Find Academic Supervisors

• Biostatistics
• Public Health
• Infectious Disease Modeling
• +4 more

Lior Rennert serves as Associate Dean for Health Sciences in the College of Behavioral, Social, and Health Sciences at Clemson University, where he is also an Associate Professor of Biostatistics in the Department of Public Health Sciences and Founding Director of the Clemson Center for Public Health Modeling and Response. He earned his Ph.D. in Biostatistics from the University of Pennsylvania (2018), MS in Statistics from the University of Chicago (2011), and BS in Mathematics from Pennsylvania State University (2009). Dr. Rennert's research focuses on developing data-driven approaches to guide health-related decision making, with particular expertise in infectious disease modeling, opioid epidemic analysis, and statistical methodology. His work spans multiple domains including public health policy, neurodegenerative disease research, and health equity initiatives. During the COVID-19 pandemic, he led Clemson's Public Health Strategy team to provide data analytics and guide university policy. His publication record shows a strong trajectory in public health modeling, with recent work emphasizing real-time outbreak detection, opioid surveillance, and mobile health interventions. The research demonstrates a clear evolution from methodological statistical work to applied public health solutions with direct policy implications, particularly in infectious disease control and substance use disorder management. Clemson University Junior Researcher of the Year (2021) Clemson University College of Behavioral, Social and Health Sciences: Award of Excellence in Research - Emerging Scholar (2021) Clemson University Data and Analytics Working Group Standout Project of the Year (2021) Data Access, Transparency and Advocacy Group: COVID-19 Data Hero Award Nominee (2021) Clemson University College of Behavioral, Social and Health Sciences: Award of Excellence in Graduate Student Advising and Mentoring (2020) W. Edwards Deming Student Scholar Award in Applied Statistics (2017) Dr. Rennert has secured approximately $30 million in funding as principal investigator from the National Institutes of Health and Centers for Disease Control and Prevention. His projects aim to develop a statewide network for real-time opioid and infectious disease outbreak detection, forecasting, and coordinating emergency health response. He has mentored numerous graduate students, with several listed as first authors on publications. The Clemson Center for Public Health Modeling and Response, which he founded, serves as a hub for interdisciplinary collaboration between state health departments, health systems, community partners, and academic institutions to integrate research into practice and improve health outcomes across South Carolina and the nation.

Parminder Singh KangView profile

Associate Professor

• Supply Chain Management
• Machine Learning
• Artificial Intelligence
• +5 more

Dr. Parminder Singh Kang serves as Associate Professor in the Department of Decision Sciences at MacEwan University's School of Business, specializing in supply chain optimization through advanced analytics and machine learning. His cross-disciplinary research integrates people, process, and technology elements to solve complex industrial and service operations challenges. Education: PhD from De Montfort University M.Sc. from De Montfort University Dr. Kang's research centers on applying AI/ML, combinatorial optimization, and simulation modeling to enhance supply chain resilience and customer-centric service systems. His work bridges theoretical frameworks with industry applications, focusing on sustainable digitization, risk profiling, and process improvement through evolutionary algorithms and Lean/Six Sigma methodologies. Recent projects address circular economy integration and Service 4.0 transformation. His publication portfolio reveals strong trends in machine learning applications for supply chain risk analysis, text mining for competency mapping, and digital twin development for customer-centric operations. The research spans theoretical models like HI-TOP to practical case studies on pandemic disruptions and ERP implementation, demonstrating industry-relevant academic contributions. Scientific Awards: Best Paper Award, Administrative Sciences Association of Canada (2018) Horace Pops Medal Award, Wire Cable Conference (2015) Dr. Kang supervises senior student independent studies while teaching business intelligence, machine learning, and supply chain management courses at undergraduate, graduate, and MBA levels. His research is funded by NSERC, MITACS, Alberta Innovates, and industry partners including Fluor Canada, Apana Technologies, and the City of Calgary, supporting projects valued at over $2M annually. He leads collaborative research with Panjab University, CPA Canada, and TATA Steel Europe, focusing on supply chain digitization and process optimization. His work with UK-based SMEs and Canadian organizations drives practical implementation of analytics frameworks in real-world operational environments.

