جست‌وجوی استاد و پژوهشگر

Robert Wilsonمشاهده پروفایل

دانشیار

• Computational Cognitive Neuroscience
• Reinforcement Learning
• Decision Making
• +۷ مورد دیگر

Robert Wilson is an Associate Professor in the School of Psychology at Georgia Institute of Technology. His research focuses on computational cognitive neuroscience, reinforcement learning, decision making, and their applications in psychiatry and aging. Wilson leads a lab integrating computational modeling with behavioral experiments, neuroimaging, and neurostimulation to explore the algorithms underlying human cognition. He holds a Ph.D. in Bioengineering from the University of Pennsylvania (2009). Education: Ph.D. in Bioengineering, University of Pennsylvania, 2009 Research Interests: Wilson’s work spans computational models of decision making, reinforcement learning dynamics, and the neural mechanisms of explore-exploit trade-offs. His lab investigates phishing detection cognition, navigation strategies, and perceptual decision making, with recent studies on aging-related cognitive decline and psychiatric disorders. Publications: His recent work includes studies on computational models of exploration strategies, phishing susceptibility (PEST task), and aging effects on decision-making. Articles often bridge neuroscience and AI, such as applying reinforcement learning to large language models. Awards & Grants: While no formal awards are listed, his research has been supported by grants exploring computational psychiatry and neuroimaging. Labs & Teams: Wilson directs a multidisciplinary lab at Georgia Tech, collaborating with experts in AI, neuroscience, and clinical psychology to advance computational theories of the mind-brain relationship.

• Natural Language Processing
• Machine Learning
• Multimodal Learning
• +۵ مورد دیگر

Ekaterina Shutova is an Associate Professor at the Institute for Logic, Language and Computation (ILLC) within the Faculty of Science at the University of Amsterdam. She concurrently holds a Visiting Associate Professor position in the Computer Science Department at Stanford University. She leads the Amsterdam Natural Language Understanding Lab and heads the NLP & Digital Humanities research unit at ILLC. An ELLIS Scholar, she earned her PhD from the University of Cambridge Computer Laboratory and Pembroke College. Her research has been funded by ERC, Innovate UK, British Academy, Leverhulme Trust, Google, Meta, and Deloitte. Her research spans natural language processing and machine learning, with core interests in: Few-shot learning for NLP Multilingual and cross-lingual systems Joint modeling of language and vision Cognitive processing and semantic representation Figurative language interpretation Computational social science applications Her recent publications (2024-2025) predominantly focus on multimodal learning, cultural alignment in AI, metaphor processing, and evaluation methodologies for language models. These works reflect a trend toward integrating cognitive science with multilingual systems and ethical considerations. Awards & Fellowships: ERC Consolidator Grant (2025) ELLIS Scholar Outstanding Paper Award at ACL 2023 Finalist for Outstanding Certification by TMLR Runner-up Best Paper Award at NAACL-HLT 2016 Research Leadership: She directs the Amsterdam Natural Language Understanding Lab, supervising 8 PhD students, 1 MSc student, and 34 alumni. Her projects include an ERC-funded initiative on globally accessible language technology and an AI Democratization grant for hate speech detection.

• Network Security
• Cryptographic Protocols
• Industrial Control System Security
• +۷ مورد دیگر

