جستجوی استاد راهنمای دانشگاهی

Danijela Efnushevaمشاهده پروفایل

استادیار

• Computer Engineering
• Network Security
• Machine Learning
• +۵ مورد دیگر

Danijela Efnusheva is an Assistant Professor at the Faculty of Electrical Engineering and Information Technologies, Ss. Cyril and Methodius University in Skopje, Macedonia. She leads the Computer Technologies and Engineering Lab since 2020 and has held academic positions since 2009. Her expertise spans computer engineering, network security, FPGA design, and machine learning applications. Education: Ph.D. in Technical Sciences (2017), Master of Electrical Engineering (2010), and Bachelor's in Informatics (2008), all from FEEIT, Skopje. Research focuses on FPGA-based hardware architectures, network security solutions, IoT systems, and machine learning applications in healthcare and finance. Key projects include the UbiLAB remote laboratory framework and FPGA implementations for network packet processing. Publications emphasize network security, embedded systems, and machine learning, with contributions to conferences like ETAI and Applied Innovations in IT. She coordinates projects such as the OBD cloud platform and has expertise in remote lab infrastructure and IoT monitoring systems.

Harshvardhan Takawaleمشاهده پروفایل

پژوهشگر

• Wearable Sensing
• Acoustics
• Multimodal Imaging
• +۷ مورد دیگر

Harshvardhan Takawale is a third-year Computer Science PhD student at the University of Maryland College Park, affiliated with the iCoSMoS Lab under Prof. Nirupam Roy. He has previously worked as a Lead Researcher at Silence Laboratories Singapore and interned at Nokia Bell Labs UK and Cambridge. Education: B.E. in Computer Science from BITS Pilani (2020), currently pursuing PhD at UMD. Research Interests: Focus on enabling acoustic and RF sensing on low-power wearable platforms, gesture/micro-motion detection for smart environments, and physics-informed ML for context-aware systems. His work bridges hardware constraints with advanced inference for ubiquitous healthcare and mobility services. Recent Publications: Contributions to wearable interfaces (Scribe), auditory attention detection on earables, and low-power acoustic event sensing highlight his expertise in multimodal systems and signal processing. Earlier works span cybersecurity (malware detection), NoC fault tolerance, and continuous authentication. Scientific Awards: Dean's Fellowship at UMD Computer Science (2022, 2023). Roles & Projects: Interned at Nokia Bell Labs on earable-based attention detection; led Silence Laboratories' projects on co-location authentication (>92% accuracy) and landmark extraction for proof-of-visit. Also served as Publicity Chair for HumanSys 2024.

• Drug Discovery
• Small Molecule Therapeutics
• Pharmaceutical Development
• +۳ مورد دیگر

Stephen Munk is a Professor of Practice and Deputy Director of the Biodesign Institute at Arizona State University. He holds affiliations with the School of Molecular Sciences and has extensive industry experience in drug discovery and manufacturing. Previously served as CEO of Ash Stevens Inc., securing numerous FDA approvals for oncology drugs including Velcade and Vidaza. Elected Senior Member of the National Academy of Inventors (2022). Education: B.S. Chemistry, Arizona State University (1979) Ph.D. Organic Chemistry, UC Berkeley (1985) Postdoctoral Fellow under Dale Boger at Purdue University (1985-1988) Research Interests: Focuses on discovery and development of small molecule therapeutics, particularly anticancer drugs. Expertise in process development for safe synthesis of pharmaceuticals and regulatory compliance. Active in advancing drug discovery efficiency through interdisciplinary approaches. Awards: Senior Member, National Academy of Inventors (2022) Six NIH research contracts secured during Ash Stevens leadership Leadership & Boards: Former Chairman, AACR Chemistry in Cancer Research Working Group (2014) Chairman, MichBio Board of Directors (2009-2014) Member, Henry Ford Community College Biotechnology Advisory Board (2009-2016) Teaching: Teaches special topics courses in biomedicine and chemistry at ASU including BIO 598 and BCH 598.