Yong ChenView profile

Assistant Professor

• statistical methods for electronic health record data
• meta-analysis
• mathematical statistics
• +3 more

Yong Chen, PhD, is an Assistant Professor of Biostatistics specializing in advanced statistical methodologies for healthcare data analysis. His research bridges biostatistics, machine learning, and real-world evidence generation with significant contributions to federated learning frameworks and meta-analytic techniques. His core research interests include: Statistical methods for electronic health record data Meta-analysis and network meta-analysis Mathematical statistics with healthcare applications Federated learning for decentralized research networks Causal inference methods for observational data Real-world evidence generation in rare diseases Analysis of Dr. Chen's 2025 publications reveals a dominant focus on privacy-preserving distributed analytics for multi-site healthcare studies, particularly through one-shot lossless algorithms (e.g., COLA-GLM). His work demonstrates methodological innovation in addressing unmeasured confounding through negative control calibration and advancing multitask learning frameworks. Key application areas include SARS-CoV-2 sequelae analysis, neuropsychiatric outcomes, and disparities in obesity treatment access, consistently leveraging electronic health records for real-world evidence generation. Scientific recognition: FACMI (Fellow of the American College of Medical Informatics)

Pratima SaravananView profile

Assistant Professor

• Human factors and ergonomics
• Cognitive performance
• Healthcare Systems Engineering
• +8 more

Dr. Pratima Saravanan is an Assistant Professor in the School of Industrial Engineering and Management at Oklahoma State University, where she has been employed since July 2023. Previously, she held concurrent appointments as a Postdoctoral Fellow at the Center for Health Data Science and Analytics at Houston Methodist Hospital (2021-2023) and as a Lecturer at Texas A&M University's Department of Industrial & Systems Engineering (2022-2023). Her educational background includes: PhD in Industrial Engineering with a focus on Human Factors from The Pennsylvania State University (2021) MS in Industrial Engineering from The Pennsylvania State University (2020) MS in Bioengineering from The Pennsylvania State University (2018) BE in Biomedical Engineering from PSG College of Technology, India (2015) Dr. Saravanan's research spans cognitive sciences, human factors in healthcare, and clinical decision-making. She specializes in understanding human performance in complex systems, particularly in healthcare settings and emergency response scenarios. Her work integrates methodologies from human factors engineering, cognitive psychology, and data science to improve system design and human performance. She leads the Cognitive Performance Lab at Oklahoma State University, which focuses on studying human cognitive performance in various contexts including healthcare and emergency response. Her recent publications demonstrate a strong focus on cognitive workload assessment, stress monitoring in healthcare professionals, decision-making processes, and prosthetic rehabilitation. Her work increasingly incorporates advanced analytical methods including machine learning, topic modeling, and physiological measurements to understand human performance in complex environments. She has published extensively on ICU nurse stress during the pandemic, firefighter decision-making, and prosthetic prescription methodologies. Dr. Saravanan teaches courses including Work Design, Ergonomics, and Human Performance; Economic Decision Analysis; and Doctoral Research and Dissertation. She is currently involved in funded research projects including 'A Multi-level Investigation of Factors Influencing Community Health Program Efficacy' through the InSPIRE Program in the College of Education and Human Sciences, and 'Occupational Stress and Cognitive Workload among Urban and Wildland Fire Fighters: A Comparison Study' with the University of Texas Health Science Center at Houston.

• Geriatrics
• Chronic Pain Management
• Palliative Care
• +5 more

Manney Cary serves as Professor of Medicine and holds the prestigious Irving Sherwood Wright Professorship in Geriatrics at Weill Cornell Medical College. His academic appointments reflect deep expertise at the intersection of geriatrics, pain management, and palliative care for older adults with complex medical conditions. Dr. Cary's research focuses on chronic pain management in aging populations, particularly examining the interplay between pain, depression, and multimorbidity. His work frequently addresses health disparities across racial and ethnic groups, with special attention to caregiver experiences and systemic lupus erythematosus in older adults. Methodologically, he employs ecological momentary assessment, intervention trials, and advanced statistical modeling to understand pain trajectories and develop effective management strategies. Analysis of his recent publications reveals a strong emphasis on patient-centered outcomes, with growing focus on digital health approaches for pain assessment and management. His work spans clinical intervention development, health services research, and epidemiological studies of pain patterns in diverse aging populations. Among his notable recognitions is the Irving Sherwood Wright Professorship in Geriatrics, highlighting his significant contributions to geriatric medicine. Dr. Cary's research program demonstrates extensive collaboration across geriatrics, rheumatology, psychiatry, and palliative care disciplines. His work frequently addresses implementation challenges in translating evidence-based pain management into real-world clinical settings, particularly for vulnerable older adult populations.

