Lijie Chen is an Assistant Professor in the Department of Electrical Engineering and Computer Sciences at UC Berkeley, where he is part of the Berkeley Theory Group. Previously, he was a Miller Research Fellow at UC Berkeley, hosted by Avishay Tal and Umesh Vazirani, and earned his Ph.D. from MIT under Ryan Williams. His research focuses on theoretical computer science, particularly computational complexity theory, with applications to quantum physics and AI safety. Education: Ph.D. in Computer Science from MIT (2022), B.Sc. from Yao Class at Tsinghua University. Research Interests: Complexity theory, quantum complexity, derandomization, circuit lower bounds, and foundational aspects of AI safety. Chen has made significant contributions to understanding fundamental questions in complexity theory, including circuit lower bounds and the connections between randomness and computation efficiency. His work often bridges theoretical insights with practical implications in quantum computing and algorithm design. Awards and Honors: Machtey Award for Best Student Paper (2019). Danny Lewin Best Student Paper Award (2019). Invited to SICOMP Special Issues for FOCS and STOC papers. He has organized workshops on complexity theory and derandomization, and his research has been recognized in venues like STOC, FOCS, and the Journal of the ACM.
Andrew Childs is a Professor at the University of Maryland, affiliated with the Department of Computer Science and the Institute for Advanced Computer Studies (UMIACS). He serves as Director of the NSF Quantum Leap Challenge Institute for Robust Quantum Simulation (RQS) and is a Fellow at the Joint Center for Quantum Information and Computer Science (QuICS). His research focuses on quantum algorithms for simulating physical systems, algebraic problems, and quantum walk protocols, with applications in quantum computing and computational complexity. University of Maryland Institute for Advanced Computer Studies (UMIACS) Joint Center for Quantum Information and Computer Science (QuICS) NSF Quantum Leap Challenge Institute for Robust Quantum Simulation Childs' research spans quantum simulation, quantum Fourier transform, phase estimation, and Hamiltonian dynamics. He has developed techniques to reduce quantum computational resources for simulating quantum systems and explored limitations of quantum computers through hidden subgroup problems and non-unitary dynamics. His publications cover diverse areas including quantum walk optimization, Hamiltonian simulation methods, and applications to cryptography and condensed matter physics. Recent works address spatial search algorithms, product formulas for commutators, and quantum routing protocols. As an educator, Childs has taught courses on quantum algorithms and information processing at both the University of Maryland and University of Waterloo, with lecture notes and materials spanning multiple years. Contact: amchilds@umd.edu | Office: ATL 3359 | Affiliated with University of Maryland's quantum research institutes.
Daniel M. Kane is a Professor at the University of California, San Diego (UCSD), holding a joint appointment in the Department of Mathematics and the Department of Computer Science and Engineering (CSE). His research spans mathematics and theoretical computer science, with a focus on number theory, combinatorics, complexity theory, and computational statistics. He earned a Ph.D. in Mathematics from Harvard University (2011) and dual BS degrees in Mathematics with Computer Science and Physics from MIT (2007). Prior to UCSD, he was a postdoctoral researcher at Stanford University (2011–2014) on an NSF fellowship. His research interests include robust statistics, machine learning, polynomial threshold functions, and algorithmic methods for high-dimensional data. Notable achievements include co-authoring the book Algorithmic High-Dimensional Robust Statistics (Cambridge University Press, 2023) and receiving the Best Paper Award at the Conference on Computational Complexity (2013), as well as gold medals at the International Mathematical Olympiad (2002 and 2003). Current teaching includes courses such as Math 96 (Putnam Seminar), Math 154 (Graph Theory), CSE 101 (Algorithms), and CSE 203A (Randomized Algorithms). He has consulted for companies like CASPER Labs and AIble, and his work extends to cryptographic protocols, including quantum money schemes based on quaternion algebras. Key contributions include breakthroughs in robust mean estimation, list-decodable learning, and the development of efficient algorithms for statistical problems. His research often bridges foundational theory with practical applications in machine learning and data analysis.