Professor Ernest Foo is a distinguished academic at Griffith University's School of Information and Communication Technology, specializing in cybersecurity with a focus on industrial control systems and cryptographic protocols. With over 15 years of experience in computer networking, he has established himself as a leading expert in SCADA security and smart grid cybersecurity. His research has significant practical applications in critical infrastructure protection, and he has developed hands-on security training programs that have trained professionals from major Australian utilities and government agencies. Professor Foo's educational background includes: Bachelor of Engineering with Honours in Electronic and Computer Engineering from University of Queensland Doctor of Philosophy from Queensland University of Technology Professor Foo's research interests center around secure cryptographic protocols with specific applications in industrial control system security and cyber physical systems. His work spans SCADA security, smart grid protection, wireless sensor network security, and post-quantum cryptography. He has made significant contributions to understanding vulnerabilities in industrial protocols like Modbus and DNP3, and has pioneered the application of process mining and data mining techniques for attack detection in critical infrastructure systems. His research bridges theoretical security concepts with practical implementations in real-world industrial environments. Professor Foo's recent publications demonstrate a clear trajectory toward increasingly sophisticated security frameworks for critical infrastructure. His work shows a progression from foundational SCADA security research to advanced applications of artificial intelligence, machine learning, and formal methods in cybersecurity. A notable trend is the integration of zero trust principles with industrial control systems, alongside growing emphasis on post-quantum cryptographic solutions. His publications span high-impact journals and conferences in cybersecurity, with increasing focus on anomaly detection in cyber-physical systems and the application of graph-based machine learning techniques to network security challenges. Professor Foo's notable scientific achievements include: Best paper award at the 2nd International Cyber Resilience Conference for "Gap analysis of Intrusion Detection in Smart Grids" Professor Foo has secured significant research funding including an ARC Linkage grant with Powerlink Queensland focused on cyber security for electricity sub-stations. He currently leads multiple research projects including Westpac Micro-Credentials in Financial Crime Investigation, Digital Banking Micro-credentials with ANZ, and research on quantum-safe cryptography. As a dedicated educator, he serves as Program Director for multiple cybersecurity programs including the Master of Cyber Security, and has supervised numerous doctoral and masters students. His Cyber Security: Industrial Control System course, conducted annually from 2013-2018, featured innovative hands-on training with real-world participants from major Australian utilities. Professor Foo has been instrumental in establishing the SCADA security research laboratory with multiple vendor system miniatures running industrial PLCs. His work bridges theoretical security concepts with practical implementations, making significant contributions to the security of industrial control systems and critical infrastructure worldwide.

Xing Gaoمشاهده پروفایل

استادیار

• Cybersecurity
• Cloud Computing
• Mobile Computing
• +۴ مورد دیگر

Xing Gao is an Assistant Professor at the University of Delaware, affiliated with the Department of Computer and Information Sciences and jointly with the Department of Electrical and Computer Engineering. His office is located at 316B FinTech Innovation Hub on the STAR Campus. He holds a PhD from the College of William and Mary (2018) and a BS from Beijing Institute of Technology (2011). Research Interests: Cybersecurity in Software Supply Chain, Web 3, High-Performance Computing, Large Language Models, with a focus on Security, Cloud Computing, and Mobile Computing. Education: PhD | 2018 | College of William and Mary BS | 2011 | Beijing Institute of Technology His recent work explores cybersecurity vulnerabilities in cloud gaming services (CCS'22), container registries (USENIX-SEC'22), and software supply chains, with specialized attention to GPU cache attacks (USENIX-SEC'24) and Ethereum smart contracts (WWW'24). His research spans theoretical and applied aspects of system security, including CI/CD pipelines (CCS'24), SDN backdoors (INFOCOM'23), and hardware-level threats (ACSAC'21). Scientific Awards NSF CAREER Award (2024) NSF CRII Award (2020) NDSS Distinguished Poster Award (2016) He serves as Registration Chair for ACM/IEEE Symposium on Edge Computing (2023) and Publicity Co-Chair for IEEE Conference on Communications and Network Security (2022). He is actively involved as TPC Member in multiple top-tier conferences including USENIX Security (2026,2025), CCS (2026,2025,2024), and IEEE DSN (2024). He has also reviewed for journals like IEEE Transactions on Dependable and Secure Computing. Labs & Teams X-Lab at the University of Delaware, a research group focused on cybersecurity in emerging technologies.

Md Manjurul Ahsanمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Dr. Md Manjurul Ahsan serves as a Research Assistant Professor in the Department of Industrial & Systems Engineering at the University of Oklahoma, where he develops AI-driven solutions for healthcare diagnostics and advanced manufacturing optimization. His work bridges theoretical AI advancements with practical industrial and medical applications. Education: Ph.D. in Industrial and Systems Engineering, University of Oklahoma M.S. in Industrial Engineering, Lamar University B.S. in Industrial and Production Engineering, Shahjalal University of Science and Technology Research Focus: Dr. Ahsan specializes in Artificial Intelligence with technical depth in Machine Learning , Deep Learning , and Computer Vision to solve critical challenges in healthcare diagnostics and additive manufacturing . His research emphasizes Explainable AI to enhance model trustworthiness and deployment efficiency across Cyber-Physical-Social Systems, with significant contributions to Aerospace and Defense applications. Publication Trends: Recent work (2023-2025) reveals a strategic expansion from core manufacturing applications into medical AI (diffusion models for diagnostics), cultural preservation (NLP for Dravidian languages), and geopolitical AI analysis. His publications consistently address data imbalance challenges while advancing digital twin integration in quality control systems. Scientific Recognition: GCOE Dissertation Excellence Award (2023) International Student Scholarship (2022) Outstanding Academic Achievement in Engineering (2022) IEEE IEMCON Best Paper Award (2020) Netti Vincent Boggs Engineering Excellence Award (2020) Research Leadership: As director of the Sooner Additive Manufacturing Laboratory , Dr. Ahsan leads cross-disciplinary teams developing real-time monitoring systems using FARO arms and CMM metrology. His postdoctoral work at Northwestern University (2023-2024) advanced AI deployment frameworks, resulting in 60+ peer-reviewed publications with multiple papers ranking in engineering's top 1% for citations.

