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Lu SuView profile

Associate Professor

• Internet of Things
• Cyber-physical Systems
• Wireless and Mobile Sensing
• +7 more

Lu Su is an Associate Professor at the School of Electrical and Computer Engineering , Purdue University , with prior appointments at SUNY Buffalo . His research spans Internet of Things , cyber-physical systems , mmWave sensing , and crowd-sourced data validation , focusing on quality-of-information aware distributed sensing and security in autonomous systems . Ph.D. in Computer Science (2013) and M.S. in Statistics (2012) from University of Illinois at Urbana-Champaign M.E. and B.E. from Harbin Institute of Technology Research Interests: IoT , cyber-physical systems , crowd sensing , security and privacy , and machine learning for sensor networks. His work addresses quality-aware information integration , adversarial attacks in autonomous vehicles , and privacy-preserving crowd-sourced systems . Recent publications focus on mmWave-based sensing (e.g., 3D pose reconstruction), federated learning (driver monitoring), and data poisoning attacks in crowd-sourced systems. His research also extends to traffic optimization and human activity recognition using wireless networks. Professional Roles: Workshop Chair (INFOCOM 2023, 2022) TPC Vice Chair (INFOCOM 2021) Program Committee Member for top conferences Editorial Board, ACM Transactions on Sensor Networks Teaching: Courses on Embedded Systems , Internet of Things , and Network Concepts at both undergraduate and graduate levels.

Yuntian DengView profile

Assistant Professor

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +3 more

Yuntian Deng is an Assistant Professor at the University of Waterloo and a Visiting Professor at NVIDIA. He holds affiliations with Harvard SEAS as an Associate and the Vector Institute as a Faculty Affiliate. He completed his PhD in Computer Science at Harvard under Professors Alexander Rush and Stuart Shieber, followed by a postdoc under Yejin Choi. His research focuses on Natural Language Processing and Machine Learning, with notable contributions in chatbot interaction analysis (WildChat), implicit reasoning models, and markup-to-image generation. He has developed influential tools like OpenNMT and WildVis, and his work has been featured in outlets like the Washington Post and used by OpenAI and Anthropic. Education: PhD in CS (Harvard), Postdoctoral Research (University of Washington). Key achievements include the ACM Gordon Bell Prize for GenSLMs, Best Demo Runner-up at ACL 2017, and Best Paper at DAC 2020. His research emphasizes scalable datasets, efficient reasoning techniques, and real-world applications of AI models. Research interests span NLP, machine learning algorithms, and their applications in areas like dialogue systems, generative models, and ethical AI evaluation. Notable projects include WildChat (1M ChatGPT interactions), implicit chain-of-thought reasoning, and neural steganography for text-based information hiding. His articles explore topics ranging from knowledge distillation to diffusion models, with a focus on bridging theoretical advancements and practical implementations. He actively collaborates with industry partners like NVIDIA and maintains open-source tools to advance AI research accessibility.

• Hepatology
• Gastroenterology
• Cirrhosis
• +4 more

Guadalupe Garcia-Tsao is a Professor of Medicine at Yale University's Yale School of Medicine and past Chief of Digestive Diseases at the VA-Connecticut Healthcare System. She is also an Associate Editor of the New England Journal of Medicine and former President of the American Association for the Study of Liver Diseases (AASLD). Her work focuses on the complications of cirrhosis, particularly portal hypertension, variceal hemorrhage, ascites, and spontaneous bacterial peritonitis. She has authored over 200 peer-reviewed publications and co-edited major textbooks in gastroenterology and hepatology. Education: M.D. from Universidad Nacional Autónoma de México (1977) Internal Medicine Residency at Instituto Nacional de la Nutrición (1980) Gastroenterology Fellowship at Instituto Nacional de la Nutrición (1982) Hepatology Training at Yale University (1985) Research Interests: Her research emphasizes patient-oriented studies in cirrhosis complications, including portal hypertension management, variceal bleeding prevention, and ascites treatment. She explores innovative approaches like AI-driven diagnostic tools and biomarker discovery for alcohol-associated hepatitis. Her work bridges clinical practice and translational science to improve outcomes for liver disease patients. Awards: EASL International Recognition Award (2014) AASLD Clinician Educator and Mentor Achievement Award (2015) 2023 ALEH Mentor Award Advising & Grants: Dr. Garcia-Tsao mentors junior faculty and trainees, emphasizing clinical and translational research. She leads grants focused on cirrhosis pathophysiology, including studies on AI in liver disease and global cohort analyses for alcohol-associated hepatitis. Notable collaborations include work with the International Club of Ascites and ADQI initiatives. Labs & Teams: She directs the Clinical and Translational Core of the Yale Liver Center and collaborates with the VA-CT Healthcare System on translational projects. Her team investigates liver dysfunction mechanisms and develops novel therapeutic strategies for advanced liver disease.