David Jao is a Professor in the Department of Combinatorics and Optimization at the University of Waterloo. His research focuses on post-quantum cryptography, particularly leveraging isogenies of supersingular elliptic curves for secure cryptographic protocols. He is renowned for co-developing the Supersingular Isogeny Key Encapsulation (SIKE) protocol, a leading candidate for post-quantum cryptography standards. His work spans theoretical foundations and practical implementations, including optimizing isogeny-based systems for embedded devices and ARM processors. Research interests include isogeny-based cryptosystems, elliptic curve cryptography, zero-knowledge proofs, and cryptographic security against quantum attacks. He explores applications of expander graphs and Ramanujan graphs in cryptography, alongside algorithmic improvements for cryptographic protocols such as SIDH (Supersingular Isogeny Diffie-Hellman). Key contributions include advancements in key compression techniques for SIKE, side-channel attack mitigation, and formalizing security models for post-quantum key exchange. His publications analyze cryptographic hardness assumptions, such as the discrete logarithm problem in finite groups and the semidirect product structure in isogeny-based systems. Jao’s work bridges theoretical mathematics and applied cryptography, with a focus on ensuring practical security in next-generation cryptographic systems. His research addresses challenges in quantum-resistant authentication, key establishment, and digital signatures, often emphasizing efficiency and resistance to both classical and quantum attacks.
Valter Moretti is a Full Professor in the Department of Mathematics at the University of Trento. His academic career spans roles from Research Fellow to Full Professor, focusing on Mathematical Physics and Quantum Field Theory (QFT) in curved spacetime. He earned an MSc in Physics from Genova University and a PhD in Theoretical Physics from Trento University. Research Interests : Algebraic QFT, General Relativity, Quantum Mechanics, Operator Algebras, and Spectral Theory. His work bridges mathematical rigor with physical applications, particularly in quantum localization, entanglement, and curved spacetime phenomena. Publications : Authored 15+ recent papers on topics like quantum particle localization, entanglement certification, and QFT on curved backgrounds. Collaborated on a 2022 patent for generating entangled photon states. Awards : Holds a patent for a quantum-certified random number generator (2022). Supervision : Advised 8 PhD students, including N. Pinamonti, L. Franceschini, and C. van de Ven. Coordinated national and international research projects (e.g., H2020-MSCA-COFUND-2015). Labs & Collaborations : Affiliated with INFN, TIFPA-INFN, and Q@TN (Quantum@Trento). Organized conferences like Quantum Physics and Geometry (2014) and Quantum Machine Learning (2023). Teaching : Lectures on Analytical Mechanics, Quantum Relativistic Theories, and Special Relativity. Authored textbooks on Spectral Theory and Quantum Mechanics.
Olivier Pfister is a Professor in the Department of Physics at the University of Virginia , with courtesy appointments in Electrical and Computer Engineering (2022–). His research focuses on experimental quantum optics and quantum information , particularly leveraging optical frequency combs to develop scalable quantum computing platforms. The Quantum Fields and Quantum Information (QFQI) group , which he leads, has pioneered techniques for generating multipartite entanglement in continuous-variable systems, achieving cluster-state entanglement in 60+ qumodes (with potential scaling to thousands). Collaborations span institutions like NIST, University of Sydney, CUNY, and Jefferson Laboratory, with applications in quantum simulation , non-Gaussian state characterization , and hybrid quantum technologies . Key contributions include the 2013 APS Fellowship for groundbreaking work on quantum frequency combs, NSF Distinguished Research Awards , and patents in quantum photonic devices. His group’s NSF-funded research (e.g., QLCI Preliminary Proposal, $3.2M; RAISE-EquIP, $750K) explores fault-tolerant quantum computing, machine learning integration, and microresonator-based entanglement. Pfister’s scientific awards include the 2013 UVA Distinguished Research Career Award and the 1996 JILA Clever Idea Contest Second Prize . His students and postdocs (e.g., Amr Hossameldin , Miller Eaton , Rajveer Nehra ) have published extensively on quantum tomography, cluster states, and photonic detector design. Pfister also serves on advisory and planning committees at UVA, emphasizing interdisciplinary collaboration across physics , engineering , and quantum information .