Aditya Joshiمشاهده پروفایل

مدرس ارشد

• Natural Language Processing (NLP)
• Machine Learning
• Cybersecurity
• +۴ مورد دیگر

Dr. Aditya Joshi is a Senior Lecturer in the School of Computer Science & Engineering at the University of New South Wales (UNSW). He specializes in Natural Language Processing (NLP), with a focus on sarcasm detection, dialectal NLP, and ethical AI applications in public health and cybersecurity. He joined UNSW in 2023 following industry roles at SEEK, Notiv, and Fractal Analytics, where he developed NLP systems for recommendation engines and meeting analytics. His research has garnered over 3,000 citations (h-index 26) and secured $3.1M in grants, including Defence Trailblazer and Google exploreCSR awards. Education: Joint PhD (2018) from IIT Bombay (India) and Monash University (Australia); MTech in CSE (2011) from IIT Bombay. Research Interests: Making NLP models robust for non-native English speakers and the LGBTI+ community, algorithmic enhancements to transformers, and applications in public health, cybersecurity, and societal issues. His work spans epidemic intelligence (collaborations with EPIWATCH and IFCYBER), cybersecurity tools like AuditNet, and inclusive AI initiatives such as queer-inclusive workshops funded by Google. He designed UNSW's new NLP course (COMP6713) and co-authored a Wiley textbook on NLP. Notable grants include the A$1.4M 'Comprehensive Defence Data Platform' (Lead CI) and A$92K Google exploreCSR grant for benchmarking dialectal sentiment. His awards include the Best PhD Thesis from IITB-Monash and Best Paper accolades at FAccT 2023 and MoMM 2020. He supervises projects on kernel-based attention reformulation, prompt-based sarcasm detection, and multilingual small-scale LLMs. His service roles include Executive Committee Member at ALTA and arXiv moderator for computational linguistics.

Ian Miersمشاهده پروفایل

استادیار

• Computer Security
• Applied Cryptography
• Blockchain
• +۴ مورد دیگر

Ian Miers serves as an Assistant Professor in the Department of Computer Science at the University of Maryland, holding a joint appointment with the University of Maryland Institute for Advanced Computer Studies (UMIACS) and serving as a core faculty member of the Maryland Cybersecurity Center (MC2). His academic home resides within the Department of Computer Science, though the overarching college/school structure is not explicitly stated in available materials. His research program centers on applied cryptography with a context-driven methodology: starting from real-world security challenges to develop deployable cryptographic protocols. Key focus areas include blockchain privacy (notably Zerocoin/Zerocash), zero-knowledge proofs, anonymous credentials, and secure messaging systems. Miers emphasizes practical implementations that address subtle security requirements in production environments, bridging theoretical cryptography with tangible system security. Analysis of his 15 most recent publications reveals dominant trends in zero-knowledge proof scalability (zkSNARKs), privacy-preserving infrastructure for blockchains, and cryptographic solutions for content moderation in encrypted messaging. His work consistently targets deployable systems, with increasing focus on balancing privacy guarantees with accountability requirements in real-world applications. Miers actively recruits PhD students for hands-on research in his small lab, emphasizing direct collaboration on applied security and blockchain problems. As a founding scientist of Aleo, Bolt Labs, and Zcash, he translates academic research into commercial products, with his work receiving coverage from major media outlets including The Washington Post, The New York Times, and Wired.

