Find Academic Supervisors

Ankita SinghView profile

Researcher

• Machine Learning
• Data Science
• Computational Finance
• +3 more

Ankita Singh is a PhD candidate and Research Associate at Kühne Logistics University (KLU) , Hamburg, Germany, since 2023. Under the primary supervision of Prof. Dr. Alexander Himme and secondary supervision by Prof. Dr. Henrik Leopold, her research explores the intersection of machine learning, accounting, and marketing by applying advanced machine learning algorithms to forecast the influence of non-financial information from earnings calls on firm value. Bachelor of Engineering in Information Technology, Amaravati University (2006-2010) Master of Science in Computer Science and Engineering, Rajiv Gandhi Proudyogiki Vishwavidyalaya (2016-2018) Ankita’s research interests span Machine Learning , Data Science , and their applications in Computational Finance and Marketing Analytics . Her work leverages Artificial Intelligence and Computer Vision to detect facial emotions in real time using deep learning. The system, validated on the ADFES-BIV dataset, achieves 81.67% training accuracy in recognizing universal emotions (happy, sad, neutral, surprise, anger) and micro-emotions (contempt, embarrassment, fear, disgust, pride) via DCNN and Haar-cascade classifiers. Her prior industry experience as a Senior Software Engineer and Team Lead at Accenture Solutions Pvt Ltd (2011-2019) and internship at Pantech Solutions Pvt Ltd (2022-2023) highlight her expertise in software engineering and team leadership across financial and telecommunications sectors in London, Düsseldorf, and India.

Yun LinView profile

Associate Professor

• Automatic programming
• Software debugging
• Software testing
• +8 more

Yun Lin is an Associate Professor and Deputy Head of the Department of Computer Science and Technology at Shanghai Jiao Tong University's School of Computer Science. Prior to joining SJTU, Lin served as a Research Assistant Professor at the National University of Singapore working with Prof. Dong Jin Song. Lin leads the CoPhi ("Code Philia") research group, which focuses on the intersection of Software Engineering, AI, and Security. Lin's research spans three major areas: Automatic Programming (including code editing, software testing, and debugging), Explainable AI (focusing on representation interpretation and training data attribution), and Web Misinformation (particularly phishing and scam detection). The research has resulted in numerous tools including CoEdPilot for code editing recommendation, DeepDebugger for interactive debugging of deep classifiers, and Phishpedia for phishing webpage detection. Lin's recent publications demonstrate a strong trend toward integrating AI techniques, particularly large language models and vision language models, with traditional software engineering and security tasks. The work shows increasing sophistication in understanding project context, handling interactive nature of programming tasks, and addressing security challenges in the age of generative AI. Key themes include consistency-based approaches for anomaly detection, agent-based frameworks for complex tasks, and hybrid models that combine symbolic reasoning with neural approaches. ACM Distinguished Paper Award in ICSE'18 for "Towards Optimal Concolic Testing" Distinguished Reviewer Award in FSE'25 2nd prize Research Prototype Award in ChinaSoft'24 Lin advises a large team of PhD, Master's, and undergraduate students, with several publications co-authored with students appearing in top venues. Current research is supported by collaborations with National University of Singapore, particularly with Prof. Dong Jin Song, and includes projects on code editing, GUI testing, and phishing detection. The CoPhi group maintains active development of multiple research tools and datasets. The CoPhi research group under Lin's leadership focuses on building practical tools that bridge the gap between theoretical advances and real-world programming and security challenges. The group's work spans from fundamental program analysis techniques to applied security solutions, with an increasing emphasis on leveraging AI capabilities while maintaining explainability and reliability.