• Software Engineering
• Machine Learning
• Precision Agriculture
• +۷ مورد دیگر

Önder Babur is an Assistant Professor in the Department of Information Technology at Eindhoven University of Technology. His research focuses on software engineering, machine learning applications, precision agriculture, and digital twin technologies. He has contributed to projects involving business process modeling, drone analytics, and energy market methodologies. Babur collaborates with institutions like Wageningen University & Research and has supervised PhD candidates in generative AI approaches and digital twin systems. His research interests span model analytics, clone detection, API usage analysis, and low-code platforms. Notable projects include an empirical study of business process models on GitHub and foundational work in digital twins for energy markets. Babur has co-developed datasets for drone imagery analysis and systematic reviews of food recommender systems. His work bridges theoretical software engineering advancements with practical applications in agriculture and energy systems. Advising PhD candidates include Gürkan Soykan (digital twins in energy markets) and Jeroen Doornbos (generative AI in drone analytics). Projects emphasize collaborative frameworks like SAMOS for model management and Apache Spark-based distributed analytics. Babur’s contributions span 45+ peer-reviewed publications and two active PhD supervisions.

Christophe Hauserمشاهده پروفایل

استادیار

• Software Security
• Binary Program Analysis
• Reverse Engineering
• +۶ مورد دیگر

Christophe Hauser is an Assistant Professor at Dartmouth College and a member of the Institute for Security, Technology and Society (ISTS). His research focuses on software security, binary program analysis, reverse engineering, and vulnerability discovery across software and hardware systems. He integrates formal methods, machine learning, and program analysis to enhance cybersecurity defenses. Education: Joint PhD from CentraleSupélec (France) and Queensland University of Technology (Australia). Prior roles include Research Lead at USC Information Sciences Institute (USC-ISI) where he founded the Binary Analysis and Systems Security (BASS) group, and postdoctoral researcher at UC Santa Barbara’s Seclab. Research Interests: Binary code and firmware analysis, intrusion detection, usable security, privacy-preserving systems. Notable projects include BinPool (vulnerability dataset), BinHunter (vulnerability localization), and Harm-DoS (DoS mitigation). His work emphasizes practical applications such as automated fuzzing, decompilation analysis, and neuro-symbolic code search systems. He has contributed to open-source tools like angr and developed frameworks for firmware integrity validation (BootKeeper).

Michael Godfreyمشاهده پروفایل

استاد

• Software Engineering
• Software Evolution
• Empirical Studies
• +۵ مورد دیگر

Michael Godfrey is a Professor at the University of Waterloo's David R. Cheriton School of Computer Science, affiliated with the Department of Electrical and Computer Engineering. His work focuses on software engineering, empirical studies of software systems, code review practices, and open-source software ecosystems. He holds a Ph.D., M.Sc., and B.Sc. from the University of Toronto (1997, 1988, 1986). Research interests include software evolution, mining software repositories, provenance tracking, code duplication analysis, and program comprehension. He actively explores how developers interact with code reviews, documentation systems, and modern CI/CD pipelines. Recent work investigates app store software ecosystems, Bash scripting vulnerabilities, and deep learning API testing. Publications span empirical studies of developer communities (e.g., Stack Overflow analysis), architectural teaching methods, and automated testing techniques like documentation-guided fuzzing. His work bridges theory and practice, addressing challenges in large-scale systems maintenance and developer productivity. Leverages tools like Elasticsearch for repository mining and explores anomaly detection in software development. Engaged in curriculum development for software architecture education and has contributed to conferences like MSR and ICSE.

Hong Zhangمشاهده پروفایل

استادیار

• Large-scale data analytics
• Distributed ML training and serving systems
• Application and network scheduling
• +۵ مورد دیگر