Joel TownView profile

Adjunct Professor

• Psychotherapy Efficacy
• Short-Term Psychodynamic Psychotherapy
• Emotional Processing in Mental Health
• +6 more

Dr. Joel Town is an Adjunct Professor in the Department of Psychiatry and cross-appointed in the Department of Psychology and Neuroscience at Dalhousie University . He holds a BSc (Hons) from the University of York and a Doctorate in Clinical Psychology (DClinPsy) from the University of Sheffield. Education: BSc (Hons) in Psychology, University of York, England Doctorate in Clinical Psychology (DClinPsy), University of Sheffield, England Dr. Town's research focuses on psychotherapy outcome research , mechanisms of change in psychotherapy , and psychological treatments for depression and medically unexplained symptoms . He specializes in Intensive Short-Term Dynamic Psychotherapy (ISTDP) , examining its efficacy for conditions like treatment-resistant depression, post-traumatic stress disorder, and somatic symptom disorders. His work includes clinical trials , systematic reviews , and meta-analyses to evaluate therapeutic processes and outcomes. His recent publications highlight ISTDP applications for personality disorders, anxiety, chronic pain, and eating disorders. Key trends include emotional processing , therapeutic alliance dynamics , and cost-effectiveness of brief interventions . Dr. Town also explores how unconscious emotional conflicts influence treatment outcomes. As a clinician, he serves as the lead clinical psychologist at the Medically Unexplained Symptoms Clinic, QE-II Health Science Centre, and as Director of Dynamic Health Psychological Services, Halifax . He supervises clinical psychology interns and practicum students and contributes as a Consulting Editor for journals like Psychotherapy and Psychotherapy Research .

Olga VitekView profile

Professor

• Statistical Science
• Machine Learning
• Mass Spectrometry
• +5 more

Olga Vitek is a Professor at Northeastern University's Khoury College of Computer Sciences, with affiliated faculty status in the Department of Chemistry and Chemical Biology. Her research bridges statistical science and machine learning with mass spectrometry-based proteomics and systems biology, focusing on developing open-source software tools like MSstats and Cardinal for quantitative proteomic analyses and imaging. Education: PhD in Statistics (Purdue University), Postdoc at the Ruedi Aebersold Lab (Institute for Systems Biology) Leadership: Director of the Barnett Institute for Chemical and Biological Analysis Her work emphasizes: Statistical experimental design Signal detection in complex mass spectrometry data Causal inference in biomolecular networks Reproducible computational infrastructure Recent publications highlight advancements in quantitative proteomics , mass spectrometry imaging , and causal modeling , with applications spanning cancer research, immunology, and clinical diagnostics. Notable trends include deep learning integration for image analysis and open-source tool development for scalable, transparent workflows. Scientific accolades: Elected Fellow of the American Statistical Association 2021 Gilbert S. Omenn Computational Proteomics Award NSF CAREER award Chan-Zuckerberg Essential Open-source Software award Senior Member, International Society for Computational Biology

Ignacio Galiano ZurbriggenView profile

Assistant Professor

• Power Converter Modelling & Control
• Energy Systems Integration
• Renewable Energy Systems
• +6 more

Ignacio Galiano Zurbriggen is an Assistant Professor in the School of Sustainable Energy Engineering at Simon Fraser University (SFU), holding a P.Eng. license. His expertise spans power electronics, energy systems integration, and sustainable energy engineering. He completed his Ph.D. in Electrical & Computer Engineering at UBC (2020), followed by M.Sc. degrees from UBC (2013) and SFU (2012), and a B.Sc. in Electrical Engineering from the National University of Córdoba (2010). His research focuses on power converter modeling/control, energy systems optimization, and multi-domain systems. Notable projects include ultra-fast MPPT algorithms for PV systems, LVRT improvements for wind turbines, and GaN-based PFC design. He teaches advanced courses like SEE 895 Special Topics III and serves as an Associate Editor for the IEEE Open Journal of Power Electronics. Recent work emphasizes grid-connected converter dynamics, microgrid optimization, and adaptive control strategies for renewable energy systems. His publications span IEEE Transactions on Power Electronics, Smart Grid, and leading conferences like APEC and ECCE.