Kambiz Ghazinourمشاهده پروفایل

استاد

• Data Security and Privacy
• Data Analysis
• Privacy Enhancing Technologies
• +۴ مورد دیگر

Kambiz Ghazinour is a Professor and Chair of the Department of Cybersecurity at SUNY Canton, where he directs the Advanced Information Security and Privacy (AISP) Lab. He holds a PhD in Computer Science from the University of Calgary (2012) and a Postdoctoral Fellowship from the University of Ottawa and Children's Hospital of Eastern Ontario (2014). Previously, he served as an Assistant Professor at Kent State University (2015-2019) and earned a Master's in High Performance Scientific Computing from the University of New Brunswick (2007). Research Focus: Data Security and Privacy, Privacy Enhancing Technologies, Usable Security, Healthcare Systems, and Social Media. Key Projects: DigitalPASS—patented simulation-based privacy education tool for social media safety. His recent publications span Cybersecurity , Deep Learning , and Health Informatics , including works on cryptocurrency price prediction, Alzheimer's detection via eye tracking, and privacy-preserving surveillance. He has received multiple teaching awards such as the Best Teaching Award at the University of Calgary (2008). Faculty Recognition Award, Kent State University (2015, 2016) University Teaching Certificate (2009) Dr. Ghazinour's teaching portfolio includes graduate courses in Data Mining, Digital Forensics, Cryptography, and undergraduate instruction in cybersecurity fundamentals and programming.

Pardis Emami-Naeiniمشاهده پروفایل

استادیار

• Security
• Privacy
• Human-Computer Interaction
• +۷ مورد دیگر

Pardis Emami-Naeini is an Assistant Professor of Computer Science at Duke University, with joint appointments in the Sanford School of Public Policy and the Department of Electrical and Computer Engineering. She serves as the Director of the Duke Interdisciplinary Security, Privacy, and Interaction Research (InSPIre) lab and is a Duke Science and Technology Scholar. Her interdisciplinary work bridges computer science, public policy, and electrical engineering, with a focus on developing usable privacy and security solutions that empower individuals from diverse sociodemographic backgrounds. Dr. Emami-Naeini earned her Ph.D. in Computer Science from Carnegie Mellon University in 2020, followed by postdoctoral research at the University of Washington (2020-2022). Her research sits at the intersection of security, privacy, and human-computer interaction, with particular expertise in IoT security, technology-enabled abuse, reproductive health privacy, and smart city security. She has published extensively at flagship venues including IEEE S&P, CHI, CSCW, and SOUPS, with her work covered by major media outlets such as Wired and The Wall Street Journal. Her recent publications reveal a clear trajectory toward examining the human dimensions of security and privacy in emerging technologies, from LLM chatbots for mental health to social robots and period-tracking apps in the post-Roe v. Wade landscape. Her work consistently emphasizes the need for privacy-aware design that accounts for diverse user needs and contexts, particularly for vulnerable populations. Google Systems and ML Research Gift Award (2025) Google AI Research Scholar Program Award (2024) Top 5% Instructor in Duke Trinity College (2024) ORAU Ralph E. Powe Junior Faculty Enhancement Award (2023) Duke Science and Technology Scholar (2022) IEEE S&P paper highlighted in IEEE Security and Privacy Magazine (2021) CyLab Presidential Fellowship (2019) Dr. Emami-Naeini actively mentors several Ph.D. students including Jabari Kwesi, Jessie Cao, and Hiba Laabadli, as well as undergraduate and master's students. Her research has influenced key organizations including the National Institute of Standards and Technology (NIST), Consumer Reports, and the World Economic Forum in creating usable security and privacy labels for smart devices. She serves on numerous program committees including USENIX Security and CHI, and has participated in NSF grant review panels, demonstrating her growing leadership in the security and privacy community. Her InSPIre lab conducts user-centered research to uncover security and privacy needs of diverse stakeholders, with a particular focus on marginalized communities. The lab's work spans multiple domains including intimate partner violence, reproductive health, virtual reality, and smart cities, always with a strong emphasis on translating research findings into practical tools and policy recommendations.