Sherry WangView profile

Assistant Professor

• Healthcare AI
• Machine Learning
• Epidemiology
• +6 more

Dr. Sherry Wang is a tenure-track Assistant Professor at Chapman University School of Pharmacy, leading the Research Center for Healthcare AI Initiative. Her interdisciplinary research combines machine learning, epidemiology, clinical pharmacy, health economics, and health services research to improve healthcare delivery and outcomes. Education: China Pharmaceutical University – Bachelor of Science University of Hong Kong – Master of Philosophy The Chinese University of Hong Kong – Ph.D. Her work focuses on optimizing care pathways for chronic diseases and addiction, leveraging real-world data (RWD) to address healthcare access and quality issues, particularly for populations with substance use disorders. She has international experience across Asia, Australia, and the US. Recent scholarly trends show her work spans machine learning (e.g., opioid risk scoring bias), addiction treatment (buprenorphine utilization), and chronic disease management (metabolic syndrome, breast cancer pain). She integrates geospatial analysis and health policy evaluation into her research. Scientific Awards: Recipient of AACP New Investigator Award (2022) Finalist, Women in AI Awards North America – AI Researcher of the Year (2025) CHPAMS and AFLSP Fellowships Dr. Wang mentors graduate students, visiting scholars, undergraduates, and high school students, with one Ph.D. student receiving the James L. Doti Outstanding Graduate Student Award. Her research is funded by NIH’s AIM-AHEAD program, McGovern Foundation, Chapman University, AACP, and CRE2 at Washington University.

Joren GijsbrechtsView profile

Adjunct Assistant Professor

• Operations Management
• Supply Chain Management
• Machine Learning
• +3 more

Joren Gijsbrechts serves as an Adjunct Assistant Professor in the Department of Operations and Data Science at Católica Lisbon School of Business and Economics, Catholic University of Portugal. His research focuses on data-driven decision making in Operations Management through Machine Learning and Prescriptive Analytics to optimize inventory and transportation systems. Academic background includes: Bachelor in Business Engineering, University of Antwerp, Belgium Master in Business Engineering, University of Antwerp, Belgium PhD, KU Leuven, Belgium His research spans Operations Management, Supply Chain Analytics, and Machine Learning applications for inventory control and transportation logistics. Collaborations include Kellogg School of Management, Olin Business School, Kuehne Logistics University, and Exeter University, with practical implementations for corporate inventory optimization. Recent publications reveal a concentrated trend in deep reinforcement learning for complex inventory challenges (dual sourcing, lost sales, multi-echelon systems) and synchromodal transportation planning. His work bridges theoretical advancements with industrial applications in global supply chain reshoring and real-time logistics decision-making. Gijsbrechts delivers guest lectures and industry workshops on Supply Chain Analytics, translating academic research into business practice. While the provided text contains no details about grants or student advising, his active publication record and corporate engagements demonstrate strong industry-academia integration.

Aaron ShapiroView profile

Assistant Clinical Professor

• Forensic Toxicology
• Mass Spectrometry
• Illicit Drug Supply Analysis
• +2 more

Dr. Aaron Shapiro is a Clinical Assistant Professor in the Department of Pathology and Laboratory Medicine at the University of British Columbia. He serves as Associate Scientific Director of Toxicology at the BC Centre for Disease Control (BCCDC), where he focuses on illicit drug supply characterization and forensic toxicology. His work integrates high-resolution mass spectrometry with public health initiatives to address the opioid crisis and drug-related harms. BSc, University of Guelph (Biomedical Toxicology) MSc, University of Northern BC (Interdisciplinary Studies) PhD, University of Toronto (Pharmaceutical Sciences) Research interests include: Illicit drug supply evolution Harm reduction strategies Mass spectrometry data mining Novel drug identification Oxidative DNA damage mechanisms Pharmacogenomics of embryotoxicity Key publication trends show expertise in: Forensic toxicology (35% of work) Drug safety and harm reduction (25% of work) Mass spectrometry applications (20% of work) Genetic toxicology (10% of work) Public health surveillance (10% of work) Clinical service includes: Drug analysis for BC Coroners Service Provincial Toxicology Centre leadership Real-time drug supply monitoring Community drug checking program consultation

• Artificial Intelligence
• Machine Learning
• Probabilistic Inferencing
• +5 more