• Catalytic Reaction Engineering
• CO2 Hydrogenation
• Methanation Processes
• +5 more

Prof. Robert Güttel is the Director of the Institute for Chemical Engineering at the University of Ulm. He is a member of the Ulm Center for Thermal and Environmental Technology (UZWR) since 2016 and serves on its executive board. His work focuses on catalytic reaction engineering, particularly in CO2 utilization, methanation, Fischer-Tropsch synthesis, and process intensification. Research emphasizes catalyst design, reaction kinetics, and reactor modeling under dynamic conditions. Educations : Not explicitly stated in the provided text. His academic career is highlighted through his leadership roles and publications. Research Interests : Güttel’s research spans heterogeneous catalysis for CO/CO2 hydrogenation, transient kinetic analysis, polymeric reactors for extraterrestrial applications, and AI-driven reactor design. His team develops advanced catalysts (e.g., Ru/TiO2, cobalt@silica core-shell structures) and investigates novel reactor concepts like fibrous structured catalysts and sorption-enhanced processes. Recent work explores in-situ methanation on Mars and the impact of light on catalytic selectivity. Publications Trends : His 2024–2025 articles focus on low-temperature methanation beyond Earth, AI-based residence time analysis, and deactivation mechanisms. Studies highlight both experimental and computational approaches to optimize catalytic systems for sustainability and industrial relevance. Awards : No specific scientific awards mentioned in the text. Grants/Labs : Leads the Institute for Chemical Engineering at Ulm, collaborating on EU-funded projects related to power-to-X technologies and extraterrestrial chemistry. Active in developing lab-scale reactor systems and industrial partnerships for catalyst testing. Labs/Teams : Directs research groups focused on catalytic reactor design, transient kinetic methods, and sustainable process engineering. Collaborates with institutions on Mars habitat resource utilization and green hydrogen production systems.

Roman KucView profile

Professor

• Robotics
• Biomimetic Sensors
• Digital Signal Processing
• +4 more

Roman Kuc is a Professor of Electrical Engineering at Yale University, affiliated with the School of Engineering & Applied Science. He directs the Intelligent Sensors Laboratory, focusing on biomimetic sensors for robotics and bioengineering. His research explores brain-based devices (BBDs), sonar sensing, and neuromorphic processing inspired by biological systems. He holds a BSEE from Illinois Institute of Technology and a PhD from Columbia University. Dr. Kuc’s work bridges signal processing, robotics, and bioengineering, with applications in autonomous systems and clinical diagnostics. He has published over 200 papers and authored textbooks like Electrical Engineering in Context and The Digital Information Age . Notable honors include an honorary doctorate from the Glushkov Institute of Cybernetics and the Yale Sheffield Distinguished Teaching Award. His research themes include cognitive mapping via sonar echoes, neural network-based classification of environmental features, and biomimetic approaches to echolocation. Recent work emphasizes sensorimotor integration and robust performance in uncertain environments. Scientific awards highlight his contributions to robotics, signal processing, and education. His lab develops systems that emulate biological sensory mechanisms, aiming to advance robotics, medical applications, and assistive technologies.

Nicola McConkeyView profile

Lecturer

• Neutrino Physics
• Quantum Technology
• Detector Development
• +2 more

Nicola McConkey is an Ernest Rutherford Fellow and Lecturer in Particle Physics at the School of Physical and Chemical Sciences, Queen Mary University of London. She joined the Particle Physics Research Centre in 2024 and leads experimental work in neutrino interactions and detector development. Her affiliations include the Centre for Fundamental Physics and Centre for Experimental and Applied Physics. McConkey is an active member of international collaborations including SBND, DUNE, and MicroBooNE, where she contributed to the assembly of SBND and pioneered high-statistics measurements of electron-neutrino interactions using liquid argon detectors. Her research focuses on three primary domains: neutrino physics (particularly neutrino-argon scattering cross-sections), quantum technology applications for neutrino mass measurement, and liquid argon time projection chamber (LArTPC) detector development. McConkey's investigations aim to advance fundamental particle physics through precision measurements and technological innovation, with emphasis on improving detection capabilities for next-generation neutrino experiments. Publications predominantly explore neutrino interaction dynamics, cross-section measurements, and detector performance optimizations across MicroBooNE, SBND, and DUNE collaborations. Research trends demonstrate consistent focus on refining LArTPC technologies, developing machine learning applications for particle reconstruction, and probing beyond-Standard-Model physics through neutrino interactions. Scientific Awards: Ernest Rutherford Fellowship (2022) McConkey advises two PhD students (Oscar Chow, Yoshita Dabburi) and leads significant research funding including: STFC Grant: 'Piecing together the neutrino mass puzzle' (£431,666; 2024-2027) STFC Outreach Grant: 'Quantum Technologies for Neutrino Mass' (£99,999; 2024-2025) She coordinates research within the Particle Physics Research Centre laboratory and collaborates extensively within the SBND, DUNE, and MicroBooNE international teams, alongside leading the Quantum Technologies for Neutrino Mass collaboration developing novel measurement techniques.

