London Advising & Grants : Mentoring Ph.D. students in machine learning and distributed systems Recipient of multiple scholarships and awards during his academic career Labs/Teams : Camera Culture Group (MIT Media Lab) Princeton University's Electrical Engineering Department

Anouar YatribiView profile

Research Fellow

• Coding and Information Theory
• Error Correcting Codes
• Wireless Communication Systems
• +5 more

Anouar Yatribi is a Postdoctoral Research Associate at Imperial College London's Department of Electrical and Electronic Engineering within the Information Processing and Communications Lab. He holds a PhD from ENSIAS, Mohammed V University (Morocco, 2021), and prior degrees in Physics (BSc, 2011) and Electrical Engineering (MSc, 2013) from Mohammed V University. His research focuses on Coding Theory, Error Correcting Codes, and their applications in wireless communications and DNA data storage, alongside discrete mathematics and optimization algorithms. His academic contributions include pioneering work on iterative decoding techniques, majority-logic decodable codes, and hybrid ARQ protocols. He has authored/co-authored over a dozen peer-reviewed publications in IEEE journals and conferences, with notable work on DNA storage error correction and LDPC code optimization. Yatribi serves as a reviewer for IEEE Access and the American Journal of Networks and Communications. Research trends in his publications emphasize improving code performance through algorithmic innovations (e.g., genetic algorithms for code construction) and exploring novel applications like non-binary codes and finite geometry-based coding. His work bridges theoretical coding advancements with practical implementations in real-world communication systems. Yatribi's professional activities include lab leadership within the Information Processing group and active participation in international conferences (e.g., WINCOM, WCCCS). His lab focuses on advancing communication systems through interdisciplinary approaches combining coding theory, optimization, and machine learning.

• Semantic Communication
• Resource Allocation Mechanisms
• 6G Networks
• +3 more

Alexander Griessel is a Researcher and PhD candidate at the Chair of Communication Networks (Prof. Wolfgang Kellerer) at the Technical University of Munich (TUM). He holds a B.Sc. (June 2020) and M.Sc. (December 2021) in Electrical and Computer Engineering from TUM. His research focuses on Resource Allocation Mechanisms in Semantic Communication , particularly addressing resilience and efficiency in 6G channels. He contributes to the Semantic Communication project and serves as a teaching associate for the Internet Kommunikation course. His work spans semantic resilience strategies , real-time video/image communication , and 6G network design . Recent research includes lossy coding techniques for semantic images, adaptive systems for challenging 6G environments, and non-invasive sensor solutions for infrastructure monitoring. His publications also explore cybersecurity (website fingerprinting) and reinforcement learning for network trace generation. Alexander actively supervises master's theses on topics like semantic symbol prioritization and reliability analysis in 5G/6G channels. He collaborates on TUM's 6G testbed initiatives and contributes to the 6G-life and Flexibility research networks. His interdisciplinary approach bridges communication theory with practical network implementations.

• Coding Theory
• Distributed Storage Systems
• Matroid Theory
• +3 more

Thomas Westerbäck is a Senior Lecturer at Mälardalen University, affiliated with the School of Education, Culture and Communication and the Division of Mathematics and Physics. His research focuses on coding theory, distributed storage systems, matroid theory, combinatorics, information theory, and algebraic coding. He has contributed to advancements in locally repairable codes, matroid structures in storage systems, and applications of combinatorial methods in coding. His publications highlight theoretical bounds, code constructions, and practical implementations in storage efficiency and error resilience. Key research themes include matroid minors in coding, alphabet-dependent code bounds, and polymatroidal frameworks for heterogeneous storage systems. His work bridges abstract mathematical concepts (e.g., Möbius inversion in lattices) with applied coding challenges in distributed environments. Publications span topics from binary matroid flats to exact regenerating codes, demonstrating a blend of theoretical depth and practical storage solutions. His research emphasizes resilience against data erasures and optimizing storage efficiency through combinatorial and algebraic innovations.