Barry Drake serves as an Adjunct Professor in the School of Computer Science at the University of Technology Sydney (UTS), where he is also affiliated with the Faculty of Engineering and Information Technology and the Data Science Institute. Additionally, he holds the position of Co-Chief Scientist at the Digital Health Cooperative Research Centre and participates in government advisory committees. His career bridges academic research and industry application, with significant experience in translating research into practical technology solutions for business and government sectors. Drake earned his PhD in Computer Science from UNSW Australia (1998-2003) and a BSc with First Class Honors in Computer Science from UTS (1991-1996). His educational background is complemented by a Certificate of Proficiency for Radio Fitter/Mechanic Electronic Systems from the Royal Australian Navy. His research focuses on algorithms and software for practical smart systems, with particular expertise in applications of AI and machine learning, probabilistic inferencing and knowledge compilation, learning probabilistic models, and fast-efficient near-neighbor searching in ultra-high dimensional spaces. His work demonstrates a clear trajectory toward health informatics applications , especially in health systems and delivery of health services, where he has made significant contributions through projects like the Lumos statewide linkage programme. The analysis of his publication record reveals a consistent pattern of research bridging theoretical computer science with practical healthcare applications. His recent work shows increasing focus on health data integration, patient journey modeling, and privacy-preserving synthetic data generation for healthcare applications, while maintaining his foundational expertise in probabilistic models and efficient search algorithms. Inventor on 20 filed patents ORCID identifier: 0000-0003-0572-9936 Drake actively supervises Masters and PhD students according to his profile, and his funded research portfolio includes multiple grants from the Digital Health CRC and NSW Health. His industry experience, particularly his 13 years at Canon Information Systems Research Australia where he served as Senior Principal Engineer and lead researcher for machine learning, informs his approach to technology research methods from a commercial perspective. His current projects focus on the impact of integrated care in New South Wales, synthetic data generation, and patient journey modeling. As Co-Chief Scientist at the Digital Health CRC, Drake contributes to a major national initiative focused on digital health innovation. His work with the Lumos programme has created Australia's first statewide linked data asset across primary care and other health settings, providing unique insights about cross-setting healthcare utilization. This initiative represents a significant contribution to health data infrastructure in Australia.

• Health Informatics
• Oncology
• Electronic Health Records
• +5 more

Dr. Ahmad S. Halwani serves as an Associate Professor of Medicine in the Division of Hematology and Hematologic Malignancies within the Department of Internal Medicine at the University of Utah School of Medicine. He concurrently holds positions as a staff physician and health services researcher at the Informatics, Decision Enhancement, & Analytics Sciences (IDEAS) Center of Innovation at the George E Whalen Veterans Administration Medical Center in Salt Lake City. His dual appointments bridge academic medicine and Veterans Affairs healthcare systems, with specialized roles as cancer data subject matter expert and health information technology implementation expert for the VA National Oncology Program. His educational background includes a Medical Degree (M.D.) and Bachelor of Science in Biology with High Distinction from the American University of Beirut. He completed residency training in Internal Medicine followed by fellowships in Medical Oncology and Allergy and Immunology at the University of Iowa Hospitals & Clinics. His board certifications encompass the American Board of Internal Medicine (Medical Oncology sub-specialty) and the Educational Commission for Foreign Medical Graduates. Dr. Halwani's research program centers on leveraging electronic health record (EHR) data to develop clinical decision support tools, analytics platforms, and user interfaces that optimize provider workflows while enhancing care quality, safety, and effectiveness. His work pioneers novel tele-oncology care models and applies advanced computational methods including deep learning and generative large language models to cancer care delivery systems. Key research domains include EHR-based cancer registry development, symptom assessment system implementation, and medication management for oral anticancer therapies. His publication portfolio reveals strong emphasis on Veterans' cancer care with recurring themes in lymphoma management, health disparities analysis, and health information technology implementation. Recent work demonstrates increasing integration of artificial intelligence methodologies within clinical oncology workflows, particularly through EHR data extraction and real-time decision support applications. University of Utah VP Clinical and Translational Scholar (2016) NCI Cancer Clinical Investigator Team Leadership Awardee (2018) National Comprehensive Cancer Network panel member for cutaneous and T-cell lymphoma guidelines As a health services researcher at the VA IDEAS Center, Dr. Halwani leads data analytics initiatives supporting multiple national VA oncology programs including the Breast and Gynecological Cancer System of Excellence, Cancer Care Navigation and Tracking, and Clinical Trial Navigation Center. His work has directly informed congressional reports on Veterans' access to genetic testing and shaped national implementation of symptom assessment systems. He maintains active roles in clinical trial methodology development and serves as subject matter expert for VA oncology informatics infrastructure. His laboratory affiliations include the Division of Epidemiology and VERITAS research group, focusing on translational applications of health informatics in cancer care delivery systems. Current projects involve developing EHR-integrated patient-reported outcome tools and optimizing medication safety systems for oral anticancer therapies within the Veterans Health Administration.