Hong Zhang is an Assistant Professor at the University of Waterloo, specializing in large-scale data analytics, distributed machine learning systems, and cloud computing. His research focuses on advancing robust and efficient methods for modern AI systems, including topics like adversarial robustness, zero-knowledge proofs for deep learning, and scalable inference techniques for large language models. He holds a Ph.D. in Computer Science from the Hong Kong University of Science and Technology and dual bachelor's and master's degrees in Electronics and Communications Engineering from Huazhong University of Science and Technology. Education: Ph.D., Computer Science and Engineering, Hong Kong University of Science and Technology (2019) B.Sc. and M.Sc., Electronics and Communications Engineering, Huazhong University of Science and Technology, China (2013) Research Interests: Hong's work bridges theoretical foundations and practical applications in distributed ML systems, data center networking, and secure AI. Key areas include optimizing large-scale training/serve pipelines, mitigating adversarial vulnerabilities, and developing privacy-preserving techniques like zero-knowledge proofs for deep learning. His contributions span both algorithmic innovations and real-world system implementations. Publications Trends: Recent work emphasizes scalable inference acceleration (e.g., Eagle series), trustworthy AI (e.g., generative model guidelines), and cryptographic safeguards for ML (e.g., zkdl/zkllm frameworks). He frequently explores intersections between security, efficiency, and scalability in modern AI systems. Awards/Grants: No specific awards or grants mentioned in available texts. Advising & Labs: While student names aren't listed, his research group likely focuses on distributed systems and secure ML. Active collaborations likely involve cloud computing and adversarial machine learning domains.

Laura Southمشاهده پروفایل

استادیار مهمان

• Human-Computer Interaction
• Accessibility Technologies
• Data Visualization
• +۴ مورد دیگر

Laura South serves as a Visiting Assistant Professor in the Department of Computer Science at Williams College. She joined the institution after completing her PhD at Northeastern University in 2024 under Michelle Borkin's supervision. Her research centers on digital accessibility , with dual specialization in: Photosensitive epilepsy safety in interactive media (VR, data visualizations, social platforms) Assistive technologies for visual impairments (3D-printed braille systems) Notable contributions include seizure-risk mitigation frameworks for dynamic content and empirical evaluations of tactile interfaces. Her 15 most recent publications (2020-2024) reveal three dominant research trajectories: Photosensitivity safety mechanisms across immersive platforms (6 papers) Accessibility extensions for visualization systems (5 papers) Novel evaluation methodologies for inclusive design (4 papers) Key venues include CHI, IEEE VIS, and ACM TOCHI. Laura teaches human-computer interaction and introductory programming courses. Her educational background includes dual B.S. degrees in Computer Science and Statistics from Colorado State University (2018), followed by a Ph.D. in Computer Science from Northeastern University (2024).

Sangita Pokhrelمشاهده پروفایل

مدرس

• Machine Learning
• Deep Learning
• Data Science
• +۱۰ مورد دیگر

Sangita Pokhrel is a Lecturer in Computer Science and Data Science at York St John University's London Campus. She holds an MSc in Computer Science (Distinction) from York St John and an undergraduate degree in Electronics and Communication Engineering from Tribhuvan University, Nepal. Her research focuses on machine learning, AI applications in agriculture and healthcare, blockchain, and educational technology. She leads the Paragon Research Group, emphasizing interdisciplinary innovation in data science and Gen AI. Research Interests: Machine Learning, Deep Learning, AI in Agriculture, Mental Health Analysis, Blockchain, and Educational Technology. She actively collaborates with IBM UK and universities like St Mary’s University to bridge academia-industry gaps. Her funded projects include SAAR and QR initiatives, and she has published in IEEE journals and conferences. Awards include the Best Presentation Award at CDSBDA 2022. Teaching: She instructs master’s modules in Big Data, Agile Software Development, AI, and Data Visualization. Pedagogical focus on practical learning and real-world problem-solving. Engages students through initiatives like The Dock and MakerVerse, offering hands-on experience with VR and podcasting tools. Labs/Teams: Paragon Research Group (focusing on blockchain and Gen AI), collaborations with UK universities to enhance teaching practices. Part of diversity initiatives like U Connect Mentoring and YSJ London Women’s Network.

• Computer Security
• Mobile Security
• Network Security
• +۶ مورد دیگر

Georg Merzdovnik is a Lecturer at Vienna University of Technology (TU Wien) with a focus on computer security and privacy . His work spans binary rewriting, web privacy, IoT security, and Android application analysis, reflected in publications in top venues like ACM Computing Surveys and IEEE Euro S&P. He actively supervises student research projects in security-related domains. Primary Affiliation: Vienna University of Technology (TU Wien) Research Interests include: Binary rewriting and obfuscation techniques Web privacy mechanisms post-GDPR IoT device security in IPv6 networks Mobile application threat analysis Malware detection in Windows shellcodes Evaluation of tracker-blocking tools Thesis Supervisions (2012–2024) cover topics like IoT testbeds, Android intent firewalls, and secure messaging services.