• Cloud Computing
• Distributed Systems
• High-Performance Computing
• +5 more

Raja Appuswamy is an Assistant Professor in the Department of Data Science at EURECOM, focusing on data management on modern hardware and molecular information storage. His research integrates cutting-edge storage technologies with bioinformatics, particularly in DNA-based data storage. He teaches courses in cloud computing, distributed systems, and databases. His work spans Optimizing storage hierarchies with DNA archival systems Hardware-conscious algorithms for GPUs and heterogeneous architectures Error correction in molecular storage Long-term database preservation strategies Key research interests include Cross-architecture data joins (e.g., OneJoin, XJoin) Cold storage innovation with CMOSS and OligoArchive Integration of bio-inspired storage with traditional computing and explores interdisciplinary challenges at the intersection of computer science and molecular biology. Publications emphasize scalable solutions for DNA storage density, error tolerance, and archival systems. Awards highlight contributions to DNA-based image encoding, storage reliability, and page cache checksums. Current projects focus on enzymatic DNA ligations for storage density improvement, motif-based error correction, and hardware acceleration for knowledge graphs. His work targets both theoretical advancements and practical implementations in storage systems.

Caleb ShorView profile

Professor

• Numerical Semigroups
• Algebraic Geometry
• Number Theory
• +1 more

Caleb Shor is a Professor in the Department of Mathematics at Western New England University, where he has taught since 2008. He also serves as director of the PROMYS for Teachers program at Boston University. His academic journey includes a Ph.D. in Mathematics from Boston University (2005) and a B.S. in Mathematics from Bates College (2000). Dr. Shor's educational background includes: Ph.D. in Mathematics, Boston University, 2005 B.S. in Mathematics, Bates College, 2000 Semester Abroad, Budapest Semesters in Mathematics, Technical University of Budapest, Spring, 1999 His dissertation was titled "On towers of function fields and the construction of the corresponding Goppa codes," advised by Dr. Emma Previato. Dr. Shor's primary research interests span multiple areas of pure mathematics with a focus on Numerical Semigroups , Algebraic Geometry , Number Theory , and Coding Theory . His work often bridges theoretical mathematics with applications in coding theory, particularly exploring connections between algebraic structures and error-correcting codes. A significant portion of his research examines properties of numerical semigroups, including their gaps, generators, and complementary structures, while his work in algebraic geometry frequently centers on superelliptic curves and Weierstrass points. Analysis of Dr. Shor's publication record reveals a consistent focus on numerical semigroup theory and algebraic geometry, with increasing attention to connections with coding theory in recent years. His most recent work (2022-2024) has explored equidistribution properties of numerical semigroup gaps and residues of shifted fractions, demonstrating the continued evolution of his research program while maintaining connections to his foundational work in semigroup theory. Dr. Shor has extensive teaching experience, having taught undergraduate courses including Introduction to Statistics, Calculus series, Differential Equations, Engineering Analysis, Linear Algebra, Modern Algebra, Complex Analysis, and Number Theory. At the graduate level, he teaches Calculus Revisited, Linear Algebra, and Number Theory in the MAMT program. He has advised numerous senior projects in mathematics, particularly in number theory, algebraic geometry, abstract algebra, numerical semigroups, and combinatorics.

• Probability
• Information Theory
• Combinatorics
• +9 more

Dr Matthew Aldridge is a Lecturer in the School of Mathematics at the University of Leeds, affiliated with the Statistics department. He holds a PhD in Mathematics from the University of Bristol (2011) and earned his MMath and BA in Mathematics from the University of Cambridge. PhD Mathematics, University of Bristol, 2011 Part III Mathematics (MMath), University of Cambridge, 2007 BA (Hons) Mathematics, University of Cambridge, 2006 His research lies at the intersection of probability, information theory, combinatorics, and statistics, with a strong focus on group testing —a method for efficiently identifying rare positives in large populations, widely applied during the COVID-19 pandemic. He also investigates interference in multiuser communication systems and develops discrete analogues of continuous probability concepts. His current PhD projects include Pooled testing to prevent the next pandemic and Genuinely discrete discrete probability . His recent publications center on group testing from both practical and theoretical angles, including survey papers co-authored with David Ellis and with Oliver Johnson and Jonathan Scarlett. These works explore applications in public health, communications, and genetics, and are grounded in information theory and statistical inference. Dr Aldridge teaches MATH5835M Statistical Computing, covering Monte Carlo estimation, variance reduction techniques (control variates, antithetic variables, importance sampling), random number generation, Markov Chain Monte Carlo (MCMC), and bootstrap methods. He emphasizes practical implementation using R and provides detailed lecture notes and problem sheets. He is actively engaged in research supervision and welcomes PhD applicants. His academic presence includes profiles on arXiv , Google Scholar , and ORCID (0000-0002-9347-1586) .