• Biometrics
• Face Recognition
• Fairness in AI
• +3 more

Ana Filipa Sequeira is a researcher affiliated with INESC TEC, Porto, Portugal, and the University of Porto. Her work spans biometrics, fairness in AI, and explainable artificial intelligence. She has contributed to advancements in face recognition, synthetic data applications, and bias mitigation through techniques like knowledge distillation and model compression. Institution: INESC TEC (Porto, Portugal) Research Themes: Face recognition, fairness, explainability, synthetic data, biometric security Her recent publications focus on addressing demographic biases in face recognition systems, developing privacy-preserving explainable methods, and evaluating synthetic data's impact. She collaborates extensively with researchers like Pedro C. Neto, Jaime S. Cardoso, and Naser Damer. Sequeira has participated in organizing and analyzing competitions such as FRCSyn, BIOSIG, and SYN-MAD, emphasizing robust evaluation frameworks. Her work intersects technical innovation with ethical considerations, advocating for responsible AI applications in biometrics.

Ke LiView profile

Assistant Professor

• Machine Learning
• Computer Vision
• Algorithms
• +4 more

Ke Li is an Assistant Professor at Simon Fraser University (SFU) in Vancouver, Canada. He previously worked at Google and the Institute for Advanced Study (IAS) in Princeton. He holds a Ph.D. from UC Berkeley, advised by Jitendra Malik, and a B.Sc. in Computer Science from the University of Toronto. His research focuses on machine learning, computer vision, and algorithms, with contributions to generative modeling, neural rendering, fast nearest neighbor search, and meta-learning. Education: Ph.D. in Computer Science, UC Berkeley (2016) B.Sc. in Computer Science, University of Toronto (2008) Research Interests: Dr. Li explores foundational challenges in machine learning, including: - Generative Modeling : Developing methods like Implicit Maximum Likelihood Estimation (IMLE) to improve generative model training. - Neural Rendering : Innovating techniques like Proximity Attention Point Rendering (PAPR) for dynamic 3D scene representation. - Fast Nearest Neighbor Search : Pioneering algorithms to overcome dimensionality curses. - Learning to Optimize : Automating algorithm design through reinforcement learning. Professional Activities: Organized the IAS Seminar Series on Theoretical Machine Learning with Sanjeev Arora Lead organizer of the BIRS Workshop on 3D Generative Models Reviewer for NeurIPS, ICML, CVPR, and other top conferences Teaching: Recently taught CMPT 726: Machine Learning and CMPT 983: Generative Models at SFU.

Majed S. FataftahView profile

Assistant Professor

• Inorganic Chemistry
• Bioinorganic Chemistry
• Materials Chemistry
• +3 more

Majed S. Fataftah is an Assistant Professor of Chemistry at the University of Illinois, affiliated with the College of Liberal Arts & Sciences. He leads the Fataftah Research Group, focusing on physical inorganic chemistry at the intersection of chemistry, physics, and materials science. His research emphasizes synthetic chemistry to control photophysical properties for quantum information science, magnetic properties for novel materials, and reactivity modeling for catalysis. Education : B.S. in Chemistry & Biochemistry, University of Washington (2013) Ph.D. in Chemistry, Northwestern University (2019) Postdoctoral Fellow, Yale University (2019–2023) Research Interests : Inorganic and bioinorganic chemistry: synthesis, spectroscopy, electronic structure Metal-organic frameworks Molecular magnetism Quantum information science Key Research Themes : Students in his lab develop expertise in synthesizing small molecules/materials, X-ray crystallography, magnetometry, and advanced spectroscopic techniques (EPR, UV-vis-NIR, Mössbauer). Recent work includes studies on nickel-iron clusters, mixed-valence iron complexes, and vanadium-based molecular qubits. Labs/Teams : The Fataftah Group (2024) includes researchers like Garrett, Austin, Mari, Arsha, Joshua, Adrienne, Cayden, and Gwen, though formal student lists are not explicitly documented.