Christophe VIGNAT is a Professor at CentraleSupélec, affiliated with the Laboratoire des Signaux et Systèmes (L2S). His research focuses on number theory, special functions, probability, and their applications in signal processing and control systems. He has held visiting professorships at École Polytechnique Fédérale de Lausanne (EPFL) and Tulane University. VIGNAT's work bridges pure mathematics and applied fields, with notable contributions to Bernoulli/Euler polynomials, multiple zeta values, and probabilistic methods in number theory. His recent publications explore topics like partition functions, theta functions, and Ramanujan-type identities. He has delivered talks at international conferences and collaborates widely with researchers in mathematics and physics. Research Interests: Number theory, special functions (Bessel, orthogonal polynomials), probability theory, signal processing, control systems, analytic combinatorics, and their interconnections. His work often employs symbolic computation and probabilistic approaches to uncover identities and structures in mathematical analysis. Publications Trends: Recent articles emphasize partition theory, zeta functions, and integrals related to classical polynomials. His collaborations highlight interdisciplinary efforts between pure mathematics and applied sciences. Over 150 refereed papers and conference contributions demonstrate his prolific output across diverse mathematical domains. Education: While specific academic history isn’t detailed, his roles and publications suggest advanced training in mathematics and engineering, typical for a full professor in systems and control.
David Damanik is the Robert L. Moody, Sr. Professor of Mathematics at Rice University, where he has established himself as a leading researcher in spectral theory, dynamical systems, and aperiodic order. His work bridges pure mathematics with mathematical physics, focusing on the spectral properties of operators arising in quantum mechanics and quasicrystal theory. Dr. Damanik received his academic training at Johann Wolfgang Goethe-Universität in Frankfurt, Germany, earning a Dipl.-Math. in 1995, Dipl.-Inform. in 1996, and Dr. phil. nat. in 1998. His educational background reflects a strong foundation in both mathematics and computer science, which informs his interdisciplinary research approach. His research interests center around spectral theory of Schrödinger operators, particularly those with ergodic, quasi-periodic, and aperiodic potentials. He has made significant contributions to understanding the spectral properties of operators associated with quasicrystals, substitution sequences, and other aperiodic structures. His work often connects spectral properties with dynamical systems concepts, particularly through the study of rotation numbers, Lyapunov exponents, and gap labeling theorems. Damanik's research has profound implications for understanding quantum transport in aperiodic media and the mathematical foundations of condensed matter physics. Analysis of his recent publications (2022-2024) reveals a continued focus on ergodic Schrödinger operators, with two comprehensive monographs providing a systematic treatment of the field. His work spans both theoretical foundations and specific applications, addressing problems in one-dimensional systems, quasi-periodic potentials, and aperiodic tilings. The research demonstrates strong connections between spectral theory, dynamical systems, and mathematical physics, with particular emphasis on the interplay between spectral properties and the underlying dynamics of the potential. Annales Henri Poincaré Prize (2014) for the paper "Continuum Schrödinger operators associated with aperiodic subshifts" Professor Damanik has mentored numerous PhD students and maintains an extensive network of collaborators across the globe, as evidenced by his long list of coauthors. His research has been supported by various grants that enable him to organize workshops and conferences, fostering collaboration in his field. He has been instrumental in organizing major conferences such as the Spectral Theory and Mathematical Physics conference honoring Barry Simon's 80th birthday (scheduled for 2026) and multiple workshops on aperiodic order at prestigious institutions like Banff International Research Station and Mathematisches Forschungsinstitut Oberwolfach. Through his teaching of specialized courses like "Mathematics of Aperiodic Order" and "Ergodic Theory and Topological Dynamics," Damanik has cultivated the next generation of researchers in his field. His leadership in organizing conferences and workshops has established him as a central figure in the international community studying spectral theory and aperiodic structures.
Luca Carloni is a Professor of Computer Science and Department Chair at Columbia University's Columbia Engineering. He leads the System-Level Design Group, focusing on heterogeneous system-on-chip (SoC) architectures, networks-on-chip (NoC), and embedded systems. Carloni holds a Laurea Summa Cum Laude in Electronics Engineering from the University of Bologna and a PhD in Electrical Engineering and Computer Sciences from UC Berkeley. His work emphasizes specialized hardware design, energy-efficient computing, and FPGA-based prototyping. Research interests include system-level design methodologies for SoCs, embedded accelerators, and quantum computing hardware. He has pioneered frameworks like Embedded Scalable Platforms (ESP) and tools like MosaicSim for rapid SoC prototyping. Carloni has received numerous awards, including the NSF CAREER Award (2006), IEEE Fellow (2017), and multiple best paper awards at DATE and CloudCom conferences. He has served on editorial boards of IEEE Transactions on CAD and ACM Transactions on Embedded Computing , and chaired key conferences like EMSOFT and ESWeek. His research addresses challenges in heterogeneous architectures, power management, and the intersection of machine learning with embedded systems. Current projects explore quantum control systems, brain-computer interfaces, and energy-efficient datacenter computing.