• Spoken Language Processing
• Natural Language Processing (NLP)
• Paralinguistics
• +۶ مورد دیگر

Sarah Ita Levitan is an Assistant Professor in the Department of Computer Science at Hunter College, CUNY, and a member of the doctoral faculty in both Computer Science and Linguistics PhD programs at the CUNY Graduate Center. She previously served as a Postdoctoral Research Scientist at Columbia University, where she completed her PhD in Computer Science in 2019 under Dr. Julia Hirschberg. Research Focus: Spoken Language Processing Natural Language Processing Paralinguistic Analysis Trustworthiness and Deception Detection Acoustic-Procedic and Lexical Feature Extraction Online Radicalization and Misinformation Recent Publications demonstrate expertise in analyzing speech and text for trust cues, deception detection, and mental health prediction. Her awards include grants from NSF, Google, and Columbia University fellowships. She leads the Hunter Speech Lab , mentoring PhD, MS, and undergraduate students in computational linguistics research. Scientific Awards and Grants: NSF EAGER Grant (2023) Google Cyber NYC Grant (2023) NSF AI Institute Grant (2023) Air Force Office of Scientific Research Grant (2020) Brown Institute Seed Grant (2020) Knight News Innovation Fellowship (2018) Teaching: Courses include Natural Language Processing (undergraduate/graduate), Computational Linguistics, Computer Theory, and advanced topics in spoken language processing at both Hunter College and Columbia University.

• Computational Linguistics
• Computer Science
• Machine Learning
• +۱ مورد دیگر

Noah A. Smith is an Adjunct Professor of Computer Science and Engineering at the University of Washington. His work focuses on computational linguistics, machine learning, and natural language processing. He holds a Ph.D. in Computer Science from Johns Hopkins University (2006). His research explores ethical AI applications, multimodal systems, and foundational aspects of language models. Key research areas include: Ethical considerations in NLP, such as detecting rights abuses through text analysis Efficient decoding and alignment strategies for large language models Large-scale evaluation frameworks for multitask and multimodal generation Understanding pretraining dynamics and data composition effects Recent work emphasizes transparency in language models (e.g., tracing outputs to training data) and improving alignment through human feedback. He has contributed to open-source projects like OLMo and Dolma, advancing reproducibility in NLP research. No awards explicitly listed in provided texts. No specific advising or grant details available, though extensive publication output indicates active research involvement.

• Systems and Network Security
• Applied Cryptography
• Cybersecurity
• +۹ مورد دیگر

Dr. Angelos D. Keromytis is the John H. Weitnauer, Jr. Endowed Chair Professor and Georgia Research Alliance (GRA) Eminent Scholar at the School of Electrical and Computer Engineering , Georgia Institute of Technology . He is a globally recognized leader in systems and network security and applied cryptography , with over 250 publications and 67 issued US patents. He is an elected Fellow of both the IEEE and ACM, and previously served as a Program Manager at DARPA and Program Director at NSF. Education: Ph.D. in Computer Science, University of Pennsylvania (2001) M.Sc. in Computer Science, University of Pennsylvania (1997) B.Sc. in Computer Science, University of Crete, Greece (1996) Research Interests: Dr. Keromytis's research spans a broad spectrum of cybersecurity topics, including: Systems and Network Security : He has led foundational work in secure systems design, intrusion detection, and network anomaly detection. Applied Cryptography : His work includes cryptographic protocols, secure communications, and privacy-preserving systems. Hardware and Side-Channel Security : He has pioneered techniques for detecting hardware Trojans using electromagnetic side-channels. Cloud and IoT Security : He has developed novel approaches to securing cloud services and IoT devices. Software Security : His work includes defenses against malware, return-oriented programming (ROP), and automated software patching. Scientific Awards: John H. Weitnauer, Jr. Endowed Chair Georgia Research Alliance (GRA) Eminent Scholar IEEE Fellow (2018) ACM Fellow (2017) ACM Distinguished Scientist (2012) DARPA Superior Public Service Medal DARPA Results Matter Award Advising and Grants: Dr. Keromytis has advised over 30 Ph.D. students and numerous postdocs. He has secured over $35M in research funding from agencies like DARPA, NSF, IARPA, ONR, and AFRL. His recent grants include: DARPA SMOKE : $22.7M for "Antikythera" cybersecurity framework NSF SaTC : $1.2M for mobile network anti-tracking architecture DARPA CHASE : $1.7M for network abuse behavioral engine DARPA OPS-5G : $7.3M for large-scale adversary defense ONR : $4.4M for dormant hardware Trojan detection Labs and Teams: He co-founded and co-directs the Center for Cyber Operations Enquiry and Unconventional Sensing (COEUS) at Georgia Tech. Previously, he founded and directed the Network Security Lab (NSL) at Columbia University, which produced foundational research in network security, intrusion detection, and software protection.