• Automated Reasoning
• Knowledge Representation and Reasoning
• Computational Logic
• +۵ مورد دیگر

Uwe Egly is an Associate Professor at the Department of Knowledge-Based Systems, Faculty of Informatics, Technische Universität Wien (TU Wien). His research focuses on automated reasoning, proof theory, knowledge representation, and computational logic, with a strong emphasis on quantified Boolean formulas (QBFs), argumentation frameworks, and applications of AI in engineering. He leads projects funded by the Austrian Science Fund (FWF) and the Vienna Science and Technology Fund (WWTF), including the Boolean project (2011–2019) and FAME (2011–2014). Egly is known for developing QBF solvers like DepQBF and contributing to SAT-solving techniques. He teaches courses such as Abstract Argumentation , Formal Methods in Computer Science , and Quantum Computing . His research interests span proof complexity, satisfiability checking, and AI-driven algorithms for path planning. He has advised numerous students on theses involving quantum algorithms, QBF solver optimizations, and argumentation frameworks. Egly’s work bridges theoretical computer science with practical applications, including contributions to deformation monitoring systems and circuit synthesis using SAT-based methods. He is involved in international workshops and conferences, such as SAT, FMCAD, and Dagstuhl Seminars, and has edited proceedings for events like SAT 2014 . His collaborations include projects on scenario-based testing of UML diagrams and semantics-aware model versioning. Egly’s interdisciplinary approach integrates logic, artificial intelligence, and computational methods to solve complex theoretical and applied problems.

Robert Souléمشاهده پروفایل

دانشیار

• Networking
• Distributed Systems
• Databases
• +۱ مورد دیگر

Robert Soulé is an Associate Professor at Yale University, holding dual appointments in Computer Science and Electrical Engineering. He previously served as an Associate Professor at the Università della Svizzera italiana (USI) in Lugano, Switzerland, and retains an Adjunct Professor position there. Soulé earned his B.A. from Brown University and his Ph.D. from New York University, followed by a postdoc at Cornell University. He is a Senior Member of the ACM and IEEE, and his research has been recognized with best paper awards at DEBS 2012, NSDI 2018, and CoNEXT 2020. His research focuses on computer systems, including networking, distributed systems, databases, and programming languages. Notable contributions include work on in-network computing, programmable data planes, and sustainable networking. He teaches advanced courses on databases, networking, and compilers at Yale and has previously taught at USI and Cornell. Soulé advises a team of PhD students and postdocs, with alumni working in industry and academia. His grants include NSF support for sustainable computing initiatives. He leads research efforts in areas like carbon-aware networking, quantum network specifications, and high-performance RPC systems. His work bridges theory and practice, emphasizing system design and verification. Affiliations: Yale University, USI (Adjunct) Education: Ph.D. (NYU), B.A. (Brown) Grants: NSF funding for sustainable computing Lab/Team: Research group focused on systems and networking innovations

Tim Weningerمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Social Media Analysis
• Network Science
• +۳ مورد دیگر

Tim Weninger is the Frank M. Freimann Associate Professor of Engineering and Director of Graduate Studies in the Department of Computer Science and Engineering at the University of Notre Dame's College of Engineering. He is affiliated with the Lucy Family Institute for Data and Society, the Pulte Institute for Global Development, and the Technology Ethics Center. His research focuses on artificial intelligence, social media analysis, network science, and understanding human information consumption/curation behaviors. Key areas include disinformation detection, AI ethics, and sociotechnical systems. Weninger holds a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign (2013). His work is funded by NSF, DARPA, USAID, Templeton Foundation, AFOSR, and Pacific Northwest National Laboratory. He actively recruits graduate students interested in AI/social media intersections. Research emphasizes real-time social media manipulation detection (e.g., MEWS system), propaganda analysis in conflicts (e.g., Russia-Ukraine Telegram narratives), and cross-cultural science communication studies across 68 countries. Recent projects include VirTLab for human-AI teaming simulations and MedCodER for medical coding assistance. Key contributions include frameworks for graph modeling (Vertex Replacement Grammars), meme dynamics analysis, and early warning systems for disinformation. His work bridges technical innovation with societal impact through ethical AI design and misinformation mitigation strategies.