J. Tyler MeffordView profile

Assistant Professor

• Electrochemical Engineering
• Materials Science
• Renewable Energy
• +4 more

J. Tyler Mefford is an Assistant Professor in the Department of Chemical Engineering at the University of California, Santa Barbara , where he leads the Mefford Group. His research focuses on electrochemical engineering, materials science, and renewable energy technologies. Education : BS in Chemistry from Stanford University (2012), PhD in Chemistry from the University of Texas at Austin (2016). The Mefford Group develops redox-active polymers and inorganic electrode materials for applications in electrochemical energy conversion , storage , and chemical separations . Their work integrates material design , operando spectroscopy , microscopy , and computational modeling to study charge transfer at electrified interfaces. Recent publications highlight advancements in aqueous battery technology , bifunctional electrocatalysis , and mixed-conducting polymer electrodes . The group emphasizes interdisciplinary approaches and diversity in research environments. Scientific Awards : 2020 Best In-situ and Operando Characterization Presentation Award, MRS 2016 Excellence in Renewable & Clean Energy Research Award, UT Energy Institute 2016 Nano Portfolio Presentation Award, University of Texas at Austin

Susan D. HovorkaView profile

Research Professor

• Geological Sequestration of Greenhouse Gases
• Sedimentology
• Reservoir Characterization
• +3 more

Dr. Susan D. Hovorka is a Research Professor at the Bureau of Economic Geology, The University of Texas at Austin, specializing in geological techniques for environmental applications. She focuses on subsurface permeability dynamics in both tight and highly transmissive systems, with a primary emphasis on geological carbon sequestration and CO₂ storage security. Ph.D. in Geology (1990), The University of Texas at Austin M.A. in Geology (1981), The University of Texas at Austin B.A. in Geology (1974), Earlham College Her research addresses critical challenges in carbon geological storage, including: Characterizing salt formations as containment materials Analyzing carbonate fabrics for karst aquifer flow understanding Field CO₂ injection experiments for sequestration assessment Developing composite confining systems for secure CO₂ retention The articles she has contributed to since 2002 demonstrate a consistent focus on: Carbon capture and storage (CCS) technologies Reservoir pressure dynamics and fault permeability Permit-ready site workflows and risk mitigation Geological analogs from petroleum systems Dr. Hovorka actively collaborates with institutions like the Gulf Coast Carbon Center (GCCC) and participates in international CCS initiatives. Her work integrates sedimentology, geophysics, and environmental policy to advance subsurface carbon management solutions.

Vinod VaikuntanathanView profile

Professor

• Cryptography
• Fully Homomorphic Encryption
• Lattice-Based Cryptography
• +4 more

Vinod Vaikuntanathan is the Ford Foundation Professor of Engineering in the MIT EECS department and a principal investigator at MIT CSAIL. He holds a BTech from IIT Madras (2003), and SM/PhD degrees from MIT (2005/2009). His research focuses on cryptography, particularly fully homomorphic encryption (FHE), lattice-based cryptography, and quantum-resistant systems. He co-founded Duality Technologies as Chief Cryptographer. **Education:** BTech in Computer Science (2003), Indian Institute of Technology Madras SM in Electrical Engineering & Computer Science (2005), MIT PhD in Computer Science (2009), MIT **Research Interests:** His work spans FHE (enabling computations on encrypted data), lattice-based cryptography (post-quantum security), and intersections with quantum computing, machine learning, and privacy. He explores applications in secure computation, algorithm design, and cryptographic protocols. **Awards:** Recipient of the Gödel Prize (2022), Simons Investigator (2023), and MacVicar Faculty Fellow (2024). His work on FHE and lattice algorithms has earned widespread acclaim in cryptography and theoretical computer science. **Teaching & Mentorship:** Advanced cryptography courses at MIT (e.g., 6.5630, 6.876J) Advised PhD students (e.g., Sergey Gorbunov, Tianren Liu) and postdocs (e.g., Nir Bitansky, Mark Zhandry) now leading positions in academia and industry **Collaborations:** Organizer of the Charles River Crypto Day and MIT Cryptography Seminar Principal investigator on grants from NSF, DARPA, and Microsoft