Kassem Fawazمشاهده پروفایل

استادیار

• Security & Privacy
• Machine Learning
• Mobile Computing
• +۵ مورد دیگر

Kassem Fawaz is an Assistant Professor in the Department of Electrical & Computer Engineering at the University of Wisconsin-Madison. His research focuses on security, privacy, and mobile computing, with applications in social robotics, generative AI, and adversarial machine learning. He teaches graduate-level courses including Advanced Computer Security, Master's Research, and Independent Study in Electrical & Computer Engineering. Education: PhD (2017) and MS (2011) from the University of Michigan, BE (2009) from the American University of Beirut His work addresses challenges in privacy-preserving analytics, model robustness, and ethical AI, leveraging commodity devices for secure systems. Recent publications explore social media algorithms, black-box attacks, and family dynamics in generative AI use. Key scientific awards include the NSF CAREER Award (2020), Caspar Bowden Award (2019), and multiple student travel grants from ACM, PETS, and USENIX. He has supervised graduate research projects and taught core security courses since 2023.

Sajedul Talukderمشاهده پروفایل

استادیار

• Cybersecurity
• Privacy-Preserving Technologies
• Machine Learning
• +۵ مورد دیگر

Dr. Sajedul Talukder is an Assistant Professor in the Department of Computer Science at The University of Texas at El Paso (UTEP), directing the SUPREME Lab. He holds a Ph.D. in Computer Science from Florida International University (2019) and has held prior faculty positions at Southern Illinois University (2021-2024) and Pennsylvania Western University (2019-2021). Education: Ph.D. in Computer Science, Florida International University (2019) M.S. in Computer Science, Florida International University (2018) B.S. in Computer Science and Engineering, Bangladesh University of Engineering and Technology (2014) Research Interests: Focuses on cybersecurity, privacy-enhanced machine learning, and AI-driven solutions for social good. Key areas include: Security and privacy in online systems Abuse detection in social networks Quantum security and distributed systems Federated learning for healthcare and industrial IoT His work emphasizes practical applications like AI for nuclear plant cybersecurity and mitigating sockpuppet attacks. Recent Article Trends: Recent publications highlight advancements in federated learning frameworks (e.g., SAFARI, FLASH), context-aware emotion detection (CAMERA), and AI-driven nuclear facility security (ContextGPT, AML-TIN). These contributions address privacy, scalability, and real-time threat monitoring. Awards & Grants: $500K NRC grant (2024) for AI-driven nuclear plant cybersecurity NSF CISE CRII Award ($157K) for sockpuppet defense IMEC/NIST grant ($99K) for industrial IoT security Best Paper Awards (ICEEICT 2014, ACM SAC 2022) Advising & Labs: Mentored over 40 students (K-12 to Ph.D.), including 2 recent M.S. graduates. Leads SUPREME Lab and affiliated with UTEP AI Institute and NSF IDEAS Center. Active in program committees for ASONAM, ICWSM, and CHI.

Lyle H. Ungarمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۷ مورد دیگر

Affiliations & Roles Professor of Computer and Information Science at University of Pennsylvania Faculty in Graduate Groups: Bioengineering (School of Engineering) Genomics & Computational Biology (School of Medicine) Operations, Information & Decisions (Wharton School) Psychology (School of Arts & Sciences) Research Affiliations: Annenberg Public Policy Center (Distinguished Fellow) Center for Cognitive Neuroscience Institute for Translational Medicine Research Interests Focuses on explainable AI, natural language processing (NLP), and machine learning applications in psychology and medicine. Key areas include: Language analysis for well-being and mental health Spectral methods for NLP (e.g., Eigenwords) Forecasting and decision-making models Bioinformatics and genomics Teaching Teaches advanced courses in Machine Learning, Deep Learning, and AI ethics, including: CIS 5200: Machine Learning CIS 5220: Deep Learning CIS 6200: Advanced Topics in Deep Learning Key Collaborations Works with interdisciplinary teams on projects like the Good Judgment Project (forecasting) and WWBP (Well-Being and Language). Collaborators include Martin Seligman (positive psychology), Dean Foster (statistics), and Michael Collins (NLP).