• Biomedical Research
• Cystitis, Interstitial
• Drug Delivery Systems
• +7 more

Darryl T. Martin is an Assistant Professor in the Department of Urology at the Yale School of Medicine and a member of the Yale Cancer Center. His research focuses on understanding the biological factors and molecular determinants that drive cancer progression and metastasis, particularly in urologic cancers. Dr. Martin is affiliated with the Cancer Signaling Networks program and the Janeway Society at Yale, demonstrating his integration into multiple research communities within the institution. Dr. Martin received his PhD from Memorial University of Newfoundland, where he trained as a cancer molecular biologist studying tumor growth and differentiation under the supervision of Drs. Robert Gendron and Hélène Paradis. He then completed postdoctoral training with Dr. Robert M. Weiss at Yale University School of Medicine, focusing on drug delivery and cancer progression, which laid the foundation for his current research program. Dr. Martin's research program investigates three main areas: defining distant metastasis by elucidating biologic factors and molecular determinants; modulating the tumor microenvironment to transform immunosuppressive conditions into immune-activated states; and enhancing tumor targeting using surface-modified nanoparticles. His work combines molecular biology, translational science, and nanomedicine to develop novel approaches for cancer treatment, with particular emphasis on prostate and bladder cancers. Analysis of Dr. Martin's recent publication record reveals a strong translational focus, bridging basic molecular mechanisms with clinical applications. His work spans genomic testing for prostate cancer, treatment optimization for bladder cancer variants, and nanoparticle-based drug delivery systems, demonstrating both breadth and depth in urologic oncology research. Dr. Martin is an active member of several professional organizations: American Association for Cancer Research (AACR) Society for Basic Urologic Research (SBUR) American Society for Biochemistry and Molecular Biology (ASBMB) The Martin Lab is currently funded by Department of Defense (DoD) and foundation grants, supporting research on cancer progression and metastasis. Dr. Martin collaborates extensively with clinical colleagues at Yale, reflecting the interdisciplinary nature of modern cancer research and his commitment to translating laboratory discoveries into clinical applications. Dr. Martin's laboratory focuses on developing practical applications for cancer treatment, particularly through nanoparticle systems that can deliver drugs to malignant tissues with high specificity. His research represents an important bridge between basic cancer biology and clinical oncology, with potential to improve outcomes for patients with urologic malignancies.

Agnes FlöelView profile

Professor

• Cognitive Neuroscience
• Sleep Physiology
• Brain Stimulation
• +7 more

Prof Dr Agnes Flöel is a Professor at the University of Greifswald Medical School, where she leads research at the intersection of cognitive neuroscience, sleep physiology, and brain stimulation. Her work focuses on understanding neural mechanisms underlying memory formation and cognitive decline in aging, with particular emphasis on sleep-related processes and non-invasive brain stimulation techniques. Her research interests center on sleep physiology , cognitive neuroscience , and neurostimulation . Dr. Flöel investigates how slow oscillations, spindles, and delta waves interact during sleep to support memory consolidation, particularly in older adults and those with cognitive impairment. Her work extends to developing interventions combining cognitive training with transcranial direct current stimulation (tDCS) to enhance cognitive function in aging and early Alzheimer's disease. She also contributes to methodological advancements in sleep staging through deep learning approaches and addresses technical challenges in neuroimaging. Dr. Flöel's publication record demonstrates consistent productivity with multiple high-impact papers annually, primarily focused on sleep neuroscience, brain stimulation, and cognitive aging. Her work shows strong collaborative patterns with researchers across Germany, particularly within the SFB 1315 research consortium. Recent publications (2022-2024) increasingly incorporate computational approaches, deep learning, and multimodal neuroimaging to address fundamental questions about neural plasticity and memory. Her research has been supported through the Collaborative Research Center 1315 (SFB 1315) funded by the German Research Foundation, focusing on neuronal circuits in aging. Dr. Flöel serves as principal investigator for multiple clinical trials examining brain stimulation approaches for cognitive enhancement in older adults and those with mild cognitive impairment. Dr. Flöel leads a research group investigating sleep-brain interactions in aging, collaborating closely with computational neuroscientists, neurologists, and psychologists. Her team utilizes multimodal approaches including EEG, MRI, and behavioral assessments to understand neural mechanisms of cognitive decline and potential interventions.