Yang P. Liu is an Assistant Professor in the Computer Science Department at Carnegie Mellon University's School of Computer Science. Previously, he was a Postdoctoral Member at the Institute for Advanced Study and earned his PhD from Stanford University under the supervision of Aaron Sidford. He completed his undergraduate studies at MIT, graduating in May 2018. His educational background includes: PhD in Computer Science, Stanford University (Advisor: Aaron Sidford) Bachelor's degree, Massachusetts Institute of Technology (graduated May 2018) Dr. Liu's research spans the intersection of mathematics and computer science, with particular focus on graph algorithms , optimization , high-dimensional geometry , and additive combinatorics . His work often develops novel algorithmic techniques that bridge theoretical insights with practical applications. He has made significant contributions to areas such as convex optimization, linear programming, and combinatorial problems. His teaching includes courses like "A Principled Approach to Optimization" (CS 15-759), which covers rigorous treatments of convex optimization topics including gradient descent, interior point methods, linear regression, linear programming, and sparsification. His extensive publication record in top-tier conferences (FOCS, STOC, SODA) demonstrates a consistent focus on developing almost-linear time algorithms for fundamental graph problems, optimization techniques, and combinatorial theorems. Recent work shows increasing emphasis on combinatorial lines, corners theorem, and k-CSP approximability, while maintaining strong connections to optimization theory and graph algorithms. Dr. Liu has received notable recognition for his work: National Defense Science and Engineering Graduate (NDSEG) Fellowship (2018-2021) Google PhD Fellowship (2022-2023) Best Paper award at FOCS 2022 for "Maximum Flow and Minimum-Cost Flow in Almost Linear Time" Best Student Paper at STOC 2021 for "Discrepancy Minimization via a Self-Balancing Walk" His research has been supported by prestigious fellowships including the NDSEG Fellowship and Google PhD Fellowship. His work on graph algorithms, optimization, and combinatorics involves collaborations with researchers across theoretical computer science and mathematics. His publications often involve co-authors from multiple institutions, suggesting active research collaborations across the field. Dr. Liu maintains an active research program with a focus on developing efficient algorithms for fundamental computational problems. His recent work continues to push the boundaries of what's computationally feasible in graph algorithms, optimization, and combinatorial mathematics, with particular emphasis on achieving almost-linear time complexity for challenging problems.
Florina Almenares Mendoza is an Associate Professor at the Telematics Engineering Department of Carlos III University of Madrid , where she also serves as the Director of the University Master's Degree in Cybersecurity. Her research focuses on addressing security challenges in emerging technologies such as IoT, post-quantum cryptography, and privacy-preserving systems. Email: florina.almenares@uc3m.es Contact: 916246234 Location: 4.0.F06 - Quevedo Towers (Leganés) Research Interests Florina's work spans cybersecurity , Internet of Things (IoT) , and post-quantum cryptography , with a focus on scalable authentication, quantum-resistant protocols, and privacy. She explores machine learning applications for security, federated identity management , and smart grid security frameworks. Recent Publications Her recent research includes papers on DNSSEC soft delegation, hybrid quantum security for TLS/IPsec, PUF-based authentication in IoT, and blockchain-enabled auditability. These studies emphasize IoT security , quantum-resistant algorithms , and privacy-enhancing technologies .