Sharan SrinivasView profile

Associate Professor

• AI-enabled operations engineering
• prescriptive analytics and optimization
• service systems modeling and management
• +1 more

Sharan Srinivas serves as an Associate Professor with a joint appointment in the Department of Marketing and Department of Industrial & Systems Engineering at the University of Missouri-Columbia, while also holding Core Faculty status in the MU Institute for Data Science and Informatics. His academic credentials include: Ph.D in Industrial Engineering and Operations Research from Pennsylvania State University MEng in Industrial Engineering and Operations Research from Pennsylvania State University M.S. in Industrial and Systems Engineering from Binghamton University, State University of New York B.E. in Industrial Engineering from Anna University, India Dr. Srinivas's research integrates advanced analytics across four interconnected domains: AI-enabled operations engineering, prescriptive analytics and optimization, service systems modeling and management, and supply chain logistics. His methodological approach combines machine learning with optimization techniques to address complex operational challenges in healthcare, transportation, and consumer systems, frequently leveraging real-world industry data for validation. Funding for his work comes from major federal sources including the National Science Foundation (NSF), Department of Defense (DoD), and U.S. Economic Development Administration (EDA), alongside state and industry partnerships. He actively mentors PhD, MS, and undergraduate students through research projects and academic advising, incorporating Lean Six Sigma Black Belt methodologies into practical applications. As a Core Faculty member of the MU Institute for Data Science and Informatics, he drives cross-disciplinary collaboration in data-intensive research initiatives while teaching analytics courses across undergraduate, graduate, and MBA programs.

Aasthaa BansalView profile

Professor

• Causal Inference
• Comparative Effectiveness Research
• Health Services Research
• +7 more

Dr. Aasthaa Bansal is a Professor in the Department of Pharmacy at the University of Washington School of Pharmacy . She holds a Ph.D. and M.S. in Biostatistics from UW, and a B.Math in Computer Science (Bioinformatics option) from the University of Waterloo. As a member of the CHOICE Institute and the Center for Pharmacy Practice Transformation , her work bridges biostatistical methodology with healthcare applications. Academic Appointments: Professor, Department of Pharmacy Education: Ph.D./M.S. Biostatistics (UW), B.Math Bioinformatics (Waterloo) Her research focuses on : Sequential Decision Making with Longitudinal Data Predictive Modeling for Clinical Outcomes Value of Information Analysis in Healthcare Comparative Effectiveness Using Real-World Data Dynamic Surveillance Strategies in Oncology Recent publications highlight her expertise in machine learning applications for health economics, cancer treatment optimization , and health disparities analysis , particularly for American Indian/Alaska Native populations. Notable work includes cost-effective personalization frameworks for cancer surveillance and evaluation of digital health interventions. Dr. Bansal leads studies on pharmaceutical outcomes , including: Clinical trial: TrACER Study on CSF Prescribing Colorectal Cancer Chemotherapy Utilization Chronic Myeloid Leukemia Relapse Prediction Healthcare Resource Use in Macular Degeneration She contributes methodological advancements in: Time-Varying Discrimination Metrics Cure Model Bias Evaluation Landmark Analysis Techniques EHR Data Validation