Taolue Chenمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۶ مورد دیگر

Taolue Chen is a Senior Lecturer in the School of Computing and Mathematical Sciences at Birkbeck, University of London. He holds a PhD from Vrije Universiteit Amsterdam and MSc/BSc degrees from Nanjing University, China. His research focuses on neuro-symbolic software engineering, combining AI (Machine Learning/NLP) with formal methods in software engineering, program analysis, and verification. He has published extensively in top conferences like POPL, OOPSLA, and NeurIPS, and has received multiple awards including the ACM SIGSOFT Distinguished Paper Award (2024). Education: PhD: Centrum Wiskunde & Informatica (CWI) and Vrije Universiteit Amsterdam (2010s) MSc: Computer Science, Nanjing University (China) BSc: Computer Science, Nanjing University (China) Research Interests: Taolue's work bridges AI and traditional software engineering, with a focus on neuro-symbolic systems, code generation, adversarial robustness, and formal verification of cryptographic programs. He explores synergies between statistical (deep learning) and logical (constraint solving) methods to address challenges in software verification and cybersecurity. Articles Overview: His recent work emphasizes code generation improvements, adversarial defense mechanisms, and formal verification of secure cryptographic implementations. Key themes include enhancing model robustness, optimizing documentation in code generation, and applying large language models to symbolic reasoning tasks. Awards: Best Paper Award at SETTA’20 (2020) 1st Prize in CCF Software Prototype Competition (2022) QF Strings Competition Win (2023) ACM SIGSOFT Distinguished Paper Award (2024) Advising & Grants: Advises PhD student JEFERSON DORNELLES SCHNEIDER. His work is supported by grants focusing on neuro-symbolic systems, cybersecurity, and formal methods for software engineering. Labs/Teams: Leads research groups in neuro-symbolic software engineering and cryptographic verification at Birkbeck, collaborating with institutions like University of Oxford and University of Twente.

Barbara J. Woldمشاهده پروفایل

استاد

• Transcriptional Networks
• Molecular Biology
• Genomics
• +۵ مورد دیگر

Barbara J. Wold is the Bren Professor of Molecular Biology and Merkin Institute Professor at the California Institute of Technology (Caltech), where she has held continuous faculty appointments since 1978. Her leadership roles include Director of the Beckman Institute (2001-2011) and Director of the Merkin Institute (2019-2023), reflecting her significant institutional impact. Her academic journey began with a B.S. from Arizona State University (1973) followed by a Caltech Ph.D. (1978). She advanced through Caltech's faculty ranks from Research Fellow (1978) to Assistant Professor (1981-1988), Associate Professor (1988-1996), Professor (1996-2002), Bren Professor (2003-), and Merkin Institute Professor (2024-). Dr. Wold's research centers on transcriptional networks in mouse and human systems, integrating molecular biology, cellular biology, developmental biology, biochemistry, and biophysics . Her work pioneers single-cell and spatial transcriptomics approaches to decode gene regulation across tissues and developmental stages, with particular emphasis on cellular heterogeneity and regulatory dynamics. Analysis of her 2022-2025 publications reveals dominant themes in large-scale collaborative genomics , including leadership in the Human Cell Atlas and ENCODE projects. Key methodological contributions span spatial transcriptomics for kidney disease modeling, cross-strain mouse genomics, long-read RNA-seq validation, and ethical frameworks for international data sharing, demonstrating her dual focus on technical innovation and responsible science. Her distinguished career is marked by two named professorships: the Bren Professorship (2003) and Merkin Institute Professorship (2024), recognizing her transformative contributions to molecular biology. As a decades-long Caltech faculty member and institute director, Dr. Wold has mentored numerous graduate students and secured substantial research funding, though specific advisee names and grant details are not publicly listed. Her current leadership in the Merkin Institute continues to drive interdisciplinary biomedical research. Her laboratory operates at the nexus of the Beckman Institute and Merkin Institute ecosystems, leveraging Caltech's strengths in engineering and quantitative biology to advance transcriptional network research through cutting-edge genomic technologies and computational approaches.