Andrew Kwong is an Assistant Professor at the University of North Carolina at Chapel Hill in the Department of Computer Science. His research focuses on computer security and applied cryptography, particularly side-channel attacks and defenses, including Rowhammer, Spectre, and cache timing vulnerabilities. He teaches courses such as Hardware Security and Side-Channels and Research Topics in Computer Security , covering topics like transient execution attacks, speculative probing, and cryptographic implementation flaws. Department of Computer Science, UNC Chapel Hill Assistant Professor Teaching COMP 790-184 (Hardware Security) and COMP 790-185 (Computer Security Research) His research involves cutting-edge work on hardware vulnerabilities, including Rowhammer-based key recovery in post-quantum cryptography, cache eviction side-channels, and speculative execution attacks. His publications appear at top venues like IEEE S&P, CCS, and USENIX Security. He received a Best Paper Award Honorable Mention at CCS 2022 for his work on FrodoKEM exploitation. Key trends in his publications include leveraging hardware flaws for data leakage, cryptographic protocol breakdowns, and combining transient execution with memory corruption attacks. His work has implications for hardware design security and cryptographic implementation practices. Best Paper Award Honorable Mention, CCS 2022 Contact: andrew@cs.unc.edu
Kyle Luh is an Assistant Professor at the University of Colorado Boulder in the Department of Mathematics, part of the College of Arts and Sciences. His research focuses on probability, random matrix theory, and randomized algorithms. Education: Ph.D. in Mathematics from Yale University (2017) His recent work explores eigenvalue gaps in random matrices, controllability of non-Hermitian systems, and applications to sparse reconstruction. Publications span topics like circular law for block band matrices, Littlewood–Offord inequalities, and stability analysis in quantum walks. Key trends in his research include spectral analysis of random graphs, robustness in learning algorithms, and combinatorial aspects of matrix theory. His articles highlight intersections between pure probability and applied computational methods.
Dr Nicholas Simm is a Principal Research Fellow in the Department of Mathematics at the University of Sussex, affiliated with the School of Mathematical and Physical Sciences. He has been funded by the Royal Society since October 2018 as a University Research Fellow. His research focuses on random matrix theory, probability, and mathematical physics, with applications to areas such as quantum physics and statistical mechanics. Key research interests include orthogonal polynomials, eigenvalue statistics, multiplicative chaos, and Painlevé transcendents. His work bridges pure mathematics and applied problems, leveraging tools from probability theory and integrable systems. Notable publications include studies on asymptotics of orthogonal polynomials, fluctuations in eigenvalues of random matrices, and connections to the Riemann zeta function. His recent work explores high-frequency limits in holomorphic multiplicative chaos and large deviations in elliptic random matrices. Dr Simm has secured grants from the Royal Society and Leverhulme Trust for projects on random matrices, log-correlated fields, and mesoscopic statistics. He collaborates widely, with co-authors including leading researchers in probability and mathematical physics.
Feng Gao is a Professor of Optoelectronics at the Department of Physics, Chemistry and Biology (IFM), Linköping University, and leads the Electronic and Photonic Materials (EFM) division. He is affiliated with the Faculty of Science and Engineering (Institute of Technology) and conducts interdisciplinary research at the intersection of physics, chemistry, and materials science. His work focuses on organic semiconductors and metal halide perovskites for sustainable energy technologies. His research interests include: Organic and perovskite solar cells with high efficiency and recyclability Perovskite LEDs for next-generation lighting and displays Electrically pumped perovskite lasers Flexible and lead-free perovskite materials for X-ray detection and information storage Sustainable materials design with full lifecycle consideration His recent publications reveal a strong focus on improving device stability, reducing environmental impact, and enhancing energy conversion efficiency in optoelectronic systems. Trends in his work show a shift toward circular economy principles, green manufacturing, and multifunctional materials. His research has been published in top journals including Nature , Science , Nature Energy , and Advanced Materials . Scientific awards received: Göran Gustafsson Prize in Physics ERC Consolidator and Starting Grants Wallenberg Scholar (2024) SSF Future Research Leader (2020) Tage Erlander Prize (2020) Wallenberg Academy Fellow (2017) Lisa Meitner Grant for Israel-Swedish Collaboration Feng Gao has secured significant research funding from the European Research Council (ERC), the Knut and Alice Wallenberg Foundation (SEK 31 million for flexible X-ray technology), Swedish Research Council (VR), Swedish Energy Agency, FORMAS, Vinnova, and Marie Skłodowska-Curie Actions. He actively mentors PhD and postdoctoral researchers, including Max Karlsson and Huotian Zhang, and fosters international collaborations with institutions such as the University of Cambridge, Oxford, and Zhejiang University. His group emphasizes both scientific excellence and career development, supporting exchanges with leading global labs. He leads a dynamic research team within the Advanced Functional Materials (AFM) environment at IFM, working on groundbreaking projects such as fully recyclable solar cells, touch-sensitive LED displays, and perovskite-based random number generators for quantum communication. The group is also building new experimental infrastructure, including advanced labs for optoelectronic materials synthesis and characterization.