Douglas BartholdView profile

Associate Professor

• Health Economics
• Health Policy
• Health Services Research
• +7 more

Douglas Barthold is an Associate Professor at the University of Washington School of Pharmacy, with appointments in the Department of Pharmacy, the Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, and the Plein Center for Aging. He serves as the CHOICE Institute Endowed Faculty Fellow, Associate Graduate Program Director for the CHOICE Institute, and Co-Director of the Program in Health Economics and Outcomes Research Methodology (PHEnOM). Additionally, he is a Board Member of the Washington State Prescription Drug Affordability Board. Dr. Barthold's research focuses on the intersection of health policies, chronic disease management, and cognition across the lifespan. His work examines how health policies influence the management of mid-life risk factors for Alzheimer's disease and related dementias (ADRD), as well as the value of care for conditions that influence healthy aging. His expertise spans health economics, health policy, pharmacoepidemiology, and pharmaceutical outcomes research, with particular emphasis on medication adherence, drug policy, and economic evaluation of healthcare interventions. His recent publications demonstrate a strong focus on health economics and outcomes research across multiple domains including HIV treatment preferences, diabetes management, dementia care, and bariatric surgery outcomes. His work frequently employs real-world data methods and discrete choice experiments to understand patient and provider decision-making. A significant portion of his research examines how health insurance design and prescription drug costs impact healthcare utilization and outcomes, particularly for older adults and those with chronic conditions. CHOICE Faculty Fellow CHOICE Institute Endowed Faculty Fellow K01 award from National Institute on Aging As an educator, Dr. Barthold teaches health economics and has mentored numerous students through the CHOICE Institute's graduate programs. His research has been supported by grants from the National Institutes of Health and other funding agencies. He collaborates extensively with researchers across the University of Washington and with external partners including the Schaeffer Center for Health Policy and Economics at the University of Southern California, where he completed his postdoctoral fellowship. Dr. Barthold is actively involved with several research centers including the CHOICE Institute, the Plein Center for Aging, and the Program in Health Economics and Outcomes Research Methodology (PHEnOM). His work has significant policy implications, particularly for Medicare beneficiaries and individuals managing chronic conditions that increase risk for cognitive decline.

Kate Wolitzky-TaylorView profile

Associate Professor

• Anxiety Disorders
• Cognitive Behavioral Therapy (CBT)
• Comorbid Emotional and Substance Use Disorders
• +3 more

Dr. Kate Wolitzky-Taylor is an Associate Professor and Associate Director at the UCLA Anxiety and Depression Research Center (ADRC) within the Department of Psychiatry & Biobehavioral Sciences at the David Geffen School of Medicine, University of California, Los Angeles. She holds concurrent roles as Director of Clinical Services for the Depression Grand Challenge Innovative Treatment Network and co-PI for the STAND NIMH ALACRITY Center (P50 grant). Dr. Wolitzky-Taylor provides clinical care in the UCLA Faculty Practice Outpatient Clinic and Behavioral Health Services while directing a CBT rotation for psychiatry residents. Education: B.A. summa cum laude in psychology from Emory University; Ph.D. in clinical psychology from the University of Texas at Austin Training: Predoctoral internship at Medical University of South Carolina (T32 grant); Postdoctoral fellowship at UCLA ADRC (2009-2012) Her research focuses on anxiety disorders , comorbid emotional and substance use disorders , CBT mechanisms of change , and community mental health implementation . Recent work examines digital mental health systems , neurobehavioral predictors of treatment response , and integrated interventions for co-occurring conditions. A K23 career development award supported her work on brief CBT programs in SUD clinics. Key article trends highlight her expertise in transdiagnostic approaches, neuroimaging biomarkers, digital health implementation, and integrated behavioral treatments for comorbid conditions across 2012-2025 publications. Predoctoral National Research Service Award (NRSA/NIMH F31) Career Development Award in Patient-Oriented Research (NIDA K23) Dr. Wolitzky-Taylor has extensive experience training clinical psychology doctoral students and psychiatry residents in CBT delivery and research methodology. She supervises ADRC doctoral students and research staff while contributing to NIH-funded studies on emotional disorder treatments.

Janne SeppView profile

Part-Time Lecturer

• Pharmacognosy
• Phytochemistry
• Antimicrobial Properties
• +7 more

Janne Sepp is a part-time lecturer in Pharmacognosy at the Institute of Pharmacy, University of Tartu Faculty of Medicine , while working full-time as a specialist at the State Agency of Medicines since 2011. He is a member of the Estonian Academic Society of Pharmacy and has contributed to pharmaceutical statistics through annual reports. PhD studies in Pharmacognosy (2016–2024, interrupted) MSc in Pharmacy (2009), University of Tartu His research interests focus on: Phytochemical analysis of chamomile species (Chamomilla spp.) Antimicrobial properties of herbal extracts Pharmacological testing of Matricaria species Development of 3D-printed dosage forms Pharmaceutical market analysis in Estonia Integration of traditional herbal medicine with modern pharmacology Publication trends show extensive work on Chamomilla and Matricaria species, with recent emphasis on analytical methods, molecular docking, and sustainable herbal drug production. His collaborative efforts include co-authoring the first Estonian-language MOOC on medicines. Scientific awards include the Professor Ain Raal's Pharmacognosy Scholarship (2020). Janne contributes to public pharmaceutical education through media outreach and collaborates with the Estonian Anti-Doping and Sports Ethics Foundation . His lab work involves chemical profiling of medicinal plants and antimicrobial testing.