• Mobile and Wireless Communications
• Satellite Communications
• Underwater Communications
• +7 more

Professor Jinhong Yuan is a distinguished academic serving as Professor of Telecommunications and Head of Telecommunications at the School of Electrical Engineering and Telecommunications, University of New South Wales (UNSW), Sydney, Australia. He received his B.E. and Ph.D. degrees in Electronics Engineering in 1991 and 1997, respectively. After serving as a Research Fellow at the University of Sydney from 1997 to 1999, he joined UNSW in 2000 where he has continued his academic career. Professor Yuan's extensive research portfolio spans multiple cutting-edge areas in telecommunications, with particular expertise in Mobile and Wireless Communications, Satellite Communications, Underwater Communications, and Integrated Communications and Sensing (ICAS). His work addresses critical challenges in IoT, Millimeter Waves, Information Theory and Error Control Coding, Turbo Coding and Iterative Processing, as well as Space-Time Coding, Processing and MIMO Techniques. His recent publications demonstrate significant contributions to Wideband CDMA, OFDM, and particularly to Orthogonal Time Frequency Space (OTFS) modulation systems which have emerged as promising technologies for 5G/6G communications and high-mobility scenarios. Analysis of Professor Yuan's recent publications reveals a strong trend toward addressing the challenges of high-mobility communications, particularly through OTFS modulation techniques. His work spans theoretical foundations in channel coding and information theory to practical implementations in satellite, underwater, and terrestrial wireless systems. The research demonstrates increasing integration of communications and sensing capabilities, reflecting the growing importance of Integrated Sensing and Communications (ISAC) in next-generation wireless networks. His publications consistently appear in top IEEE journals including IEEE Transactions on Communications and IEEE Transactions on Wireless Communications. Best Paper Award of IEEE Wireless Communications and Networking Conference (WCNC), Cancun, Mexico (2011) Best Paper Award of IEEE International Symposium on Wireless Communications Systems (ISWCS), Trondheim, Norway (2007) Four additional Best Paper Awards across various conferences One Best Poster Award Professor Yuan serves as the IEEE NSW Chair of the joint Communications/Signal Processing/Ocean Engineering Chapter and holds editorial positions as Associate Editor for both IEEE Transactions on Communications and IEEE Transactions on Wireless Communications. His research has resulted in over 300 journal and conference publications, two books, two book chapters, and 40 industrial reports. He is also a co-inventor of one patent on MIMO systems and two patents on low-density-parity-check (LDPC) codes, demonstrating the practical impact of his theoretical work.

Laurence HurstView profile

Professor

• Genetics
• Evolutionary Biology
• Molecular Biology
• +2 more

Laurence Hurst is a Professor in the Department of Life Sciences at the University of Bath , where he leads research at the Milner Centre for Evolution and Centre for Mathematical Biology . His work bridges mathematical, bioinformatic, and experimental approaches to evolutionary genetics. Research Focus : Selection on synonymous mutations, gene order evolution, genomic redundancy, codon usage bias, and long non-coding RNA dynamics. Key Collaborations : Projects funded by The Evolution Education Trust, The Royal Society, MRC, and Biotechnology and Biological Sciences Research Council (BBSRC). Methodologies : Integrates systems biology, computational genomics, and experimental validation. SDG Contributions : Work indirectly supports UN Sustainable Development Goals through advancing genetic understanding for health and environmental applications. Notable Trends in Publications : Recent articles examine protein evolution mechanisms, retroviral co-option in human embryogenesis, transgene design optimization, and bacterial adaptation via epistasis. These studies highlight interdisciplinary applications of genetics, molecular biology, and computational methods. Laboratory & Affiliations : Affiliated with the Milner Centre for Evolution and Centre for Mathematical Biology, focusing on evolutionary dynamics and genomic systems biology.